[](https://CRAN.R-project.org/package=nflfastR)
[](https://CRAN.R-project.org/package=nflfastR)
[](https://nflfastr.com/)
[](https://github.com/nflverse/nflfastR/actions)
[](https://lifecycle.r-lib.org/articles/stages.html#stable)
[](https://discord.com/invite/5Er2FBnnQa)
`nflfastR` is a set of functions to efficiently scrape NFL play-by-play data. `nflfastR` expands upon the features of nflscrapR:
* The package contains NFL play-by-play data back to 1999
* As suggested by the package name, it obtains games **much** faster
* Includes completion probability (`cp`), completion percentage over expected (`cpoe`), and expected yards after the catch (`xyac_epa` and `xyac_mean_yardage`) in play-by-play going back to 2006
* Includes drive information, including drive starting position and drive result
* Includes series information, including series number and series success
* Hosts [a release of play-by-play data going back to 1999](https://github.com/nflverse/nflverse-data/releases/tag/pbp) for very quick access
* Features models for Expected Points, Win Probability, Completion Probability, and Yards After the Catch (see section below)
* Includes a function `update_db()` that creates and updates a database
We owe a debt of gratitude to the original [`nflscrapR`](https://github.com/maksimhorowitz/nflscrapR) team, Maksim Horowitz, Ronald Yurko, and Samuel Ventura, without whose contributions and inspiration this package would not exist.
## Installation
The easiest way to get nflfastR is to install it from [CRAN](https://cran.r-project.org/package=nflfastR) with:
```{r, eval=FALSE}
install.packages("nflfastR")
```
To get a bug fix or to use a feature from the development version, you can install the development version of nflfastR either from [GitHub](https://github.com/nflverse/nflfastR/) with:
``` {r eval = FALSE}
if (!require("pak")) install.packages("pak")
pak::pak("nflverse/nflfastR")
```
or prebuilt from the [development repo](https://nflverse.r-universe.dev) with:
```{r eval = FALSE}
install.packages("nflfastR", repos = c("https://nflverse.r-universe.dev", getOption("repos")))
```
## Usage
We have provided some application examples in the **[Getting Started](https://nflfastr.com/articles/nflfastR.html)** article. However, these require a basic knowledge of R. For this reason we have the **[nflfastR beginner's guide](https://nflfastr.com/articles/beginners_guide.html)**, which we recommend to all those who are looking for an introduction to nflfastR with R.
You can find column names and descriptions in the **[Field Descriptions](https://nflfastr.com/articles/field_descriptions.html)** article, or by accessing the `field_descriptions` dataframe from the package.
## Data access
Even though `nflfastR` is very fast, **we recommend downloading the data from [here](https://github.com/nflverse/nflverse-data/releases/tag/pbp) or using the `nflreadr` package**. These data sets include play-by-play data of complete seasons going back to 1999 and are updated nightly during the season. The files contain both regular season and postseason data, and one can use game_type or week to figure out which games occurred in the postseason.
## nflfastR models
`nflfastR` uses its own models for Expected Points, Win Probability, Completion Probability, and Expected Yards After the Catch. To read about the models, please see [this post on Open Source Football](https://opensourcefootball.com/posts/2020-09-28-nflfastr-ep-wp-and-cp-models/). For a more detailed description of the motivation for Expected Points models, we highly recommend this paper [from the nflscrapR team located here](https://arxiv.org/pdf/1802.00998).
Here is a visualization of the Expected Points model by down and yardline.
``` {r epa-model, warning = FALSE, message = FALSE, results = 'hide', fig.keep = 'all', dpi = 600, echo=FALSE, eval = FALSE}
# This code was used to create the ep model image. Since we don't want to include
# the resulting png file in the package for file size reasons it was uploaded to
# the nflfastR repo and embedded remotely with the next chunk
library(tidyverse)
df <- nflreadr::load_pbp(2014:2019) |>
filter(!is.na(posteam) & !is.na(ep), !is.na(down)) |>
select(ep, down, yardline_100, air_yards, pass_location, cp)
df |>
ggplot(aes(x = yardline_100, y = ep, color = as.factor(down))) +
geom_smooth(size = 2) +
labs(x = "Yards from opponent's end zone",
y = "Expected points value",
color = "Down",
title = "Expected Points by Yardline and Down") +
theme_bw() +
scale_y_continuous(expand=c(0,0), breaks = scales::pretty_breaks(10)) +
scale_x_continuous(expand=c(0,0), breaks = seq(from = 5, to = 95, by = 10)) +
theme(
plot.title = element_text(size = 18, hjust = 0.5),
plot.subtitle = element_text(size = 16, hjust = 0.5),
axis.title = element_text(size = 18),
axis.text = element_text(size = 16),
legend.text = element_text(size = 16),
legend.title = element_text(size = 16),
legend.position = c(.90, .80)) +
annotate("text", x = 14, y = -2.2, size = 3, label = "2014-2019 | Model: @nflfastR")
```
```{r echo=FALSE, fig.align='center', fig.cap='', out.width='100%'}
knitr::include_graphics('man/figures/readme-epa-model-1.png')
```
Here is a visualization of the Completion Probability model by air yards and pass direction.
``` {r cp-model, warning = FALSE, message = FALSE, results = 'hide', fig.keep = 'all', dpi = 600, echo=FALSE, eval = FALSE}
# This code was used to create the cp model image. Since we don't want to include
# the resulting png file in the package for file size reasons it was uploaded to
# the nflfastR repo and embedded remotely with the next chunk
df |>
filter(!is.na(cp), between(air_yards, -5, 45)) |>
mutate(pass_middle = if_else(pass_location == "middle", "Yes", "No")) |>
ggplot(aes(x = air_yards, y = cp, color = as.factor(pass_middle))) +
geom_smooth(size = 2) +
labs(x = "Air yards",
y = "Expected completion %",
color = "Pass middle",
title = "Expected Completion % by Air Yards and Pass Direction") +
theme_bw() +
scale_y_continuous(expand=c(0,0), breaks = scales::pretty_breaks(5)) +
scale_x_continuous(expand=c(0,0)) +
theme(
plot.title = element_text(size = 18, hjust = 0.5),
plot.subtitle = element_text(size = 16, hjust = 0.5),
axis.title = element_text(size = 18),
axis.text = element_text(size = 16),
legend.text = element_text(size = 16),
legend.title = element_text(size = 16),
legend.position = c(.80, .80)) +
annotate("text", x = 2, y = .32, size = 3, label = "2014-2019 | Model: @nflfastR")
```
```{r echo=FALSE, fig.align='center', fig.cap='', out.width='100%'}
knitr::include_graphics('man/figures/readme-cp-model-1.png')
```
`nflfastR` includes two win probability models: one with and one without incorporating the pre-game spread.
## Special thanks
* To Nick Shoemaker for [finding and making available JSON-formatted NFL play-by-play back to 1999](https://github.com/CroppedClamp/nfl_pbps) (`nflfastR` uses this source for 1999 and 2000 and previously also used it for 2001-2010)
* To Lau Sze Yui for developing a scraping function to access JSON-formatted NFL play-by-play beginning in 2001
* To Aaron Schatz and FTN Fantasy for providing charting data to correctly mark scrambles in the 1999-2005 seasons
* To Lee Sharpe for curating a resource for game information
* To Timo Riske, Lau Sze Yui, Sean Clement, and Daniel Houston for many helpful discussions regarding the development of the new `nflfastR` models
* To Zach Feldman and Josh Hermsmeyer for many helpful discussions about CPOE models as well as Peter Owen for many helpful suggestions for the CP model
* To Florian Schmitt for the logo design
* The many users who found and reported bugs in `nflfastR` 1.0
* And of course, the original [`nflscrapR`](https://github.com/maksimhorowitz/nflscrapR) team, Maksim Horowitz, Ronald Yurko, and Samuel Ventura, whose work represented a dramatic step forward for the state of public NFL research
================================================
FILE: README.md
================================================
# **nflfastR**
[](https://CRAN.R-project.org/package=nflfastR)
[](https://CRAN.R-project.org/package=nflfastR)
[](https://nflfastr.com/)
[](https://github.com/nflverse/nflfastR/actions)
[](https://lifecycle.r-lib.org/articles/stages.html#stable)
[](https://discord.com/invite/5Er2FBnnQa)
`nflfastR` is a set of functions to efficiently scrape NFL play-by-play
data. `nflfastR` expands upon the features of nflscrapR:
- The package contains NFL play-by-play data back to 1999
- As suggested by the package name, it obtains games **much** faster
- Includes completion probability (`cp`), completion percentage over
expected (`cpoe`), and expected yards after the catch (`xyac_epa` and
`xyac_mean_yardage`) in play-by-play going back to 2006
- Includes drive information, including drive starting position and
drive result
- Includes series information, including series number and series
success
- Hosts [a release of play-by-play data going back to
1999](https://github.com/nflverse/nflverse-data/releases/tag/pbp) for
very quick access
- Features models for Expected Points, Win Probability, Completion
Probability, and Yards After the Catch (see section below)
- Includes a function `update_db()` that creates and updates a database
We owe a debt of gratitude to the original
[`nflscrapR`](https://github.com/maksimhorowitz/nflscrapR) team, Maksim
Horowitz, Ronald Yurko, and Samuel Ventura, without whose contributions
and inspiration this package would not exist.
## Installation
The easiest way to get nflfastR is to install it from
[CRAN](https://cran.r-project.org/package=nflfastR) with:
``` r
install.packages("nflfastR")
```
To get a bug fix or to use a feature from the development version, you
can install the development version of nflfastR either from
[GitHub](https://github.com/nflverse/nflfastR/) with:
``` r
if (!require("pak")) install.packages("pak")
pak::pak("nflverse/nflfastR")
```
or prebuilt from the [development repo](https://nflverse.r-universe.dev)
with:
``` r
install.packages("nflfastR", repos = c("https://nflverse.r-universe.dev", getOption("repos")))
```
## Usage
We have provided some application examples in the **[Getting
Started](https://nflfastr.com/articles/nflfastR.html)** article.
However, these require a basic knowledge of R. For this reason we have
the **[nflfastR beginner’s
guide](https://nflfastr.com/articles/beginners_guide.html)**, which we
recommend to all those who are looking for an introduction to nflfastR
with R.
You can find column names and descriptions in the **[Field
Descriptions](https://nflfastr.com/articles/field_descriptions.html)**
article, or by accessing the `field_descriptions` dataframe from the
package.
## Data access
Even though `nflfastR` is very fast, **we recommend downloading the data
from [here](https://github.com/nflverse/nflverse-data/releases/tag/pbp)
or using the `nflreadr` package**. These data sets include play-by-play
data of complete seasons going back to 1999 and are updated nightly
during the season. The files contain both regular season and postseason
data, and one can use game_type or week to figure out which games
occurred in the postseason.
## nflfastR models
`nflfastR` uses its own models for Expected Points, Win Probability,
Completion Probability, and Expected Yards After the Catch. To read
about the models, please see [this post on Open Source
Football](https://opensourcefootball.com/posts/2020-09-28-nflfastr-ep-wp-and-cp-models/).
For a more detailed description of the motivation for Expected Points
models, we highly recommend this paper [from the nflscrapR team located
here](https://arxiv.org/pdf/1802.00998).
Here is a visualization of the Expected Points model by down and
yardline.
Here is a visualization of the Completion Probability model by air yards
and pass direction.
`nflfastR` includes two win probability models: one with and one without
incorporating the pre-game spread.
## Special thanks
- To Nick Shoemaker for [finding and making available JSON-formatted NFL
play-by-play back to 1999](https://github.com/CroppedClamp/nfl_pbps)
(`nflfastR` uses this source for 1999 and 2000 and previously also
used it for 2001-2010)
- To Lau Sze Yui for developing a scraping function to access
JSON-formatted NFL play-by-play beginning in 2001
- To Aaron Schatz and FTN Fantasy for providing charting data to
correctly mark scrambles in the 1999-2005 seasons
- To Lee Sharpe for curating a resource for game information
- To Timo Riske, Lau Sze Yui, Sean Clement, and Daniel Houston for many
helpful discussions regarding the development of the new `nflfastR`
models
- To Zach Feldman and Josh Hermsmeyer for many helpful discussions about
CPOE models as well as Peter Owen for many helpful suggestions for the
CP model
- To Florian Schmitt for the logo design
- The many users who found and reported bugs in `nflfastR` 1.0
- And of course, the original
[`nflscrapR`](https://github.com/maksimhorowitz/nflscrapR) team,
Maksim Horowitz, Ronald Yurko, and Samuel Ventura, whose work
represented a dramatic step forward for the state of public NFL
research
================================================
FILE: air.toml
================================================
================================================
FILE: cran-comments.md
================================================
## Release summary
This is a minor release that
* deprecates old functions, and
* fixes bugs.
## R CMD check results
0 errors | 0 warnings | 0 notes
## revdepcheck results
We checked 3 reverse dependencies, comparing R CMD check results across CRAN and dev versions of this package.
* We saw 0 new problems
* We failed to check 0 packages
================================================
FILE: data-raw/MODELS.R
================================================
################################################################################
# Author: Ben Baldwin
# Purpose: Estimate nflfastR models for EP, CP, Field Goals, and WP
################################################################################
library(tidyverse)
library(xgboost)
source('R/helper_add_ep_wp.R')
source('R/helper_add_cp_cpoe.R')
source('R/helper_add_nflscrapr_mutations.R')
################################################################################
# Estimate EP model
################################################################################
# from remote
# pbp_data <- readRDS(url('https://github.com/nflverse/nflfastR-data/blob/master/models/cal_data.rds?raw=true'))
# from local
pbp_data <- readRDS('../nflfastR-data/models/cal_data.rds')
#function in helper_add_ep_wp.R
model_data <- pbp_data |>
make_model_mutations() |>
mutate(
label = case_when(
Next_Score_Half == "Touchdown" ~ 0,
Next_Score_Half == "Opp_Touchdown" ~ 1,
Next_Score_Half == "Field_Goal" ~ 2,
Next_Score_Half == "Opp_Field_Goal" ~ 3,
Next_Score_Half == "Safety" ~ 4,
Next_Score_Half == "Opp_Safety" ~ 5,
Next_Score_Half == "No_Score" ~ 6
),
label = as.factor(label),
# Calculate the drive difference between the next score drive and the
# current play drive:
Drive_Score_Dist = Drive_Score_Half - drive,
# Create a weight column based on difference in drives between play and next score:
Drive_Score_Dist_W = (max(Drive_Score_Dist) - Drive_Score_Dist) /
(max(Drive_Score_Dist) - min(Drive_Score_Dist)),
# Create a weight column based on score differential:
ScoreDiff_W = (max(abs(score_differential), na.rm = T) -
abs(score_differential)) /
(max(abs(score_differential), na.rm = T) -
min(abs(score_differential), na.rm = T)),
# Add these weights together and scale again:
Total_W = Drive_Score_Dist_W + ScoreDiff_W,
Total_W_Scaled = (Total_W - min(Total_W, na.rm = T)) /
(max(Total_W, na.rm = T) - min(Total_W, na.rm = T))
) |>
filter(
!is.na(defteam_timeouts_remaining),
!is.na(posteam_timeouts_remaining),
!is.na(yardline_100)
) |>
select(
label,
half_seconds_remaining,
yardline_100,
home,
retractable,
dome,
outdoors,
ydstogo,
era0,
era1,
era2,
era3,
era4,
down1,
down2,
down3,
down4,
posteam_timeouts_remaining,
defteam_timeouts_remaining,
Total_W_Scaled
)
nrounds = 525
params <-
list(
booster = "gbtree",
objective = "multi:softprob",
eval_metric = c("mlogloss"),
num_class = 7,
eta = 0.025,
gamma = 1,
subsample = 0.8,
colsample_bytree = 0.8,
max_depth = 5,
min_child_weight = 1
)
model_data <- model_data |>
mutate(label = as.numeric(label), label = label - 1)
full_train = xgboost::xgb.DMatrix(
model.matrix(~ . + 0, data = model_data |> select(-label, -Total_W_Scaled)),
label = model_data$label,
weight = model_data$Total_W_Scaled
)
set.seed(2013) #GoHawks
ep_model <- xgboost::xgboost(
params = params,
data = full_train,
nrounds = nrounds,
verbose = 2
)
################################################################################
# Estimate FG model
################################################################################
fg_model_data <- pbp_data |>
filter(
play_type %in%
c("field_goal", "extra_point", "run") &
(!is.na(extra_point_result) | !is.na(field_goal_result))
) |>
make_model_mutations()
#estimate model
fg_model <- mgcv::bam(
sp ~ s(yardline_100, by = interaction(era, model_roof)) + model_roof + era,
data = fg_model_data,
family = "binomial"
)
################################################################################
# Estimate CP model
################################################################################
model_vars <- pbp_data |>
filter(season >= 2006) |>
make_model_mutations() |>
prepare_cp_data() |>
filter(valid_pass == 1) |>
select(-valid_pass)
nrounds = 560
params <-
list(
booster = "gbtree",
objective = "binary:logistic",
eval_metric = c("logloss"),
eta = 0.025,
gamma = 5,
subsample = 0.8,
colsample_bytree = 0.8,
max_depth = 4,
min_child_weight = 6,
base_score = mean(model_vars$complete_pass)
)
full_train = xgboost::xgb.DMatrix(
model.matrix(~ . + 0, data = model_vars |> dplyr::select(-complete_pass)),
label = model_vars$complete_pass
)
set.seed(2013) #GoHawks
cp_model <- xgboost::xgboost(
params = params,
data = full_train,
nrounds = nrounds,
verbose = 2
)
################################################################################
# Estimate WP model: spread
################################################################################
model_data <-
readRDS(url(
'https://github.com/guga31bb/metrics/blob/master/wp_tuning/cal_data.rds?raw=true'
)) |>
filter(Winner != "TIE") |>
make_model_mutations() |>
prepare_wp_data() |>
mutate(label = ifelse(posteam == Winner, 1, 0)) |>
filter(
qtr <= 4 &
!is.na(ep) &
!is.na(score_differential) &
!is.na(play_type) &
!is.na(label),
!is.na(yardline_100)
) |>
select(
label,
receive_2h_ko,
spread_time,
home,
half_seconds_remaining,
game_seconds_remaining,
Diff_Time_Ratio,
score_differential,
down,
ydstogo,
yardline_100,
posteam_timeouts_remaining,
defteam_timeouts_remaining
)
nrounds = 534
params <-
list(
booster = "gbtree",
objective = "binary:logistic",
eval_metric = c("logloss"),
eta = 0.05,
gamma = .79012017,
subsample = 0.9224245,
colsample_bytree = 5 / 12,
max_depth = 5,
min_child_weight = 7,
monotone_constraints = "(0, 0, 0, 0, 0, 1, 1, -1, -1, -1, 1, -1)"
)
full_train = xgboost::xgb.DMatrix(
model.matrix(~ . + 0, data = model_data |> select(-label)),
label = model_data$label
)
set.seed(2013) #GoHawks
wp_model_spread <- xgboost::xgboost(
params = params,
data = full_train,
nrounds = nrounds,
verbose = 2
)
importance <- xgboost::xgb.importance(
feature_names = colnames(wp_model_spread),
model = wp_model_spread
)
xgboost::xgb.ggplot.importance(importance_matrix = importance)
#xgboost::xgb.plot.tree(model = wp_model_spread, trees = 1, show_node_id = TRUE)
################################################################################
# Estimate WP model: no spread
################################################################################
model_data <- model_data |>
select(
-spread_time
)
nrounds = 65
params <-
list(
booster = "gbtree",
objective = "binary:logistic",
eval_metric = c("logloss"),
eta = 0.2,
gamma = 0,
subsample = 0.8,
colsample_bytree = 0.8,
max_depth = 4,
min_child_weight = 1
)
full_train = xgboost::xgb.DMatrix(
model.matrix(~ . + 0, data = model_data |> select(-label)),
label = model_data$label
)
set.seed(2013) #GoHawks
wp_model <- xgboost::xgboost(
params = params,
data = full_train,
nrounds = nrounds,
verbose = 2
)
################################################################################
# save models to use in package
################################################################################
usethis::use_data(
ep_model,
wp_model,
wp_model_spread,
fg_model,
cp_model,
internal = TRUE,
overwrite = TRUE
)
================================================
FILE: data-raw/_tune_spread_wp.R
================================================
library(tidyverse)
library(tidymodels)
source('R/helper_add_ep_wp.R')
source('R/helper_add_nflscrapr_mutations.R')
set.seed(2013)
model_data <-
# readRDS('data-raw/cal_data.rds') |>
readRDS(url(
'https://github.com/nflverse/nflfastR-data/blob/master/models/cal_data.rds?raw=true'
)) |>
filter(Winner != "TIE") |>
make_model_mutations() |>
prepare_wp_data() |>
mutate(label = ifelse(posteam == Winner, 1, 0)) |>
filter(
!is.na(ep) &
!is.na(score_differential) &
!is.na(play_type) &
!is.na(label) &
!is.na(yardline_100),
qtr <= 4
) |>
select(
label,
receive_2h_ko,
spread_time,
home,
half_seconds_remaining,
game_seconds_remaining,
ExpScoreDiff_Time_Ratio,
score_differential,
# ep,
down,
ydstogo,
yardline_100,
posteam_timeouts_remaining,
defteam_timeouts_remaining,
season
)
folds <- map(0:9, function(x) {
f <- which(model_data$season %in% c(2000 + x, 2010 + x))
return(f)
})
full_train = xgboost::xgb.DMatrix(
model.matrix(~ . + 0, data = model_data |> select(-label, -season)),
label = model_data$label
)
#params
nrounds = 5000
# #################################################################################
# try tidymodels
grid <- grid_latin_hypercube(
finalize(mtry(), model_data),
min_n(),
tree_depth(),
learn_rate(),
loss_reduction(),
sample_size = sample_prop(),
size = 20
)
grid <- grid |>
mutate(
# it was making dumb learn rates
learn_rate = .1 * ((1:nrow(grid)) / nrow(grid)),
# has to be between 0 and 1
mtry = mtry / length(model_data)
)
# bonus round at the end: do more searching after finding good ones
grid <- grid |>
head(6) |>
mutate(
learn_rate = c(0.01, 0.02, .03, .04, .05, .06),
min_n = 14,
tree_depth = 5,
mtry = 0.5714286,
loss_reduction = 3.445502e-01,
sample_size = 0.7204741
)
grid
# function to search over hyperparameter grid
get_metrics <- function(df, row = 1) {
# testing only
# df <- grid |> dplyr::slice(1)
params <-
list(
booster = "gbtree",
objective = "binary:logistic",
eval_metric = c("logloss"),
eta = df$learn_rate,
gamma = df$loss_reduction,
subsample = df$sample_size,
colsample_bytree = df$mtry,
max_depth = df$tree_depth,
min_child_weight = df$min_n
)
#train
wp_cv_model <- xgboost::xgb.cv(
data = full_train,
params = params,
nrounds = nrounds,
folds = folds,
metrics = list("logloss"),
early_stopping_rounds = 10,
print_every_n = 10
)
output <- params
output$iter = wp_cv_model$best_iteration
output$logloss = wp_cv_model$evaluation_log[output$iter]$test_logloss_mean
output$error = wp_cv_model$evaluation_log[output$iter]$test_error_mean
this_param <- bind_rows(output)
if (row == 1) {
saveRDS(this_param, "data-raw/modeling.rds")
} else {
prev <- readRDS("data-raw/modeling.rds")
for_save <- bind_rows(prev, this_param)
saveRDS(for_save, "data-raw/modeling.rds")
}
return(this_param)
}
# get results
results <- map_df(1:nrow(grid), function(x) {
message(glue::glue("Row {x}"))
get_metrics(grid |> dplyr::slice(x), row = x)
})
# plot
results |>
select(
logloss,
eta,
gamma,
subsample,
colsample_bytree,
max_depth,
min_child_weight
) |>
pivot_longer(
eta:min_child_weight,
values_to = "value",
names_to = "parameter"
) |>
ggplot(aes(value, logloss, color = parameter)) +
geom_point(alpha = 0.8, show.legend = FALSE, size = 3) +
facet_wrap(~parameter, scales = "free_x") +
labs(x = NULL, y = "logloss") +
theme_minimal()
# final best model
#
# eta 0.02
# gamma 0.3445502
# subsample 0.7204741
# colsample_bytree 0.5714286
# max_depth 5
# min_child_weight 14
# iter 760
# logloss 0.4485878
# https://parsnip.tidymodels.org/reference/boost_tree.html
# https://xgboost.readthedocs.io/en/latest/parameter.html
================================================
FILE: data-raw/build_scramble_fix.R
================================================
library(tidyverse)
pbp <- nflfastR::load_pbp(1999:2005) |>
# plays that could plausibly be scramble
filter(
!is.na(rusher_player_id) | penalty == 1,
is.na(passer_player_id),
is.na(receiver_player_id)
) |>
select(
season,
game_id,
play_id,
week,
away_team,
home_team,
posteam,
qtr,
down,
ydstogo,
time,
desc
) |>
# not in scramble data this year
mutate(
time = case_when(
nchar(time) == 3 ~ paste0("00", time),
nchar(time) == 4 ~ paste0("0", time),
TRUE ~ time
)
)
# Thank you to Aaron Schatz and Football Outsiders
# For the charting data to fix scrambles in 2005
s <- readxl::read_xlsx("data-raw/scrambles_2005.xlsx") |>
as_tibble() |>
janitor::clean_names() |>
select(
season = year,
week,
qtr,
away_team = away,
home_team = home,
posteam = offense,
down,
ydstogo = togo,
date_time = time
)
# Thank you to Aaron Schatz
# For the charting data to fix scrambles in 1999 - 2004
s2 <- readxl::read_xlsx(
"data-raw/Scrambles 1999-2004 UPDATE for NFLfastR.xlsx",
sheet = 1
) |>
as_tibble() |>
janitor::clean_names() |>
filter(type %in% c("scramble", "assume scramble")) |>
select(
season = year,
week,
qtr,
away_team = away,
home_team = home,
posteam = offense,
down,
ydstogo = togo,
date_time = time,
yards_gained = yards
)
# s3 is a correction. the plays are in s3 should be rushes and therefore excluded from scramble_fix
# see #475
s3 <- readxl::read_xlsx(
"data-raw/Scrambles.1999-2003.FURTHER.UPDATE.for.NFLfastR.xlsx",
sheet = 1
) |>
as_tibble() |>
janitor::clean_names() |>
select(
season = year,
week,
qtr,
away_team = away,
home_team = home,
posteam = offense,
down,
ydstogo = togo,
date_time = time,
yards_gained = yards
) |>
mutate(
time = paste0(
formatC(lubridate::hour(date_time), width = 2, flag = "0"),
":",
formatC(lubridate::minute(date_time), width = 2, flag = "0")
)
) |>
select(-date_time) |>
mutate_at(vars(home_team, away_team, posteam), nflfastR:::team_name_fn) |>
dplyr::left_join(
pbp,
by = c(
"week",
"away_team",
"home_team",
"posteam",
"qtr",
"down",
"ydstogo",
"time",
"season"
)
) |>
mutate(no_scramble_id = paste0(game_id, "_", play_id))
dat <- bind_rows(
s2,
s
) |>
mutate(
time = paste0(
formatC(lubridate::hour(date_time), width = 2, flag = "0"),
":",
formatC(lubridate::minute(date_time), width = 2, flag = "0")
)
) |>
select(-date_time) |>
mutate_at(vars(home_team, away_team, posteam), nflfastR:::team_name_fn)
d <- dat |>
dplyr::left_join(
pbp,
by = c(
"week",
"away_team",
"home_team",
"posteam",
"qtr",
"down",
"ydstogo",
"time",
"season"
)
) |>
mutate(scramble_id = paste0(game_id, "_", play_id)) |>
filter(scramble_id != "2005_09_CIN_BAL_1725") |>
filter(!scramble_id %in% s3$no_scramble_id)
# number non-matched by season
nrow(d)
d |> filter(is.na(desc)) |> group_by(season) |> summarise(n = n())
# get rid of non-match
d <- d |>
filter(!is.na(desc))
d |> group_by(season) |> summarise(n = n())
scramble_fix <- d$scramble_id
scramble_fix <- scramble_fix |>
unique()
length(scramble_fix)
saveRDS(scramble_fix, file = "data-raw/scramble_fix.rds")
================================================
FILE: data-raw/build_stat_id_df.R
================================================
stat_ids <- "https://www.nflgsis.com/gsis/Documentation/Partners/StatIDs_files/sheet001.html" |>
xml2::read_html() |>
rvest::html_table(fill = TRUE) |>
as.data.frame() |>
dplyr::rename("stat_id" = X1, "name" = X2, "comment" = X3) |>
dplyr::select(1:3) |>
dplyr::slice(-1) |>
dplyr::mutate(stat_id = as.integer(stat_id)) |>
dplyr::filter(!is.na(stat_id)) |>
dplyr::group_by(stat_id, name) |>
dplyr::summarise(comment = paste0(comment, collapse = " ")) |>
dplyr::ungroup() |>
dplyr::mutate(comment = stringr::str_squish(comment))
usethis::use_data(stat_ids, overwrite = TRUE)
================================================
FILE: data-raw/compare_dfs.R
================================================
library(tidyverse)
future::plan("multisession")
# function for comparing revisions against data in repo
# make sure to build package first
compare_pbp <- function(id, cols) {
s <- substr(id[1], 1, 4) |> as.integer()
# no idea why this is necessary
games <- id
new_pbp <- build_nflfastR_pbp(
id
# comment this out to use the "normal" way
# , dir = "../nflfastR-raw/raw"
) |>
filter(!stringr::str_detect(desc, "GAME")) |>
select(all_of(cols)) |>
# necessary to pass the equality checks
mutate(
ep = round(ep, 2),
epa = round(epa, 2),
vegas_home_wp = round(vegas_home_wp, 2),
vegas_home_wpa = round(vegas_home_wpa, 2),
home_wp = round(home_wp, 2)
)
repo_pbp <- readRDS(url(glue::glue(
"https://raw.githubusercontent.com/guga31bb/nflfastR-data/master/data/play_by_play_{s}.rds"
))) |>
filter(game_id %in% games) |>
filter(!stringr::str_detect(desc, "GAME")) |>
select(all_of(cols)) |>
mutate(
ep = round(ep, 2),
epa = round(epa, 2),
vegas_home_wp = round(vegas_home_wp, 2),
vegas_home_wpa = round(vegas_home_wpa, 2),
home_wp = round(home_wp, 2)
)
sum <- arsenal::diffs(arsenal::comparedf(
new_pbp |> select(-desc, -game_id, -play_id),
repo_pbp |> select(-desc, -game_id, -play_id)
))
dfs <- bind_cols(
new_pbp |> select(-desc, -game_id, -play_id),
repo_pbp |> select(-desc, -game_id, -play_id)
)
dfs$desc <- new_pbp$desc
dfs$play_id <- new_pbp$play_id
dfs$game_id <- new_pbp$game_id
return(
list(sum, dfs)
)
}
cols <- c(
# DO NOT REMOVE THESE ONES OR THE COMPARISON WILL BREAK
"game_id",
"play_id",
"desc",
"ep",
"epa",
"vegas_home_wp",
"vegas_home_wpa",
"home_wp"
# here is stuff you can choose whether to include
# , "posteam_timeouts_remaining", "defteam_timeouts_remaining"
)
id <- "2002_05_PHI_JAX"
id <- "2006_01_MIA_PIT"
id <- "2006_02_PIT_JAX"
id <- "2017_08_LAC_NE"
id <- "2006_04_JAX_WAS"
id <- "2019_01_SF_TB"
id <- "2017_12_JAX_ARI"
ids <- nflfastR::fast_scraper_schedules(2020) |>
dplyr::slice(1:20) |>
pull(game_id)
compared <- compare_pbp(
id = ids,
cols = cols
)
# summary table
compared[[1]]
# get row numbers of things with differences
obs <- compared[[1]]$..row.names.. |> unique()
# dfs
compared[[2]] |> arrange(play_id)
# dfs with differences
compared[[2]][obs, ] |> arrange(play_id)
# play description of plays with differences
compared[[2]][obs, ] |> arrange(play_id) |> select(desc)
================================================
FILE: data-raw/create_field_descriptions.R
================================================
library(dplyr)
library(tidyr)
library(stringr)
library(usethis)
x <- readLines("data-raw/variable_list.txt")
field_descriptions <- tibble(x = x) |>
separate(x, "{", into = c(NA, "Field", "Description")) |>
mutate_all(str_remove_all, "\\}")
usethis::use_data(field_descriptions, overwrite = TRUE)
# save(field_descriptions, file = "vignettes/field_descriptions.rda")
================================================
FILE: data-raw/default_play.R
================================================
### Create datatype dataframe
### This is a db that is stored on Seb's local machine
connection <- DBI::dbConnect(duckdb::duckdb(), "../_data_cache/pbp_db")
pbp_db <- dplyr::tbl(connection, "nflfastR_pbp")
### This is heavy, only run if necessary
sk <- pbp_db |>
dplyr::collect() |>
skimr::skim()
readr::write_csv(sk, "data-raw/pbp_datatypes.csv")
sk <- readr::read_csv("data-raw/pbp_datatypes.csv")
random_play <- pbp_db |>
dplyr::filter(season == 1999) |>
dplyr::collect() |>
dplyr::slice_sample(n = 1) |>
as.list()
default_play <-
purrr::map(
seq_along(random_play),
function(i, play, sk) {
val <- play[[i]]
var <- names(play[i])
if (is.character(val)) {
max_char <- sk$character.max[sk$skim_variable == var]
rnd_char <- ifelse(is.na(val), 0L, nchar(val))
if (is.na(max_char)) {
max_char <- switch(
var,
"lateral_sack_player_id" = 10L,
"lateral_sack_player_name" = 20L,
"tackle_with_assist_2_player_id" = 10L,
"tackle_with_assist_2_player_name" = 20L,
"tackle_with_assist_2_team" = 3L,
"drive_real_start_time" = 20L
)
}
if (max_char > rnd_char) {
val <- strsplit(val, character(0L))[[1]] |>
sample(size = max_char, replace = TRUE) |>
paste0(collapse = "")
}
}
val
},
play = random_play,
sk = sk
) |>
purrr::set_names(names(random_play)) |>
tibble::as_tibble_row() |>
dplyr::mutate(game_id = "9999_99_DEF_TYP")
readr::write_csv(default_play, "data-raw/pbp_defaultplay.csv")
saveRDS(default_play, "data-raw/pbp_defaultplay.rds")
================================================
FILE: data-raw/nfl_stats_variables.R
================================================
s1 <- calculate_stats(2023, "season", "player")
s2 <- calculate_stats(2023, "week", "player")
s3 <- calculate_stats(2023, "season", "team")
s4 <- calculate_stats(2023, "week", "team")
n1 <- names(s1)
n2 <- names(s2)
n3 <- names(s3)
n4 <- names(s4)
setdiff(n1, n2)
setdiff(n2, n1)
setdiff(n1, n3)
setdiff(n3, n1)
# tibble::tibble(
# variable = c(n1, n2, n3, n4) |> unique(),
# description = ""
# ) |>
# jsonlite::write_json("data-raw/nfl_stats_variables.json", pretty = TRUE)
nfl_stats_variables <- jsonlite::fromJSON("data-raw/nfl_stats_variables.json")
usethis::use_data(nfl_stats_variables, overwrite = TRUE)
s_old_1 <- nflreadr::load_player_stats(2023, "offense")
s_old_2 <- nflreadr::load_player_stats(2023, "defense")
s_old_3 <- nflreadr::load_player_stats(2023, "kicking")
n_old_1 <- names(s_old_1)
n_old_2 <- names(s_old_2)
n_old_3 <- names(s_old_3)
# Differences to old offense stats ----------------------------------------
# recent_team -> team (recent team in weekly data never made sense)
# interceptions -> passing_interceptions (all passing stats have the passing prefix)
# sacks -> sacks_suffered (to make clear it's not on defensive side)
# sack_yards -> sack_yards_lost (to make clear it's not on defensive side)
# dakota -> not implemented at the moment
setdiff(n_old_1, n2)
setdiff(n2, n_old_1)
# Differences to old defense stats ----------------------------------------
# def_tackles -> there is def_tackles_solo and def_tackles_with_assist
# def_fumble_recovery_own -> fumble_recovery_own (it is not exclusive to defense)
# def_fumble_recovery_yards_own -> fumble_recovery_yards_own (it is not exclusive to defense)
# def_fumble_recovery_opp -> fumble_recovery_opp (it is not exclusive to defense)
# def_fumble_recovery_yards_opp -> fumble_recovery_yards_opp (it is not exclusive to defense)
# def_safety -> def_safeties (we use plural everywhere)
# def_penalty -> penalties (it is not exclusive to defense)
# def_penalty_yards -> penalty_yards (it is not exclusive to defense)
setdiff(n_old_2, n2)
setdiff(n2, n_old_2)
# Differences to old kicking stats ----------------------------------------
# No differences
setdiff(n_old_3, n2)
setdiff(n2, n_old_3)
================================================
FILE: data-raw/nfl_stats_variables.json
================================================
[
{
"variable": "player_id",
"description": "GSIS player ID. Available if stat_type = 'player'."
},
{
"variable": "player_name",
"description": "Short player name as listed in play-by-play data. Please keep in mind that this name is not always unique for one player and can change from season to season and sometimes even within a season. Do not group by this variable. Available if stat_type = 'player'."
},
{
"variable": "player_display_name",
"description": "Full name of player. Available if stat_type = 'player'."
},
{
"variable": "position",
"description": "Position of player. Available if stat_type = 'player'."
},
{
"variable": "position_group",
"description": "Position group of player. Available if stat_type = 'player'."
},
{
"variable": "headshot_url",
"description": "URL to a player headshot image. Available if stat_type = 'player'."
},
{
"variable": "season",
"description": "The NFL season"
},
{
"variable": "week",
"description": "The NFL week. Available if summary_level = 'week'"
},
{
"variable": "season_type",
"description": "One of 'REG', 'POST', or 'REG+POST'"
},
{
"variable": "game_id",
"description": "The nflverse game id of the form '{season}_{week}_{away abbreviation}_{home abbreviation}'. Available if summary_level = 'week'"
},
{
"variable": "recent_team",
"description": "Most recent team player appears in data with. Available if stat_type = 'player' & summary_level = 'season'."
},
{
"variable": "team",
"description": "Team stats are counted for."
},
{
"variable": "opponent_team",
"description": "The opponent team in that week. Available if summary_level = 'week'."
},
{
"variable": "games",
"description": "The number of games where stats were counted. Available if summary_level = 'season'."
},
{
"variable": "completions",
"description": "The number of completed passes."
},
{
"variable": "attempts",
"description": "The number of pass attempts as defined by the NFL."
},
{
"variable": "passing_yards",
"description": "Yards gained on pass plays."
},
{
"variable": "passing_tds",
"description": "The number of passing touchdowns."
},
{
"variable": "passing_interceptions",
"description": "The number of interceptions thrown."
},
{
"variable": "sacks_suffered",
"description": "The Number of times sacked."
},
{
"variable": "sack_yards_lost",
"description": "Yards lost on sack plays."
},
{
"variable": "sack_fumbles",
"description": "The number of sacks with a fumble."
},
{
"variable": "sack_fumbles_lost",
"description": "The number of sacks with a lost fumble."
},
{
"variable": "passing_air_yards",
"description": "Passing air yards (includes incomplete passes)."
},
{
"variable": "passing_yards_after_catch",
"description": "Yards after the catch gained on plays in which player was the passer (this is an unofficial stat and may differ slightly between different sources)."
},
{
"variable": "passing_first_downs",
"description": "First downs on pass attempts."
},
{
"variable": "passing_epa",
"description": "Total expected points added on pass attempts and sacks. NOTE: this uses the variable `qb_epa`, which gives QB credit for EPA for up to the point where a receiver lost a fumble after a completed catch and makes EPA work more like passing yards on plays with fumbles."
},
{
"variable": "passing_cpoe",
"description": "Completion percentage over expectation"
},
{
"variable": "passing_2pt_conversions",
"description": "Two-point conversion passes."
},
{
"variable": "pacr",
"description": "Passing Air Conversion Ratio. PACR = `passing_yards` / `passing_air_yards`. Available if stat_type = 'player'."
},
{
"variable": "passing_10",
"description": "The number of passes that gained 10 or more yards. Some define this as an 'explosive' play."
},
{
"variable": "passing_16",
"description": "The number of passes that gained 16 or more yards. Some define this as an 'explosive' play."
},
{
"variable": "passing_20",
"description": "The number of passes that gained 20 or more yards. Some define this as an 'explosive' play."
},
{
"variable": "passing_40",
"description": "The number of passes that gained 40 or more yards. Some define this as an 'explosive' play."
},
{
"variable": "carries",
"description": "The number of official rush attempts (incl. scrambles and kneel downs). Rushes after a lateral reception don't count as carry."
},
{
"variable": "rushing_yards",
"description": "Yards gained when rushing with the ball (incl. scrambles and kneel downs). Also includes yards gained after obtaining a lateral on a play that started with a rushing attempt."
},
{
"variable": "rushing_tds",
"description": "The number of rushing touchdowns (incl. scrambles). Also includes touchdowns after obtaining a lateral on a play that started with a rushing attempt."
},
{
"variable": "rushing_fumbles",
"description": "The number of rushes with a fumble."
},
{
"variable": "rushing_fumbles_lost",
"description": "The number of rushes with a lost fumble."
},
{
"variable": "rushing_first_downs",
"description": "First downs on rush attempts (incl. scrambles)."
},
{
"variable": "rushing_epa",
"description": "Expected points added on rush attempts (incl. scrambles and kneel downs)."
},
{
"variable": "rushing_2pt_conversions",
"description": "Two-point conversion rushes."
},
{
"variable": "rushing_10",
"description": "The number of runs that gained 10 or more yards. Some define this as an 'explosive' play."
},
{
"variable": "rushing_12",
"description": "The number of runs that gained 12 or more yards. Some define this as an 'explosive' play."
},
{
"variable": "rushing_20",
"description": "The number of runs that gained 20 or more yards. Some define this as an 'explosive' play."
},
{
"variable": "rushing_40",
"description": "The number of runs that gained 40 or more yards. Some define this as an 'explosive' play."
},
{
"variable": "receptions",
"description": "The number of pass receptions. Lateral receptions officially don't count as reception."
},
{
"variable": "targets",
"description": "The number of pass plays where the player was the targeted receiver."
},
{
"variable": "receiving_yards",
"description": "Yards gained after a pass reception. Includes yards gained after receiving a lateral on a play that started as a pass play."
},
{
"variable": "receiving_tds",
"description": "The number of touchdowns following a pass reception. Also includes touchdowns after receiving a lateral on a play that started as a pass play."
},
{
"variable": "receiving_fumbles",
"description": "The number of fumbles after a pass reception."
},
{
"variable": "receiving_fumbles_lost",
"description": "The number of fumbles lost after a pass reception."
},
{
"variable": "receiving_air_yards",
"description": "Receiving air yards (incl. incomplete passes)."
},
{
"variable": "receiving_yards_after_catch",
"description": "Yards after the catch gained on plays in which player was receiver (this is an unofficial stat and may differ slightly between different sources)."
},
{
"variable": "receiving_first_downs",
"description": "First downs on receptions."
},
{
"variable": "receiving_epa",
"description": "Expected points added on receptions."
},
{
"variable": "receiving_2pt_conversions",
"description": "Two-point conversion receptions."
},
{
"variable": "receiving_10",
"description": "The number of receptions that gained 10 or more yards. Some define this as an 'explosive' play."
},
{
"variable": "receiving_16",
"description": "The number of receptions that gained 16 or more yards. Some define this as an 'explosive' play."
},
{
"variable": "receiving_20",
"description": "The number of receptions that gained 20 or more yards. Some define this as an 'explosive' play."
},
{
"variable": "receiving_40",
"description": "The number of receptions that gained 40 or more yards. Some define this as an 'explosive' play."
},
{
"variable": "racr",
"description": "Receiver Air Conversion Ratio. RACR = `receiving_yards` / `receiving_air_yards`. Available if stat_type = 'player'."
},
{
"variable": "target_share",
"description": "The share of targets of the player in all targets of his team. Available if stat_type = 'player'."
},
{
"variable": "air_yards_share",
"description": "The share of receiving_air_yards of the player in all air_yards of his team. Available if stat_type = 'player'."
},
{
"variable": "wopr",
"description": "Weighted Opportunity Rating. WOPR = 1.5 × `target_share` + 0.7 × `air_yards_share`. Available if stat_type = 'player'."
},
{
"variable": "special_teams_tds",
"description": "The number of touchdowns scored in special teams plays."
},
{
"variable": "def_tackles_solo",
"description": "Solo tackles."
},
{
"variable": "def_tackles_with_assist",
"description": "Tackles where another player assisted."
},
{
"variable": "def_tackle_assists",
"description": "Assist to another player's tackle."
},
{
"variable": "def_tackles_for_loss",
"description": "Tackles for loss."
},
{
"variable": "def_tackles_for_loss_yards",
"description": "Yards lost by the opposing team through a tackle."
},
{
"variable": "def_fumbles_forced",
"description": "Forced fumbles."
},
{
"variable": "def_sacks",
"description": "Number of Sacks."
},
{
"variable": "def_sack_yards",
"description": "Yards lost by the opposing team through a sack."
},
{
"variable": "def_qb_hits",
"description": "Number of QB hits"
},
{
"variable": "def_interceptions",
"description": "Interceptions caught."
},
{
"variable": "def_interception_yards",
"description": "Yards gained after interceptions."
},
{
"variable": "def_pass_defended",
"description": "Number of defended passes."
},
{
"variable": "def_tds",
"description": "Defensive touchdowns."
},
{
"variable": "def_fumbles",
"description": "Number of fumbles while playing on defense."
},
{
"variable": "def_safeties",
"description": "Tackles that resulted in a safety."
},
{
"variable": "misc_yards",
"description": "Yardage gained/lost that doesn't fall into any other category. Examples are blocked field goals or blocked punts."
},
{
"variable": "fumble_recovery_own",
"description": "Recovered fumbles where the ball was fumbled by own team."
},
{
"variable": "fumble_recovery_yards_own",
"description": "Yardage gained/lost by a player after he recovered a fumble by his own team. Includes yardage gained/lost where a team mate recovered a fumble and lateraled the ball to the player."
},
{
"variable": "fumble_recovery_opp",
"description": "Recovered fumbles where the ball was fumbled by opposing team."
},
{
"variable": "fumble_recovery_yards_opp",
"description": "Yardage gained/lost by a player after he recovered a fumble by the opposing team. Includes yardage gained/lost where a team mate recovered a fumble and lateraled the ball to the player."
},
{
"variable": "fumble_recovery_tds",
"description": "Touchdowns scored after a fumble recovery. This can be in any unit. And both the own team and the opposing team can have fumbled the ball initially. Includes touchdowns where a team mate recovered a fumble and lateraled the ball to the player."
},
{
"variable": "penalties",
"description": "Penalties caused."
},
{
"variable": "penalty_yards",
"description": "Yardage lost through penalties."
},
{
"variable": "timeouts",
"description": "Number of timeouts taken by team. Available if stat_type = 'team'."
},
{
"variable": "fumbles_forced_by_opp",
"description": "The number of fumbles by the player. The fumble was forced by the opponent."
},
{
"variable": "fumbles_not_forced",
"description": "The number of fumbles by the player. The fumble was NOT forced by the opponent."
},
{
"variable": "fumbles_out_of_bounds",
"description": "The number of fumbles by the player, and the ball went out of bounds. The fumble may or may not have been forced."
},
{
"variable": "fumbles_total",
"description": "The total number of fumbles by the player. Equals `fumbles_forced_by_opp` + `fumbles_not_forced`."
},
{
"variable": "fumbles_lost_total",
"description": "The total number of fumbles lost by the player."
},
{
"variable": "punt_returns",
"description": "Number of punts returned."
},
{
"variable": "punt_return_yards",
"description": "Yardage gained/lost by a player during a punt return."
},
{
"variable": "kickoff_returns",
"description": "Number of kickoffs returned."
},
{
"variable": "kickoff_return_yards",
"description": "Yardage gained/lost by a player during a kickoff return."
},
{
"variable": "fg_made",
"description": "Successful field goal attempts."
},
{
"variable": "fg_att",
"description": "Attempted field goals."
},
{
"variable": "fg_missed",
"description": "Missed field goals."
},
{
"variable": "fg_blocked",
"description": "Attempted field goals that were blocked."
},
{
"variable": "fg_long",
"description": "Distance of longest made field goal."
},
{
"variable": "fg_pct",
"description": "Percentage of successful field goal attempts."
},
{
"variable": "fg_made_0_19",
"description": "Successful field goal attempts where distance was between 0 and 19 yards."
},
{
"variable": "fg_made_20_29",
"description": "Successful field goal attempts where distance was between 20 and 29 yards."
},
{
"variable": "fg_made_30_39",
"description": "Successful field goal attempts where distance was between 30 and 39 yards."
},
{
"variable": "fg_made_40_49",
"description": "Successful field goal attempts where distance was between 40 and 49 yards."
},
{
"variable": "fg_made_50_59",
"description": "Successful field goal attempts where distance was between 50 and 59 yards."
},
{
"variable": "fg_made_60_",
"description": "Successful field goal attempts where distance was 60+ yards."
},
{
"variable": "fg_missed_0_19",
"description": "Missed field goal attempts where distance was between 0 and 19 yards."
},
{
"variable": "fg_missed_20_29",
"description": "Missed field goal attempts where distance was between 20 and 29 yards."
},
{
"variable": "fg_missed_30_39",
"description": "Missed field goal attempts where distance was between 30 and 39 yards."
},
{
"variable": "fg_missed_40_49",
"description": "Missed field goal attempts where distance was between 40 and 49 yards."
},
{
"variable": "fg_missed_50_59",
"description": "Missed field goal attempts where distance was between 50 and 59 yards."
},
{
"variable": "fg_missed_60_",
"description": "Missed field goal attempts where distance was 60+ yards."
},
{
"variable": "fg_made_list",
"description": "Distances of all successful field goal attempts."
},
{
"variable": "fg_missed_list",
"description": "Distances of all missed field goal attempts."
},
{
"variable": "fg_blocked_list",
"description": "Distances of all blocked field goal attempts."
},
{
"variable": "fg_made_distance",
"description": "Sum of distances of all made field goals."
},
{
"variable": "fg_missed_distance",
"description": "Sum of distances of all missed field goals."
},
{
"variable": "fg_blocked_distance",
"description": "Sum of distances of all blocked field goals."
},
{
"variable": "pat_made",
"description": "Successful extra point attempts."
},
{
"variable": "pat_att",
"description": "Attempted extra points."
},
{
"variable": "pat_missed",
"description": "Missed extra points."
},
{
"variable": "pat_blocked",
"description": "Extra points blocked by opponent."
},
{
"variable": "pat_pct",
"description": "Percentage of successful extra point attempts."
},
{
"variable": "gwfg_made",
"description": "Successful game winning field goal attempts."
},
{
"variable": "gwfg_att",
"description": "Attempted game winning field goals."
},
{
"variable": "gwfg_missed",
"description": "Missed game winning field goals."
},
{
"variable": "gwfg_blocked",
"description": "Game winning field goal attempts blocked by opponent."
},
{
"variable": "gwfg_distance",
"description": "Distance of game winning field goal attempt. Available if summary_level = 'week'."
},
{
"variable": "gwfg_distance_list",
"description": "Distances of game winning field goal attempts. Available if summary_level = 'season'."
},
{
"variable": "pt_att",
"description": "Kicked punts."
},
{
"variable": "pt_blocked",
"description": "Kicked punts that were blocked."
},
{
"variable": "pt_long",
"description": "Longest punt kicked."
},
{
"variable": "pt_yards",
"description": "Length of punts kicked."
},
{
"variable": "pt_inside_20",
"description": "The number of punts where the RETURN ended inside the opponent's 20 yard line."
},
{
"variable": "pt_out_of_bounds",
"description": "The number of punts that went out of bounds without return."
},
{
"variable": "pt_downed",
"description": "The number of punts downed without return."
},
{
"variable": "pt_touchback",
"description": "The number of punts that resulted in a touchback."
},
{
"variable": "pt_fair_caught",
"description": "The number of punts that resulted in a fair catch."
},
{
"variable": "pt_returned",
"description": "The number of punts that were returned by the opponent team."
},
{
"variable": "pt_return_yards",
"description": "The punt return yardage of the opponent team."
},
{
"variable": "pt_return_tds",
"description": "The number of punts that were returned for a touchdown by the opponent team."
},
{
"variable": "pt_net_yards",
"description": "Net punt yardage. Equals `pt_yards` - `pt_return_yards` - `pt_touchback` * `20`."
},
{
"variable": "fantasy_points",
"description": "Standard fantasy points."
},
{
"variable": "fantasy_points_ppr",
"description": "PPR fantasy points."
}
]
================================================
FILE: data-raw/pbp_datatypes.csv
================================================
skim_type,skim_variable,n_missing,complete_rate,character.min,character.max,character.empty,character.n_unique,character.whitespace,numeric.mean,numeric.sd,numeric.p0,numeric.p25,numeric.p50,numeric.p75,numeric.p100,numeric.hist
character,game_id,0,1,13,15,0,6134,0,NA,NA,NA,NA,NA,NA,NA,NA
character,old_game_id,0,1,10,10,0,6134,0,NA,NA,NA,NA,NA,NA,NA,NA
character,home_team,0,1,2,3,0,32,0,NA,NA,NA,NA,NA,NA,NA,NA
character,away_team,0,1,2,3,0,32,0,NA,NA,NA,NA,NA,NA,NA,NA
character,season_type,0,1,3,4,0,2,0,NA,NA,NA,NA,NA,NA,NA,NA
character,posteam,74782,0.931927869867191,0,3,104,33,0,NA,NA,NA,NA,NA,NA,NA,NA
character,posteam_type,74782,0.931927869867191,4,4,0,2,0,NA,NA,NA,NA,NA,NA,NA,NA
character,defteam,74782,0.931927869867191,2,3,0,32,0,NA,NA,NA,NA,NA,NA,NA,NA
character,side_of_field,85173,0.9224692099729649,0,5,79,38,0,NA,NA,NA,NA,NA,NA,NA,NA
character,game_date,0,1,10,10,0,1169,0,NA,NA,NA,NA,NA,NA,NA,NA
character,game_half,0,1,5,8,0,3,0,NA,NA,NA,NA,NA,NA,NA,NA
character,time,1137,0.9989650181599716,0,5,62,1502,0,NA,NA,NA,NA,NA,NA,NA,NA
character,yrdln,7356,0.9933040225019798,0,6,2,1659,0,NA,NA,NA,NA,NA,NA,NA,NA
character,desc,0,1,4,1079,0,990769,0,NA,NA,NA,NA,NA,NA,NA,NA
character,play_type,50328,0.9541877167590596,3,11,0,9,0,NA,NA,NA,NA,NA,NA,NA,NA
character,pass_length,806758,0.26562895400384134,4,5,0,2,0,NA,NA,NA,NA,NA,NA,NA,NA
character,pass_location,806698,0.26568357045977953,4,6,0,3,0,NA,NA,NA,NA,NA,NA,NA,NA
character,run_location,778466,0.2913824335272217,4,6,0,3,0,NA,NA,NA,NA,NA,NA,NA,NA
character,run_gap,870143,0.20793121967648853,3,6,0,3,0,NA,NA,NA,NA,NA,NA,NA,NA
character,field_goal_result,1075311,0.02117206914443326,4,7,0,3,0,NA,NA,NA,NA,NA,NA,NA,NA
character,extra_point_result,1070162,0.025859071338194206,4,7,0,4,0,NA,NA,NA,NA,NA,NA,NA,NA
character,two_point_conv_result,1096605,0.0017886889319752575,7,7,0,2,0,NA,NA,NA,NA,NA,NA,NA,NA
character,timeout_team,1053072,0.04141565853791751,2,3,0,32,0,NA,NA,NA,NA,NA,NA,NA,NA
character,td_team,1068075,0.02775881373057698,2,3,0,32,0,NA,NA,NA,NA,NA,NA,NA,NA
character,td_player_name,1068075,0.02775881373057698,5,19,0,2989,0,NA,NA,NA,NA,NA,NA,NA,NA
character,td_player_id,1068076,0.02775790345631135,10,10,0,3264,0,NA,NA,NA,NA,NA,NA,NA,NA
character,passer_player_id,653500,0.40513576740671964,10,10,0,767,0,NA,NA,NA,NA,NA,NA,NA,NA
character,passer_player_name,653500,0.40513576740671964,5,17,0,802,0,NA,NA,NA,NA,NA,NA,NA,NA
character,receiver_player_id,715364,0.34882256023739955,10,10,0,3088,0,NA,NA,NA,NA,NA,NA,NA,NA
character,receiver_player_name,715364,0.34882256023739955,5,18,0,2971,0,NA,NA,NA,NA,NA,NA,NA,NA
character,rusher_player_id,764576,0.3040261430769091,10,10,0,2262,0,NA,NA,NA,NA,NA,NA,NA,NA
character,rusher_player_name,764576,0.3040261430769091,5,18,0,2206,0,NA,NA,NA,NA,NA,NA,NA,NA
character,lateral_receiver_player_id,1098347,2.0299116123689842e-4,10,10,0,181,0,NA,NA,NA,NA,NA,NA,NA,NA
character,lateral_receiver_player_name,1098347,2.0299116123689842e-4,6,16,0,181,0,NA,NA,NA,NA,NA,NA,NA,NA
character,lateral_rusher_player_id,1098531,3.550069635982478e-5,10,10,0,37,0,NA,NA,NA,NA,NA,NA,NA,NA
character,lateral_rusher_player_name,1098531,3.550069635982478e-5,6,13,0,37,0,NA,NA,NA,NA,NA,NA,NA,NA
character,lateral_sack_player_id,1098570,0,NA,NA,0,0,0,NA,NA,NA,NA,NA,NA,NA,NA
character,lateral_sack_player_name,1098570,0,NA,NA,0,0,0,NA,NA,NA,NA,NA,NA,NA,NA
character,interception_player_id,1086906,0.01061743903438106,10,10,0,1982,0,NA,NA,NA,NA,NA,NA,NA,NA
character,interception_player_name,1086906,0.01061743903438106,5,19,0,1904,0,NA,NA,NA,NA,NA,NA,NA,NA
character,lateral_interception_player_id,1098491,7.19116669852804e-5,10,10,0,70,0,NA,NA,NA,NA,NA,NA,NA,NA
character,lateral_interception_player_name,1098491,7.19116669852804e-5,5,14,0,70,0,NA,NA,NA,NA,NA,NA,NA,NA
character,punt_returner_player_id,1059306,0.03574100876594122,10,10,0,930,0,NA,NA,NA,NA,NA,NA,NA,NA
character,punt_returner_player_name,1059305,0.03574191904020685,5,19,0,910,0,NA,NA,NA,NA,NA,NA,NA,NA
character,lateral_punt_returner_player_id,1098509,5.552673020381427e-5,10,10,0,56,0,NA,NA,NA,NA,NA,NA,NA,NA
character,lateral_punt_returner_player_name,1098509,5.552673020381427e-5,5,19,0,56,0,NA,NA,NA,NA,NA,NA,NA,NA
character,kickoff_returner_player_name,1059285,0.03576012452551958,5,19,0,2072,0,NA,NA,NA,NA,NA,NA,NA,NA
character,kickoff_returner_player_id,1059286,0.035759214251253946,10,10,0,2222,0,NA,NA,NA,NA,NA,NA,NA,NA
character,lateral_kickoff_returner_player_id,1098419,1.374514141110339e-4,10,10,0,132,0,NA,NA,NA,NA,NA,NA,NA,NA
character,lateral_kickoff_returner_player_name,1098419,1.374514141110339e-4,6,16,0,132,0,NA,NA,NA,NA,NA,NA,NA,NA
character,punter_player_id,1041530,0.05192204411189094,10,10,0,222,0,NA,NA,NA,NA,NA,NA,NA,NA
character,punter_player_name,1041530,0.05192204411189094,5,16,0,243,0,NA,NA,NA,NA,NA,NA,NA,NA
character,kicker_player_name,985912,0.10254967821804706,3,14,0,334,0,NA,NA,NA,NA,NA,NA,NA,NA
character,kicker_player_id,985912,0.10254967821804706,10,10,0,310,0,NA,NA,NA,NA,NA,NA,NA,NA
character,own_kickoff_recovery_player_id,1098310,2.3667130906546152e-4,10,10,0,238,0,NA,NA,NA,NA,NA,NA,NA,NA
character,own_kickoff_recovery_player_name,1098310,2.3667130906546152e-4,5,19,0,236,0,NA,NA,NA,NA,NA,NA,NA,NA
character,blocked_player_id,1097590,8.920687803235516e-4,10,10,0,622,0,NA,NA,NA,NA,NA,NA,NA,NA
character,blocked_player_name,1097589,8.929790545891825e-4,4,19,0,603,0,NA,NA,NA,NA,NA,NA,NA,NA
character,tackle_for_loss_1_player_id,1048762,0.04533894062280963,10,10,0,3367,0,NA,NA,NA,NA,NA,NA,NA,NA
character,tackle_for_loss_1_player_name,1048699,0.04539628790154471,4,19,0,3226,0,NA,NA,NA,NA,NA,NA,NA,NA
character,tackle_for_loss_2_player_id,1098559,1.0013016922050255e-5,10,10,0,11,0,NA,NA,NA,NA,NA,NA,NA,NA
character,tackle_for_loss_2_player_name,1098559,1.0013016922050255e-5,6,12,0,11,0,NA,NA,NA,NA,NA,NA,NA,NA
character,qb_hit_1_player_id,1050497,0.0437596147719308,10,10,0,2982,0,NA,NA,NA,NA,NA,NA,NA,NA
character,qb_hit_1_player_name,1050490,0.043765986691790215,4,19,0,2829,0,NA,NA,NA,NA,NA,NA,NA,NA
character,qb_hit_2_player_id,1096391,0.0019834876248213673,10,10,0,1015,0,NA,NA,NA,NA,NA,NA,NA,NA
character,qb_hit_2_player_name,1096391,0.0019834876248213673,5,19,0,995,0,NA,NA,NA,NA,NA,NA,NA,NA
character,forced_fumble_player_1_team,1087072,0.010466333506285452,2,3,0,32,0,NA,NA,NA,NA,NA,NA,NA,NA
character,forced_fumble_player_1_player_id,1087105,0.010436294455519413,10,10,0,2977,0,NA,NA,NA,NA,NA,NA,NA,NA
character,forced_fumble_player_1_player_name,1087079,0.010459961586426036,4,19,0,2720,0,NA,NA,NA,NA,NA,NA,NA,NA
character,forced_fumble_player_2_team,1098504,6.0078101531968464e-5,2,3,0,26,0,NA,NA,NA,NA,NA,NA,NA,NA
character,forced_fumble_player_2_player_id,1098504,6.0078101531968464e-5,10,10,0,65,0,NA,NA,NA,NA,NA,NA,NA,NA
character,forced_fumble_player_2_player_name,1098504,6.0078101531968464e-5,6,14,0,65,0,NA,NA,NA,NA,NA,NA,NA,NA
character,solo_tackle_1_team,599256,0.45451268467189165,2,3,0,32,0,NA,NA,NA,NA,NA,NA,NA,NA
character,solo_tackle_2_team,1092308,0.005700137451414067,2,3,0,32,0,NA,NA,NA,NA,NA,NA,NA,NA
character,solo_tackle_1_player_id,599641,0.45416222907962167,10,10,0,8252,0,NA,NA,NA,NA,NA,NA,NA,NA
character,solo_tackle_2_player_id,1092376,0.005638238801350837,10,10,0,3134,0,NA,NA,NA,NA,NA,NA,NA,NA
character,solo_tackle_1_player_name,599306,0.4544671709586098,4,19,0,7320,0,NA,NA,NA,NA,NA,NA,NA,NA
character,solo_tackle_2_player_name,1092313,0.005695586080085913,4,18,0,2863,0,NA,NA,NA,NA,NA,NA,NA,NA
character,assist_tackle_1_player_id,956715,0.12912695595182833,10,10,0,5669,0,NA,NA,NA,NA,NA,NA,NA,NA
character,assist_tackle_1_player_name,956715,0.12912695595182833,5,19,0,5142,0,NA,NA,NA,NA,NA,NA,NA,NA
character,assist_tackle_1_team,956715,0.12912695595182833,2,3,0,32,0,NA,NA,NA,NA,NA,NA,NA,NA
character,assist_tackle_2_player_id,1039980,0.05333296922362707,10,10,0,4638,0,NA,NA,NA,NA,NA,NA,NA,NA
character,assist_tackle_2_player_name,1039980,0.05333296922362707,5,19,0,4165,0,NA,NA,NA,NA,NA,NA,NA,NA
character,assist_tackle_2_team,1039980,0.05333296922362707,2,3,0,32,0,NA,NA,NA,NA,NA,NA,NA,NA
character,assist_tackle_3_player_id,1098567,2.730822796892518e-6,10,10,0,3,0,NA,NA,NA,NA,NA,NA,NA,NA
character,assist_tackle_3_player_name,1098567,2.730822796892518e-6,8,9,0,3,0,NA,NA,NA,NA,NA,NA,NA,NA
character,assist_tackle_3_team,1098567,2.730822796892518e-6,3,3,0,3,0,NA,NA,NA,NA,NA,NA,NA,NA
character,assist_tackle_4_player_id,1098567,2.730822796892518e-6,10,10,0,3,0,NA,NA,NA,NA,NA,NA,NA,NA
character,assist_tackle_4_player_name,1098567,2.730822796892518e-6,7,8,0,3,0,NA,NA,NA,NA,NA,NA,NA,NA
character,assist_tackle_4_team,1098567,2.730822796892518e-6,3,3,0,3,0,NA,NA,NA,NA,NA,NA,NA,NA
character,tackle_with_assist_1_player_id,1015313,0.0757867045340761,10,10,0,4738,0,NA,NA,NA,NA,NA,NA,NA,NA
character,tackle_with_assist_1_player_name,1015313,0.0757867045340761,5,19,0,4380,0,NA,NA,NA,NA,NA,NA,NA,NA
character,tackle_with_assist_1_team,1015313,0.0757867045340761,2,3,0,32,0,NA,NA,NA,NA,NA,NA,NA,NA
character,tackle_with_assist_2_player_id,1098570,0,NA,NA,0,0,0,NA,NA,NA,NA,NA,NA,NA,NA
character,tackle_with_assist_2_player_name,1098570,0,NA,NA,0,0,0,NA,NA,NA,NA,NA,NA,NA,NA
character,tackle_with_assist_2_team,1098570,0,NA,NA,0,0,0,NA,NA,NA,NA,NA,NA,NA,NA
character,pass_defense_1_player_id,1042237,0.05127848020608605,10,10,0,3379,0,NA,NA,NA,NA,NA,NA,NA,NA
character,pass_defense_1_player_name,1042236,0.05127939048035168,4,19,0,3197,0,NA,NA,NA,NA,NA,NA,NA,NA
character,pass_defense_2_player_id,1096864,0.0015529278971754268,10,10,0,996,0,NA,NA,NA,NA,NA,NA,NA,NA
character,pass_defense_2_player_name,1096864,0.0015529278971754268,5,19,0,963,0,NA,NA,NA,NA,NA,NA,NA,NA
character,fumbled_1_team,1081551,0.01549195772686307,2,3,0,32,0,NA,NA,NA,NA,NA,NA,NA,NA
character,fumbled_1_player_id,1081555,0.015488316629800547,10,10,0,2696,0,NA,NA,NA,NA,NA,NA,NA,NA
character,fumbled_1_player_name,1081555,0.015488316629800547,5,19,0,2517,0,NA,NA,NA,NA,NA,NA,NA,NA
character,fumbled_2_player_id,1098456,1.0377126628258182e-4,10,10,0,111,0,NA,NA,NA,NA,NA,NA,NA,NA
character,fumbled_2_player_name,1098456,1.0377126628258182e-4,5,12,0,110,0,NA,NA,NA,NA,NA,NA,NA,NA
character,fumbled_2_team,1098456,1.0377126628258182e-4,2,3,0,30,0,NA,NA,NA,NA,NA,NA,NA,NA
character,fumble_recovery_1_team,1082877,0.014284934050629472,2,3,0,32,0,NA,NA,NA,NA,NA,NA,NA,NA
character,fumble_recovery_1_player_id,1082887,0.014275831307973053,10,10,0,5004,0,NA,NA,NA,NA,NA,NA,NA,NA
character,fumble_recovery_1_player_name,1082887,0.014275831307973053,5,19,0,4398,0,NA,NA,NA,NA,NA,NA,NA,NA
character,fumble_recovery_2_team,1098447,1.1196373467325937e-4,2,3,0,31,0,NA,NA,NA,NA,NA,NA,NA,NA
character,fumble_recovery_2_player_id,1098447,1.1196373467325937e-4,10,10,0,120,0,NA,NA,NA,NA,NA,NA,NA,NA
character,fumble_recovery_2_player_name,1098447,1.1196373467325937e-4,5,13,0,118,0,NA,NA,NA,NA,NA,NA,NA,NA
character,sack_player_id,1073024,0.023253866389943312,10,10,0,2582,0,NA,NA,NA,NA,NA,NA,NA,NA
character,sack_player_name,1072977,0.023296649280428183,4,19,0,2488,0,NA,NA,NA,NA,NA,NA,NA,NA
character,half_sack_1_player_id,1096089,0.002258390453043546,10,10,0,1118,0,NA,NA,NA,NA,NA,NA,NA,NA
character,half_sack_1_player_name,1096089,0.002258390453043546,5,18,0,1084,0,NA,NA,NA,NA,NA,NA,NA,NA
character,half_sack_2_player_id,1096089,0.002258390453043546,10,10,0,1094,0,NA,NA,NA,NA,NA,NA,NA,NA
character,half_sack_2_player_name,1096089,0.002258390453043546,5,19,0,1063,0,NA,NA,NA,NA,NA,NA,NA,NA
character,return_team,971115,0.11601900652666652,2,3,0,32,0,NA,NA,NA,NA,NA,NA,NA,NA
character,penalty_team,1021292,0.07034417469983711,2,3,0,32,0,NA,NA,NA,NA,NA,NA,NA,NA
character,penalty_player_id,1024660,0.06727837097317424,10,47,0,7741,0,NA,NA,NA,NA,NA,NA,NA,NA
character,penalty_player_name,1024735,0.06721010040325148,5,19,0,6791,0,NA,NA,NA,NA,NA,NA,NA,NA
character,replay_or_challenge_result,1090418,0.007420555813466567,6,8,0,3,0,NA,NA,NA,NA,NA,NA,NA,NA
character,penalty_type,1021527,0.07013026024741253,7,38,0,69,0,NA,NA,NA,NA,NA,NA,NA,NA
character,safety_player_name,1098320,2.275685664090421e-4,4,15,0,217,0,NA,NA,NA,NA,NA,NA,NA,NA
character,safety_player_id,1098325,2.230171950808879e-4,10,47,0,224,0,NA,NA,NA,NA,NA,NA,NA,NA
character,series_result,248,0.9997742519821222,4,17,0,11,0,NA,NA,NA,NA,NA,NA,NA,NA
character,start_time,91628,0.916593389588283,7,8,0,48,0,NA,NA,NA,NA,NA,NA,NA,NA
character,time_of_day,157093,0.8570022847884068,7,8,0,62195,0,NA,NA,NA,NA,NA,NA,NA,NA
character,stadium,569653,0.48145953375752115,3,35,0,149,0,NA,NA,NA,NA,NA,NA,NA,NA
character,weather,563302,0.4872406856185769,22,123,0,2682,0,NA,NA,NA,NA,NA,NA,NA,NA
character,nfl_api_id,91628,0.916593389588283,36,36,0,5619,0,NA,NA,NA,NA,NA,NA,NA,NA
character,play_clock,409460,0.6272790991925867,1,2,0,47,0,NA,NA,NA,NA,NA,NA,NA,NA
character,play_type_nfl,91848,0.916393129249843,4,11,0,15,0,NA,NA,NA,NA,NA,NA,NA,NA
character,st_play_type,1097598,8.847865861983939e-4,7,7,0,1,0,NA,NA,NA,NA,NA,NA,NA,NA
character,end_clock_time,893921,0.1862867181881901,4,5,0,902,0,NA,NA,NA,NA,NA,NA,NA,NA
character,end_yard_line,249182,0.7731760379402314,2,7,0,2240,0,NA,NA,NA,NA,NA,NA,NA,NA
character,fixed_drive_result,556,0.9994938875083063,4,17,0,9,0,NA,NA,NA,NA,NA,NA,NA,NA
character,drive_real_start_time,1098570,0,NA,NA,0,0,0,NA,NA,NA,NA,NA,NA,NA,NA
character,drive_time_of_possession,14081,0.9871824280655762,4,5,0,675,0,NA,NA,NA,NA,NA,NA,NA,NA
character,drive_start_transition,18201,0.9834320980911548,4,19,0,29,0,NA,NA,NA,NA,NA,NA,NA,NA
character,drive_end_transition,50801,0.9537571570314136,4,19,0,31,0,NA,NA,NA,NA,NA,NA,NA,NA
character,drive_game_clock_start,14081,0.9871824280655762,4,5,0,1500,0,NA,NA,NA,NA,NA,NA,NA,NA
character,drive_game_clock_end,14081,0.9871824280655762,4,5,0,1500,0,NA,NA,NA,NA,NA,NA,NA,NA
character,drive_start_yard_line,16021,0.9854164959902418,0,6,241,1614,0,NA,NA,NA,NA,NA,NA,NA,NA
character,drive_end_yard_line,16021,0.9854164959902418,0,6,241,1634,0,NA,NA,NA,NA,NA,NA,NA,NA
character,location,0,1,4,7,0,2,0,NA,NA,NA,NA,NA,NA,NA,NA
character,roof,4387,0.9960066267966539,4,8,0,4,0,NA,NA,NA,NA,NA,NA,NA,NA
character,surface,0,1,5,10,0,9,0,NA,NA,NA,NA,NA,NA,NA,NA
character,home_coach,0,1,7,20,0,151,0,NA,NA,NA,NA,NA,NA,NA,NA
character,away_coach,0,1,7,20,0,151,0,NA,NA,NA,NA,NA,NA,NA,NA
character,stadium_id,0,1,5,5,0,59,0,NA,NA,NA,NA,NA,NA,NA,NA
character,game_stadium,0,1,8,35,0,94,0,NA,NA,NA,NA,NA,NA,NA,NA
character,passer,616172,0.4391144851943891,5,16,0,737,0,NA,NA,NA,NA,NA,NA,NA,NA
character,rusher,771805,0.2974457704106247,5,18,0,2248,0,NA,NA,NA,NA,NA,NA,NA,NA
character,receiver,669086,0.3909482327025132,4,18,0,2722,0,NA,NA,NA,NA,NA,NA,NA,NA
character,passer_id,616172,0.4391144851943891,10,10,0,765,0,NA,NA,NA,NA,NA,NA,NA,NA
character,rusher_id,771806,0.29744486013635907,10,10,0,2456,0,NA,NA,NA,NA,NA,NA,NA,NA
character,receiver_id,669086,0.3909482327025132,10,10,0,3088,0,NA,NA,NA,NA,NA,NA,NA,NA
character,name,289407,0.7365602556050138,5,18,0,2325,0,NA,NA,NA,NA,NA,NA,NA,NA
character,id,289408,0.7365593453307482,10,10,0,2538,0,NA,NA,NA,NA,NA,NA,NA,NA
character,fantasy_player_name,381375,0.6528441519429804,5,18,0,3442,0,NA,NA,NA,NA,NA,NA,NA,NA
character,fantasy_player_id,381375,0.6528441519429804,10,10,0,3587,0,NA,NA,NA,NA,NA,NA,NA,NA
character,fantasy,326758,0.7025606015092347,4,18,0,3342,0,NA,NA,NA,NA,NA,NA,NA,NA
character,fantasy_id,326759,0.7025596912349691,10,10,0,3764,0,NA,NA,NA,NA,NA,NA,NA,NA
numeric,play_id,0,1,NA,NA,NA,NA,NA,2084.4356254039344,1219.3576690394557,1,1036,2066,3102,5921,▇▇▇▃▁
numeric,week,0,1,NA,NA,NA,NA,NA,9.522483774361215,5.284186738284365,1,5,10,14,22,▇▆▆▆▁
numeric,yardline_100,85487,0.922183383853555,NA,NA,NA,NA,NA,49.03448977033471,24.905220727748304,1,30,51,70,99,▅▆▆▇▃
numeric,quarter_seconds_remaining,1199,0.9989085811555022,NA,NA,NA,NA,NA,416.734325036838,282.64536464321304,0,150,400,663,900,▇▅▅▅▆
numeric,half_seconds_remaining,1199,0.9989085811555022,NA,NA,NA,NA,NA,815.5808409371124,558.844159835077,0,287,806,1296,1800,▇▅▅▅▅
numeric,game_seconds_remaining,1199,0.9989085811555022,NA,NA,NA,NA,NA,1714.1759377639833,1058.2081334837549,0,801,1800,2607,3600,▇▆▇▆▆
numeric,quarter_end,0,1,NA,NA,NA,NA,NA,0.01757557552090445,0.13140277920743262,0,0,0,0,1,▇▁▁▁▁
numeric,drive,14081,0.9871824280655762,NA,NA,NA,NA,NA,12.280475873890838,7.123816430268896,1,6,12,18,38,▇▇▇▂▁
numeric,sp,0,1,NA,NA,NA,NA,NA,0.07154209563341436,0.2577283155762031,0,0,0,0,1,▇▁▁▁▁
numeric,qtr,0,1,NA,NA,NA,NA,NA,2.5646176392947195,1.1313198255404997,1,2,3,4,6,▇▃▅▁▁
numeric,down,184365,0.8321772850159753,NA,NA,NA,NA,NA,2.0047494817901894,1.0067423782563265,1,1,2,3,4,▇▆▁▃▂
numeric,goal_to_go,13,0.9999881664345467,NA,NA,NA,NA,NA,0.04769165368751918,0.21311311831669968,0,0,0,0,1,▇▁▁▁▁
numeric,ydstogo,0,1,NA,NA,NA,NA,NA,7.136612141238155,4.9257457058179615,0,3,9,10,50,▇▁▁▁▁
numeric,ydsnet,14081,0.9871824280655762,NA,NA,NA,NA,NA,38.70946777698989,28.730318595751015,-39,12,37,65,99,▁▇▇▇▅
numeric,yards_gained,50525,0.9540083927287292,NA,NA,NA,NA,NA,3.9359645816734976,7.807584532205186,-38,0,0,6,99,▁▇▁▁▁
numeric,shotgun,0,1,NA,NA,NA,NA,NA,0.2984989577359661,0.45759973839118473,0,0,0,1,1,▇▁▁▁▃
numeric,no_huddle,0,1,NA,NA,NA,NA,NA,0.043568457176147136,0.20413300724484748,0,0,0,0,1,▇▁▁▁▁
numeric,qb_dropback,50328,0.9541877167590596,NA,NA,NA,NA,NA,0.4362780731930223,0.4959231297944922,0,0,0,1,1,▇▁▁▁▆
numeric,qb_kneel,0,1,NA,NA,NA,NA,NA,0.00735046469501261,0.08541921332781825,0,0,0,0,1,▇▁▁▁▁
numeric,qb_spike,0,1,NA,NA,NA,NA,NA,0.0015210682978781499,0.03897122055563391,0,0,0,0,1,▇▁▁▁▁
numeric,qb_scramble,0,1,NA,NA,NA,NA,NA,0.014260356645457247,0.1185622691649317,0,0,0,0,1,▇▁▁▁▁
numeric,air_yards,804184,0.267971999963589,NA,NA,NA,NA,NA,8.308679760586442,10.100947914566389,-93,2,6,13,78,▁▁▇▃▁
numeric,yards_after_catch,915119,0.1669907243052332,NA,NA,NA,NA,NA,5.121536541092717,7.023980347723798,-72,1,3,7,91,▁▁▇▁▁
numeric,kick_distance,964499,0.1220413810681158,NA,NA,NA,NA,NA,41.25097895890983,15.058408894839559,-2,31,41,53,88,▁▇▇▆▁
numeric,home_timeouts_remaining,0,1,NA,NA,NA,NA,NA,2.5088369425707966,0.7915343388518676,-1,2,3,3,3,▁▁▁▃▇
numeric,away_timeouts_remaining,0,1,NA,NA,NA,NA,NA,2.4807158396824964,0.813320107324933,0,2,3,3,3,▁▁▁▃▇
numeric,timeout,50525,0.9540083927287292,NA,NA,NA,NA,NA,0.04347332414161605,0.20392016552278353,0,0,0,0,1,▇▁▁▁▁
numeric,posteam_timeouts_remaining,74782,0.931927869867191,NA,NA,NA,NA,NA,2.5355298167198677,0.7704586202045379,-1,2,3,3,3,▁▁▁▂▇
numeric,defteam_timeouts_remaining,74782,0.931927869867191,NA,NA,NA,NA,NA,2.5542592802416126,0.7423333886351559,-1,2,3,3,3,▁▁▁▂▇
numeric,total_home_score,0,1,NA,NA,NA,NA,NA,11.808507423286635,10.161861231134086,0,3,10,17,62,▇▅▁▁▁
numeric,total_away_score,0,1,NA,NA,NA,NA,NA,10.394369043392777,9.571924926888174,0,3,7,17,59,▇▃▁▁▁
numeric,posteam_score,75540,0.9312378819738387,NA,NA,NA,NA,NA,10.229523083389541,9.55150831293642,0,0,7,17,62,▇▃▁▁▁
numeric,defteam_score,75540,0.9312378819738387,NA,NA,NA,NA,NA,11.41926434219915,10.011129519281944,0,3,10,17,62,▇▅▁▁▁
numeric,score_differential,75540,0.9312378819738387,NA,NA,NA,NA,NA,-1.1897412588096141,10.834589890553639,-59,-7,0,4,59,▁▂▇▁▁
numeric,posteam_score_post,74782,0.931927869867191,NA,NA,NA,NA,NA,10.472527515462184,9.629131505015522,0,3,7,17,62,▇▃▁▁▁
numeric,defteam_score_post,74782,0.931927869867191,NA,NA,NA,NA,NA,11.424630880612003,10.018617374348864,0,3,10,17,62,▇▅▁▁▁
numeric,score_differential_post,74782,0.931927869867191,NA,NA,NA,NA,NA,-0.9521033651498161,10.915129362273541,-59,-7,0,6,59,▁▂▇▁▁
numeric,no_score_prob,0,1,NA,NA,NA,NA,NA,0.1318170844272374,0.2041972997826963,0,0.006777436123229563,0.03241235762834549,0.17009594291448593,1,▇▁▁▁▁
numeric,opp_fg_prob,0,1,NA,NA,NA,NA,NA,0.0900442372636615,0.07039615565190616,0,0.02218738803640008,0.08674044534564018,0.14487330988049507,0.42820701003074646,▇▆▂▁▁
numeric,opp_safety_prob,0,1,NA,NA,NA,NA,NA,0.0024300688393332974,0.005656309098386118,0,4.499515416682698e-4,0.0013044169172644615,0.002646706940140575,0.3727701008319855,▇▁▁▁▁
numeric,opp_td_prob,0,1,NA,NA,NA,NA,NA,0.13686450993658264,0.11023031029440622,0,0.030053429771214724,0.12771396338939667,0.22834347561001778,0.5410013794898987,▇▅▅▁▁
numeric,fg_prob,0,1,NA,NA,NA,NA,NA,0.2320199917491022,0.16120988501708008,0,0.14781925082206726,0.21269237995147705,0.2992970049381256,0.9976794235436337,▇▇▂▁▁
numeric,safety_prob,0,1,NA,NA,NA,NA,NA,0.0026556686697281505,0.002310675572790794,0,0.001050723367370665,0.0024312720634043217,0.003875198948662728,0.3445877730846405,▇▁▁▁▁
numeric,td_prob,0,1,NA,NA,NA,NA,NA,0.2910022321016449,0.174859975956561,0,0.1884789690375328,0.3141609728336334,0.39814645051956177,0.9335877299308777,▅▇▅▁▁
numeric,extra_point_prob,0,1,NA,NA,NA,NA,NA,0.02504230941374404,0.1535238490465528,0,0,0,0,0.9963630685616458,▇▁▁▁▁
numeric,two_point_conversion_prob,0,1,NA,NA,NA,NA,NA,8.469442092902586e-4,0.02000777681298465,0,0,0,0,0.4735,▇▁▁▁▁
numeric,ep,17843,0.9837579762782527,NA,NA,NA,NA,NA,1.687473113671753,1.7057576445967129,-3.8036762471310794,0.4870520166296046,1.4019992728717625,2.8423898457549512,6.593665642023552,▁▃▇▅▁
numeric,epa,18018,0.9835986782817663,NA,NA,NA,NA,NA,-0.007954446230637966,1.2560468088794987,-13.58485902735265,-0.5379002675181255,-0,0.5221822524326853,9.579868719680235,▁▁▇▃▁
numeric,total_home_epa,0,1,NA,NA,NA,NA,NA,0.24846134966507072,12.107505734241665,-63.419816149475174,-6.520948685618038,0.1629172118846327,7.009262653625,65.34455354430793,▁▂▇▁▁
numeric,total_away_epa,0,1,NA,NA,NA,NA,NA,-0.22035254191216969,12.12565119448133,-65.34455354430793,-6.986512561861116,-0.1464349998728821,6.554438007757298,73.00163108506858,▁▂▇▁▁
numeric,total_home_rush_epa,0,1,NA,NA,NA,NA,NA,-0.06469372946176401,5.308144641341979,-32.110373332952676,-2.927859448711388,0,2.827283695190957,33.16040635136608,▁▁▇▁▁
numeric,total_away_rush_epa,0,1,NA,NA,NA,NA,NA,0.06469372946176401,5.308144641341979,-33.16040635136608,-2.827283695190957,0,2.927859448711388,32.110373332952676,▁▁▇▁▁
numeric,total_home_pass_epa,0,1,NA,NA,NA,NA,NA,-0.1637843757034343,10.596039297207732,-60.38258939230582,-6.080178061468196,0,5.74475710087931,53.981246434958145,▁▁▇▂▁
numeric,total_away_pass_epa,0,1,NA,NA,NA,NA,NA,0.16382928846033679,10.595990115688988,-53.981246434958145,-5.74475710087931,0,6.080178061468196,60.38258939230582,▁▂▇▁▁
numeric,air_epa,805471,0.26680047698371523,NA,NA,NA,NA,NA,0.5055065487066353,1.354761434024009,-11.79624876496382,-0.4898784961551428,0.2779173366725445,1.3612197960610501,7.454971208120696,▁▁▅▇▁
numeric,yac_epa,805500,0.2667740790300117,NA,NA,NA,NA,NA,-0.36660423146545995,1.924923089183378,-14,-0.8769923797808588,0,0.5234156415099278,9.848225327499676,▁▁▇▅▁
numeric,comp_air_epa,364010,0.6686510645657537,NA,NA,NA,NA,NA,0.05577522160824954,0.6080947516859125,-11.79624876496382,0,0,0,7.423614024184644,▁▁▁▇▁
numeric,comp_yac_epa,364019,0.668642872097363,NA,NA,NA,NA,NA,0.1588122908959473,0.5770241464224364,-10.914922855328768,0,0,0,9.848225327499676,▁▁▇▁▁
numeric,total_home_comp_air_epa,328090,0.7013481161874073,NA,NA,NA,NA,NA,-0.1715972755615049,6.026821816064234,-34.2570441190619,-3.49196311540436,0,3.224452398380345,30.63045173761202,▁▁▇▂▁
numeric,total_away_comp_air_epa,328090,0.7013481161874073,NA,NA,NA,NA,NA,0.1715972755615049,6.026821816064234,-30.63045173761202,-3.224452398380345,0,3.49196311540436,34.2570441190619,▁▂▇▁▁
numeric,total_home_comp_yac_epa,328090,0.7013481161874073,NA,NA,NA,NA,NA,-0.06711449665539697,6.386129449480004,-32.63186197145842,-3.6308591519482434,0,3.5630386369884945,35.91268990805838,▁▂▇▁▁
numeric,total_away_comp_yac_epa,328090,0.7013481161874073,NA,NA,NA,NA,NA,0.06711449665539697,6.386129449480004,-35.91268990805838,-3.5630386369884945,0,3.6308591519482434,32.63186197145842,▁▁▇▂▁
numeric,total_home_raw_air_epa,328090,0.7013481161874073,NA,NA,NA,NA,NA,-0.5431016530492653,9.369514500698392,-67.52350558768376,-5.610673192248214,-0.13607840356417,4.56955827208003,62.42438889516052,▁▁▇▁▁
numeric,total_away_raw_air_epa,328090,0.7013481161874073,NA,NA,NA,NA,NA,0.5431016530492653,9.369514500698392,-62.42438889516052,-4.56955827208003,0.13607840356417,5.610673192248214,67.52350558768376,▁▁▇▁▁
numeric,total_home_raw_yac_epa,328090,0.7013481161874073,NA,NA,NA,NA,NA,0.28727892012474604,12.25002005575581,-66.52721119566374,-6.30992435511531,0,6.773971046050304,83.97783668081532,▁▃▇▁▁
numeric,total_away_raw_yac_epa,328090,0.7013481161874073,NA,NA,NA,NA,NA,-0.28727892012474604,12.25002005575581,-83.97783668081532,-6.773971046050304,0,6.30992435511531,66.52721119566374,▁▁▇▃▁
numeric,wp,6298,0.994267092675023,NA,NA,NA,NA,NA,0.5092682336602672,0.3000892471142395,0,0.2650805339217186,0.5197814106941223,0.7546021823708784,0.999977398025294,▇▆▇▇▇
numeric,def_wp,6298,0.994267092675023,NA,NA,NA,NA,NA,0.49073176633973276,0.3000892471142395,2.2601974706049077e-5,0.24539781762912163,0.4802185893058777,0.7349194660782814,1,▇▇▇▆▇
numeric,home_wp,0,1,NA,NA,NA,NA,NA,0.5651212434687914,0.29463946094535143,0,0.34911757707595825,0.58470419049263,0.8092272281646729,1,▅▅▇▇▇
numeric,away_wp,0,1,NA,NA,NA,NA,NA,0.43487875653120855,0.29463946094535143,0,0.19077277183532715,0.41529580950737,0.6508824229240417,1,▇▇▇▅▅
numeric,wpa,14462,0.9868356135703688,NA,NA,NA,NA,NA,2.3231512244109806e-4,0.041179407416532865,-0.999494194984436,-0.01393437385559082,-0,0.01011665165424347,0.9997061546600889,▁▁▇▁▁
numeric,vegas_wpa,14462,0.9868356135703688,NA,NA,NA,NA,NA,5.26771687176859e-4,0.0399261106770947,-0.9998733997344971,-0.011666126549243927,0,0.008488729596138,0.9998747144678148,▁▁▇▁▁
numeric,vegas_home_wpa,6134,0.9944163776545873,NA,NA,NA,NA,NA,4.930193089403416e-6,0.039854870927841776,-0.9998747144678148,-0.010171317495405674,0,0.010242700576782227,0.9998733997344971,▁▁▇▁▁
numeric,home_wp_post,84757,0.9228478840674695,NA,NA,NA,NA,NA,0.5654515316738287,0.2932497903348318,0,0.3504820764064789,0.588352620601654,0.8072708249092102,1,▅▅▇▇▇
numeric,away_wp_post,84757,0.9228478840674695,NA,NA,NA,NA,NA,0.4345613652772663,0.293342597120003,-0.9994123093201779,0.19272546470165253,0.41165006160736084,0.6495179235935211,1.9977154731750488,▁▃▇▂▁
numeric,vegas_wp,6298,0.994267092675023,NA,NA,NA,NA,NA,0.5093007509900243,0.3234289117543515,0,0.22046128660440445,0.5167959928512573,0.799371525645256,0.9999985694885254,▇▆▆▆▇
numeric,vegas_home_wp,0,1,NA,NA,NA,NA,NA,0.5658029819469882,0.3181085215410204,0,0.2971372455358505,0.60519078373909,0.8528302535414696,1,▅▃▅▅▇
numeric,total_home_rush_wpa,0,1,NA,NA,NA,NA,NA,-0.005736035352490824,0.15295769414640503,-1.0790940578000532,-0.08720871806144714,0,0.08142374248139406,1.0827744475655492,▁▁▇▁▁
numeric,total_away_rush_wpa,0,1,NA,NA,NA,NA,NA,0.005736035352490824,0.15295769414640503,-1.0827744475655492,-0.08142374248139406,0,0.08720871806144714,1.0790940578000532,▁▁▇▁▁
numeric,total_home_pass_wpa,0,1,NA,NA,NA,NA,NA,-0.011704553292779056,0.2612775797505144,-1.8669247376815488,-0.1780981719493866,0.0036022216081619263,0.1692317584797332,1.7035376865755814,▁▁▇▁▁
numeric,total_away_pass_wpa,0,1,NA,NA,NA,NA,NA,0.011704553292779056,0.2612775797505144,-1.7035376865755814,-0.1692317584797332,-0.0036022216081619263,0.1780981719493866,1.8669247376815488,▁▁▇▁▁
numeric,air_wpa,805469,0.2668022975322465,NA,NA,NA,NA,NA,0.0031944892416476147,0.04235070909282636,-0.9980781078338623,0,0,0,0.9912653528153896,▁▁▇▁▁
numeric,yac_wpa,805469,0.2668022975322465,NA,NA,NA,NA,NA,3.550292191821682e-4,0.05655707094397412,-0.99085608497262,-0.015901625156402588,0,0.011798828840255737,1,▁▁▇▁▁
numeric,comp_air_wpa,364008,0.668652885114285,NA,NA,NA,NA,NA,0.001331281430309251,0.021105782500084776,-0.99611663818359375,0,0,0,0.9882552844937891,▁▁▇▁▁
numeric,comp_yac_wpa,364008,0.668652885114285,NA,NA,NA,NA,NA,0.004087812878937085,0.026691557398439505,-0.9883022714639083,0,0,0,1,▁▁▇▁▁
numeric,total_home_comp_air_wpa,328090,0.7013481161874073,NA,NA,NA,NA,NA,-0.006595088517105849,0.1518415145504115,-1.9444250103439105,-0.04968388275176994,0,0.04606897134688148,3.0175069247978037,▁▇▃▁▁
numeric,total_away_comp_air_wpa,328090,0.7013481161874073,NA,NA,NA,NA,NA,0.006595088517105849,0.1518415145504115,-3.0175069247978037,-0.04606897134688148,0,0.04968388275176994,1.9444250103439105,▁▁▃▇▁
numeric,total_home_comp_yac_wpa,328090,0.7013481161874073,NA,NA,NA,NA,NA,-1.2000175624890671e-4,0.23046011134609773,-2.555464788224241,-0.11639988422393799,0,0.11682116985321045,2.106908860423353,▁▁▇▁▁
numeric,total_away_comp_yac_wpa,328090,0.7013481161874073,NA,NA,NA,NA,NA,1.2000175624890671e-4,0.23046011134609773,-2.106908860423353,-0.11682116985321045,0,0.11639988422393799,2.555464788224241,▁▁▇▁▁
numeric,total_home_raw_air_wpa,328090,0.7013481161874073,NA,NA,NA,NA,NA,-0.011168386565439632,0.1927320921131443,-2.9340697821495256,-0.05357837677001953,0,0.04698159838693505,3.905425994589482,▁▁▇▁▁
numeric,total_away_raw_air_wpa,328090,0.7013481161874073,NA,NA,NA,NA,NA,0.011168386565439632,0.1927320921131443,-3.905425994589482,-0.04698159838693505,0,0.05357837677001953,2.9340697821495256,▁▁▇▁▁
numeric,total_home_raw_yac_wpa,328090,0.7013481161874073,NA,NA,NA,NA,NA,-0.0026903383881771385,0.30053654108944405,-3.7097175012884205,-0.1533583104610443,0,0.14303510306494469,3.265507598971233,▁▁▇▁▁
numeric,total_away_raw_yac_wpa,328090,0.7013481161874073,NA,NA,NA,NA,NA,0.0026903383881771385,0.30053654108944405,-3.265507598971233,-0.14303510306494469,0,0.1533583104610443,3.7097175012884205,▁▁▇▁▁
numeric,punt_blocked,50525,0.9540083927287292,NA,NA,NA,NA,NA,3.024679283809378e-4,0.017388983007877862,0,0,0,0,1,▇▁▁▁▁
numeric,first_down_rush,50525,0.9540083927287292,NA,NA,NA,NA,NA,0.07168966981379617,0.25797349583877194,0,0,0,0,1,▇▁▁▁▁
numeric,first_down_pass,50525,0.9540083927287292,NA,NA,NA,NA,NA,0.13458868655448952,0.3412838747160773,0,0,0,0,1,▇▁▁▁▁
numeric,first_down_penalty,50525,0.9540083927287292,NA,NA,NA,NA,NA,0.019788272450133332,0.13927209063948912,0,0,0,0,1,▇▁▁▁▁
numeric,third_down_converted,50525,0.9540083927287292,NA,NA,NA,NA,NA,0.06017108044024827,0.23780364899861764,0,0,0,0,1,▇▁▁▁▁
numeric,third_down_failed,50525,0.9540083927287292,NA,NA,NA,NA,NA,0.09510087830198129,0.2933543648216251,0,0,0,0,1,▇▁▁▁▁
numeric,fourth_down_converted,50525,0.9540083927287292,NA,NA,NA,NA,NA,0.005742119851723924,0.07555893963498897,0,0,0,0,1,▇▁▁▁▁
numeric,fourth_down_failed,50525,0.9540083927287292,NA,NA,NA,NA,NA,0.00593295135227972,0.07679685584657968,0,0,0,0,1,▇▁▁▁▁
numeric,incomplete_pass,50525,0.9540083927287292,NA,NA,NA,NA,NA,0.14255017675767742,0.34961370180594376,0,0,0,0,1,▇▁▁▁▁
numeric,touchback,0,1,NA,NA,NA,NA,NA,0.023482345230618002,0.15142967201489163,0,0,0,0,1,▇▁▁▁▁
numeric,interception,50525,0.9540083927287292,NA,NA,NA,NA,NA,0.01112929311241407,0.10490682746207507,0,0,0,0,1,▇▁▁▁▁
numeric,punt_inside_twenty,50525,0.9540083927287292,NA,NA,NA,NA,NA,0.017976327352356058,0.132865329756134,0,0,0,0,1,▇▁▁▁▁
numeric,punt_in_endzone,50525,0.9540083927287292,NA,NA,NA,NA,NA,3.339551259726445e-5,0.005778791326959958,0,0,0,0,1,▇▁▁▁▁
numeric,punt_out_of_bounds,50525,0.9540083927287292,NA,NA,NA,NA,NA,0.0051133300573925735,0.07132453131353966,0,0,0,0,1,▇▁▁▁▁
numeric,punt_downed,50525,0.9540083927287292,NA,NA,NA,NA,NA,0.007430978631642728,0.08588228121016313,0,0,0,0,1,▇▁▁▁▁
numeric,punt_fair_catch,50525,0.9540083927287292,NA,NA,NA,NA,NA,0.012493738341388016,0.11107500445965617,0,0,0,0,1,▇▁▁▁▁
numeric,kickoff_inside_twenty,50525,0.9540083927287292,NA,NA,NA,NA,NA,0.0064730044988526225,0.08019420707197665,0,0,0,0,1,▇▁▁▁▁
numeric,kickoff_in_endzone,50525,0.9540083927287292,NA,NA,NA,NA,NA,0.011002390164544478,0.10431369976053685,0,0,0,0,1,▇▁▁▁▁
numeric,kickoff_out_of_bounds,50525,0.9540083927287292,NA,NA,NA,NA,NA,7.356554346425972e-4,0.0271130032851308,0,0,0,0,1,▇▁▁▁▁
numeric,kickoff_downed,50525,0.9540083927287292,NA,NA,NA,NA,NA,3.8166300111159326e-5,0.006177773050218164,0,0,0,0,1,▇▁▁▁▁
numeric,kickoff_fair_catch,50525,0.9540083927287292,NA,NA,NA,NA,NA,9.636990778067718e-5,0.009816349248312638,0,0,0,0,1,▇▁▁▁▁
numeric,fumble_forced,50525,0.9540083927287292,NA,NA,NA,NA,NA,0.01097281128195831,0.10417494444176967,0,0,0,0,1,▇▁▁▁▁
numeric,fumble_not_forced,50525,0.9540083927287292,NA,NA,NA,NA,NA,0.005325153023009507,0.072779123533286,0,0,0,0,1,▇▁▁▁▁
numeric,fumble_out_of_bounds,50525,0.9540083927287292,NA,NA,NA,NA,NA,0.001254717116154364,0.03539977396551467,0,0,0,0,1,▇▁▁▁▁
numeric,solo_tackle,50525,0.9540083927287292,NA,NA,NA,NA,NA,0.4764241993425855,0.49944411061962346,0,0,0,1,1,▇▁▁▁▇
numeric,safety,50525,0.9540083927287292,NA,NA,NA,NA,NA,3.730755835865827e-4,0.019311570470469743,0,0,0,0,1,▇▁▁▁▁
numeric,penalty,50525,0.9540083927287292,NA,NA,NA,NA,NA,0.07373538349975431,0.2613398972362713,0,0,0,0,1,▇▁▁▁▁
numeric,tackled_for_loss,50525,0.9540083927287292,NA,NA,NA,NA,NA,0.029865129836982186,0.17021525049721078,0,0,0,0,1,▇▁▁▁▁
numeric,fumble_lost,50525,0.9540083927287292,NA,NA,NA,NA,NA,0.007655205644795784,0.08715853784738917,0,0,0,0,1,▇▁▁▁▁
numeric,own_kickoff_recovery,50525,0.9540083927287292,NA,NA,NA,NA,NA,2.4712679321975634e-4,0.015718331886929632,0,0,0,0,1,▇▁▁▁▁
numeric,own_kickoff_recovery_td,50525,0.9540083927287292,NA,NA,NA,NA,NA,9.54157502778982e-7,9.768098600950877e-4,0,0,0,0,1,▇▁▁▁▁
numeric,qb_hit,50525,0.9540083927287292,NA,NA,NA,NA,NA,0.04588161767863027,0.20922843164238794,0,0,0,0,1,▇▁▁▁▁
numeric,rush_attempt,50525,0.9540083927287292,NA,NA,NA,NA,NA,0.3186847892981695,0.4659667386623199,0,0,0,1,1,▇▁▁▁▃
numeric,pass_attempt,50525,0.9540083927287292,NA,NA,NA,NA,NA,0.4246687880768479,0.49429287030579566,0,0,0,1,1,▇▁▁▁▆
numeric,sack,50525,0.9540083927287292,NA,NA,NA,NA,NA,0.026963536871031302,0.16197694152013542,0,0,0,0,1,▇▁▁▁▁
numeric,touchdown,50525,0.9540083927287292,NA,NA,NA,NA,NA,0.0290970330472451,0.16807862050375538,0,0,0,0,1,▇▁▁▁▁
numeric,pass_touchdown,50525,0.9540083927287292,NA,NA,NA,NA,NA,0.016936295674326952,0.1290328386472942,0,0,0,0,1,▇▁▁▁▁
numeric,rush_touchdown,50525,0.9540083927287292,NA,NA,NA,NA,NA,0.00968946944072058,0.09795709662084069,0,0,0,0,1,▇▁▁▁▁
numeric,return_touchdown,50525,0.9540083927287292,NA,NA,NA,NA,NA,0.0022794822741389917,0.04768949994212801,0,0,0,0,1,▇▁▁▁▁
numeric,extra_point_attempt,50525,0.9540083927287292,NA,NA,NA,NA,NA,0.027105706338945365,0.16239153975780735,0,0,0,0,1,▇▁▁▁▁
numeric,two_point_attempt,50525,0.9540083927287292,NA,NA,NA,NA,NA,0.0018749194929607034,0.04325974983135766,0,0,0,0,1,▇▁▁▁▁
numeric,field_goal_attempt,50525,0.9540083927287292,NA,NA,NA,NA,NA,0.022192749357136384,0.14731005375929296,0,0,0,0,1,▇▁▁▁▁
numeric,kickoff_attempt,50498,0.9540329701339013,NA,NA,NA,NA,NA,0.05856372462960561,0.2348064466583969,0,0,0,0,1,▇▁▁▁▁
numeric,punt_attempt,50525,0.9540083927287292,NA,NA,NA,NA,NA,0.0547314285169053,0.22745537719220404,0,0,0,0,1,▇▁▁▁▁
numeric,fumble,50525,0.9540083927287292,NA,NA,NA,NA,NA,0.016238806539795515,0.12639273295859219,0,0,0,0,1,▇▁▁▁▁
numeric,complete_pass,50525,0.9540083927287292,NA,NA,NA,NA,NA,0.24267374015428733,0.4286996283554495,0,0,0,0,1,▇▁▁▁▂
numeric,assist_tackle,50525,0.9540083927287292,NA,NA,NA,NA,NA,0.13535201255671275,0.3420993377960261,0,0,0,0,1,▇▁▁▁▁
numeric,lateral_reception,50525,0.9540083927287292,NA,NA,NA,NA,NA,2.1277712311971333e-4,0.014585336883167023,0,0,0,0,1,▇▁▁▁▁
numeric,lateral_rush,50525,0.9540083927287292,NA,NA,NA,NA,NA,3.721214260838033e-5,0.00610006502996325,0,0,0,0,1,▇▁▁▁▁
numeric,lateral_return,50525,0.9540083927287292,NA,NA,NA,NA,NA,2.776598333086835e-4,0.016660822404177992,0,0,0,0,1,▇▁▁▁▁
numeric,lateral_recovery,50525,0.9540083927287292,NA,NA,NA,NA,NA,0.001992280865802518,0.044590509975986924,0,0,0,0,1,▇▁▁▁▁
numeric,passing_yards,844237,0.23151278480206083,NA,NA,NA,NA,NA,11.454679494992785,10.155601152890332,-22,5,9,15,99,▁▇▁▁▁
numeric,receiving_yards,844237,0.23151278480206083,NA,NA,NA,NA,NA,11.449501244431513,10.148341932961369,-22,5,9,15,99,▁▇▁▁▁
numeric,rushing_yards,765120,0.30353095387640294,NA,NA,NA,NA,NA,4.177474883790673,6.277634572361271,-34,1,3,6,99,▁▇▁▁▁
numeric,lateral_receiving_yards,1098347,2.0299116123689842e-4,NA,NA,NA,NA,NA,5.941704035874439,10.321900567115344,-21,0,4,10,62,▁▇▂▁▁
numeric,lateral_rushing_yards,1098531,3.550069635982478e-5,NA,NA,NA,NA,NA,9.692307692307692,9.878615517086033,0,4,6,12,44,▇▃▁▁▁
numeric,tackle_with_assist,50525,0.9540083927287292,NA,NA,NA,NA,NA,0.07944029120886999,0.2704248529974212,0,0,0,0,1,▇▁▁▁▁
numeric,fumble_recovery_1_yards,1082877,0.014284934050629472,NA,NA,NA,NA,NA,2.3068246989103423,9.281173192373814,-100,0,0,0,104,▁▁▇▁▁
numeric,fumble_recovery_2_yards,1098447,1.1196373467325937e-4,NA,NA,NA,NA,NA,3.926829268292683,12.171702422588814,-16,0,0,1.5,77,▇▂▁▁▁
numeric,return_yards,50525,0.9540083927287292,NA,NA,NA,NA,NA,1.215521280097707,5.810803247891786,-100,0,0,0,109,▁▁▇▁▁
numeric,penalty_yards,1021292,0.07034417469983711,NA,NA,NA,NA,NA,8.364502186909599,5.267519745457818,0,5,5,10,66,▇▂▁▁▁
numeric,replay_or_challenge,0,1,NA,NA,NA,NA,NA,0.0074205558134665915,0.08582247881242441,0,0,0,0,1,▇▁▁▁▁
numeric,defensive_two_point_attempt,50525,0.9540083927287292,NA,NA,NA,NA,NA,4.7707875138949524e-5,0.006906927291951021,0,0,0,0,1,▇▁▁▁▁
numeric,defensive_two_point_conv,50525,0.9540083927287292,NA,NA,NA,NA,NA,1.0495732530568788e-5,0.0032396963414267495,0,0,0,0,1,▇▁▁▁▁
numeric,defensive_extra_point_attempt,50525,0.9540083927287292,NA,NA,NA,NA,NA,0,0,0,0,0,0,0,▁▁▇▁▁
numeric,defensive_extra_point_conv,50525,0.9540083927287292,NA,NA,NA,NA,NA,0,0,0,0,0,0,0,▁▁▇▁▁
numeric,season,0,1,NA,NA,NA,NA,NA,2010.1182082161356,6.627584365671061,1999,2004,2010,2016,2021,▇▆▇▆▇
numeric,cp,811614,0.2612086621699118,NA,NA,NA,NA,NA,0.6348154096544791,0.17004701657348936,0.09544014185667038,0.5279483497142792,0.6781390309333801,0.7639535367488861,0.926070511341095,▁▃▃▇▆
numeric,cpoe,811614,0.2612086621699118,NA,NA,NA,NA,NA,0.06548366550596109,44.90345874861157,-92.05909371376038,-44.26913559436798,20.371761918067932,32.09476172924042,85.26444137096405,▃▃▁▇▁
numeric,series,0,1,NA,NA,NA,NA,NA,29.29300545254285,17.06057955007624,1,15,29,44,82,▇▇▇▃▁
numeric,series_success,0,1,NA,NA,NA,NA,NA,0.550455592269951,0.49744794547782784,0,0,1,1,1,▆▁▁▁▇
numeric,order_sequence,91628,0.916593389588283,NA,NA,NA,NA,NA,2089.286688328847,1223.2124087724426,1,1038,2071,3110,5921,▇▇▇▃▁
numeric,play_deleted,91628,0.916593389588283,NA,NA,NA,NA,NA,0,0,0,0,0,0,0,▁▁▇▁▁
numeric,special_teams_play,91628,0.916593389588283,NA,NA,NA,NA,NA,0.15910747590228633,0.36577646163240873,0,0,0,0,1,▇▁▁▁▂
numeric,fixed_drive,0,1,NA,NA,NA,NA,NA,12.20017932403033,7.136661236285931,1,6,12,18,38,▇▆▆▁▁
numeric,drive_play_count,14081,0.9871824280655762,NA,NA,NA,NA,NA,7.189677350346567,3.602393232327467,0,4,7,10,24,▅▇▅▁▁
numeric,drive_first_downs,14081,0.9871824280655762,NA,NA,NA,NA,NA,2.3803994323593884,1.8755856899745,0,1,2,4,9,▇▇▅▁▁
numeric,drive_inside20,14081,0.9871824280655762,NA,NA,NA,NA,NA,0.37966636821581407,0.4853040636890067,0,0,0,1,1,▇▁▁▁▅
numeric,drive_ended_with_score,14081,0.9871824280655762,NA,NA,NA,NA,NA,0.4375959553301142,0.4960906793535729,0,0,0,1,1,▇▁▁▁▆
numeric,drive_quarter_start,14081,0.9871824280655762,NA,NA,NA,NA,NA,2.5190509078469216,1.130511492046773,1,2,3,4,5,▇▇▇▇▁
numeric,drive_quarter_end,14081,0.9871824280655762,NA,NA,NA,NA,NA,2.6349700181375746,1.1228361579111892,1,2,3,4,6,▇▃▅▁▁
numeric,drive_yards_penalized,105709,0.9037758176538591,NA,NA,NA,NA,NA,0.0910671282284217,7.611621086271443,-40,0,0,0,77,▁▇▁▁▁
numeric,drive_play_id_started,14081,0.9871824280655762,NA,NA,NA,NA,NA,1994.7812905432884,1209.712470152506,10,953,1986,3005,5764,▇▇▇▃▁
numeric,drive_play_id_ended,14081,0.9871824280655762,NA,NA,NA,NA,NA,2192.7340221984737,1213.3905594679325,34,1149,2164,3206,5921,▇▇▇▅▁
numeric,away_score,0,1,NA,NA,NA,NA,NA,21.140365202035373,10.101971087488094,0,14,21,28,59,▃▇▆▂▁
numeric,home_score,0,1,NA,NA,NA,NA,NA,23.40198530817335,10.330063582737433,0,16,23,30,62,▂▇▆▂▁
numeric,result,0,1,NA,NA,NA,NA,NA,2.2616201061379795,14.548871420505362,-49,-7,3,11,59,▁▃▇▂▁
numeric,total,0,1,NA,NA,NA,NA,NA,44.54235051020873,14.34748784077857,3,34,44,54,106,▁▇▆▂▁
numeric,spread_line,0,1,NA,NA,NA,NA,NA,2.339101286217539,5.952923025351251,-19,-3,3,6.5,27,▁▅▇▂▁
numeric,total_line,0,1,NA,NA,NA,NA,NA,43.481633851279376,5.017518021658727,30,40,43.5,47,63.5,▂▇▇▂▁
numeric,div_game,0,1,NA,NA,NA,NA,NA,0.380814149303185,0.4855872193867445,0,0,0,1,1,▇▁▁▁▅
numeric,temp,317103,0.7113492995439525,NA,NA,NA,NA,NA,58.22617333809361,16.860510369502123,-6,46,59,71,109,▁▃▇▇▁
numeric,wind,317103,0.7113492995439525,NA,NA,NA,NA,NA,8.494006784675488,5.383877047778842,0,5,8,12,71,▇▁▁▁▁
numeric,aborted_play,0,1,NA,NA,NA,NA,NA,0.002607935771047818,0.051001341255008464,0,0,0,0,1,▇▁▁▁▁
numeric,success,18018,0.9835986782817663,NA,NA,NA,NA,NA,0.41713494584249533,0.49308580166962673,0,0,0,1,1,▇▁▁▁▆
numeric,passer_jersey_number,656502,0.40240312406127965,NA,NA,NA,NA,NA,9.03425717310459,4.860778988279489,1,5,9,12,92,▇▁▁▁▁
numeric,rusher_jersey_number,794957,0.2763711006126146,NA,NA,NA,NA,NA,27.7503301900775,10.75144904832512,1,22,28,33,99,▂▇▁▁▁
numeric,receiver_jersey_number,702732,0.3603211447609165,NA,NA,NA,NA,NA,53.07991400522436,32.341174900030225,1,18,80,84,99,▅▃▁▁▇
numeric,pass,0,1,NA,NA,NA,NA,NA,0.43929380922471944,0.49630130225070546,0,0,0,1,1,▇▁▁▁▆
numeric,rush,0,1,NA,NA,NA,NA,NA,0.2900707283104399,0.4537949849222303,0,0,0,1,1,▇▁▁▁▃
numeric,first_down,50525,0.9540083927287292,NA,NA,NA,NA,NA,0.223826267001894,0.41680719159581336,0,0,0,0,1,▇▁▁▁▂
numeric,special,0,1,NA,NA,NA,NA,NA,0.15393466051321264,0.360886269285787,0,0,0,0,1,▇▁▁▁▂
numeric,play,0,1,NA,NA,NA,NA,NA,0.752477311413929,0.43157314184813556,0,1,1,1,1,▂▁▁▁▇
numeric,jersey_number,367370,0.6655925430332159,NA,NA,NA,NA,NA,16.811021608315098,12.101034042875968,1,8,12,26,99,▇▅▁▁▁
numeric,out_of_bounds,0,1,NA,NA,NA,NA,NA,0.06955041554020228,0.25438792059600834,0,0,0,0,1,▇▁▁▁▁
numeric,home_opening_kickoff,0,1,NA,NA,NA,NA,NA,0.48775408030439565,0.4998502424557511,0,0,0,1,1,▇▁▁▁▇
numeric,qb_epa,18018,0.9835986782817663,NA,NA,NA,NA,NA,-7.359714411560366e-4,1.2454625465492268,-13.58485902735265,-0.5353464668150991,0,0.5254294750135534,9.579868719680235,▁▁▇▃▁
numeric,xyac_epa,831471,0.24313334607717307,NA,NA,NA,NA,NA,0.6872020672438497,0.5040984516422667,-1.2820399739124755,0.30739913538713626,0.5661891744628638,0.920687893258089,13.028142577118448,▇▁▁▁▁
numeric,xyac_mean_yardage,831419,0.2431806803389861,NA,NA,NA,NA,NA,5.217610647958738,2.983742858931366,-77.34254090196919,3.6430345882508846,4.496286971581867,6.384836019860813,78.85111491640419,▁▁▇▁▁
numeric,xyac_median_yardage,831419,0.2431806803389861,NA,NA,NA,NA,NA,3.4332418744455384,2.3961516593295906,0,2,3,5,48,▇▁▁▁▁
numeric,xyac_success,831419,0.2431806803389861,NA,NA,NA,NA,NA,0.7963682448146061,0.24753272979377464,0.010269990365486592,0.5846049897518242,0.9878865564242005,1,1,▁▁▃▂▇
numeric,xyac_fd,831419,0.2431806803389861,NA,NA,NA,NA,NA,0.598139960266696,0.35654205947727374,0,0.24512977158883587,0.5134540184517391,0.9991877254215069,1,▂▆▂▁▇
numeric,xpass,522120,0.5247276004260084,NA,NA,NA,NA,NA,0.6137813038965859,0.2410066250760552,0.01067630760371685,0.44443003088235855,0.5740557610988617,0.8400976061820984,0.998187243938446,▁▃▇▅▆
numeric,pass_oe,538745,0.5095942907598059,NA,NA,NA,NA,NA,-0.26308551422534004,41.94502679344846,-99.23535585403442,-41.299596428871155,4.3928563594818115,34.751224517822266,97.72196300327778,▂▇▇▇▂
================================================
FILE: data-raw/replace_models.R
================================================
# Helper function to replace the internal calls to the models
# with a call to the fastrmodels package
models <- c(
"ep_model,",
"wp_model,",
"wp_model_spread,",
"fg_model,",
"cp_model,",
"xyac_model,",
"xpass_model,"
)
purrr::walk(models, function(model) {
xfun::gsub_dir(
# paste0(model,"(?![:alpha:]+)"),
model,
paste0("fastrmodels::", model),
dir = usethis::proj_path("R"),
ext = "R"
)
})
================================================
FILE: data-raw/teams_colors_logos.R
================================================
teams_colors_logos <- nflreadr::load_teams()
use_data(teams_colors_logos, overwrite = TRUE)
================================================
FILE: data-raw/tidy_play_stats_row.R
================================================
# Script to create the tidy_play_stats_row tibble that is used in
# the internal function `sum_play_stats`
library(tidyverse)
tidy_play_stats_row <-
as_tibble_row(
matrix(NA, ncol = length(pbp_stat_columns)),
.name_repair = "minimal"
) |>
set_names(pbp_stat_columns) |>
modify_at(indicator_stats, function(x) {
x <- 0
}) |>
modify_if(is.na, function(x) {
x <- NA_character_
}) |>
modify_at(
c(
"air_yards",
"yards_after_catch",
"penalty_yards",
"kick_distance",
"fumble_recovery_1_yards",
"fumble_recovery_2_yards",
"rushing_yards",
"lateral_rushing_yards",
"passing_yards",
"receiving_yards",
"lateral_receiving_yards"
),
as.integer
)
tidy_play_stats_row <- nflfastR:::tidy_play_stats_row
scramble_fix <- readRDS("data-raw/scramble_fix.rds")
default_play <- readRDS("data-raw/pbp_defaultplay.rds")
usethis::use_data(
tidy_play_stats_row,
scramble_fix,
default_play,
internal = TRUE,
overwrite = TRUE
)
# stats character vectors -------------------------------------------------
pbp_stat_columns <-
c(
# "play_id",
"punt_blocked",
"first_down_rush",
"first_down_pass",
"first_down_penalty",
"third_down_converted",
"third_down_failed",
"fourth_down_converted",
"fourth_down_failed",
"incomplete_pass",
"interception",
"punt_inside_twenty",
"punt_in_endzone",
"punt_out_of_bounds",
"punt_downed",
"punt_fair_catch",
"kickoff_inside_twenty",
"kickoff_in_endzone",
"kickoff_out_of_bounds",
"kickoff_fair_catch",
"fumble_forced",
"fumble_not_forced",
"fumble_out_of_bounds",
"timeout",
"field_goal_missed",
"field_goal_made",
"field_goal_blocked",
"extra_point_good",
"extra_point_failed",
"extra_point_blocked",
"two_point_rush_good",
"two_point_rush_failed",
"two_point_pass_good",
"two_point_pass_failed",
"solo_tackle",
"safety",
"penalty",
"tackled_for_loss",
"extra_point_safety",
"two_point_rush_safety",
"two_point_pass_safety",
"kickoff_downed",
"two_point_pass_reception_good",
"two_point_pass_reception_failed",
"fumble_lost",
"own_kickoff_recovery",
"own_kickoff_recovery_td",
"qb_hit",
"extra_point_aborted",
"two_point_return",
"rush_attempt",
"pass_attempt",
"sack",
"touchdown",
"pass_touchdown",
"rush_touchdown",
"return_touchdown",
"extra_point_attempt",
"two_point_attempt",
"field_goal_attempt",
"kickoff_attempt",
"punt_attempt",
"fumble",
"complete_pass",
"assist_tackle",
"lateral_reception",
"lateral_rush",
"lateral_return",
"lateral_recovery",
"passer_player_id",
"passer_player_name",
"receiver_player_id",
"receiver_player_name",
"rusher_player_id",
"rusher_player_name",
"lateral_receiver_player_id",
"lateral_receiver_player_name",
"lateral_rusher_player_id",
"lateral_rusher_player_name",
"lateral_sack_player_id",
"lateral_sack_player_name",
"interception_player_id",
"interception_player_name",
"lateral_interception_player_id",
"lateral_interception_player_name",
"punt_returner_player_id",
"punt_returner_player_name",
"lateral_punt_returner_player_id",
"lateral_punt_returner_player_name",
"kickoff_returner_player_name",
"kickoff_returner_player_id",
"lateral_kickoff_returner_player_id",
"lateral_kickoff_returner_player_name",
"punter_player_id",
"punter_player_name",
"kicker_player_name",
"kicker_player_id",
"own_kickoff_recovery_player_id",
"own_kickoff_recovery_player_name",
"blocked_player_id",
"blocked_player_name",
"tackle_for_loss_1_player_id",
"tackle_for_loss_1_player_name",
"tackle_for_loss_2_player_id",
"tackle_for_loss_2_player_name",
"qb_hit_1_player_id",
"qb_hit_1_player_name",
"qb_hit_2_player_id",
"qb_hit_2_player_name",
"forced_fumble_player_1_team",
"forced_fumble_player_1_player_id",
"forced_fumble_player_1_player_name",
"forced_fumble_player_2_team",
"forced_fumble_player_2_player_id",
"forced_fumble_player_2_player_name",
"solo_tackle_1_team",
"solo_tackle_2_team",
"solo_tackle_1_player_id",
"solo_tackle_2_player_id",
"solo_tackle_1_player_name",
"solo_tackle_2_player_name",
"assist_tackle_1_player_id",
"assist_tackle_1_player_name",
"assist_tackle_1_team",
"assist_tackle_2_player_id",
"assist_tackle_2_player_name",
"assist_tackle_2_team",
"assist_tackle_3_player_id",
"assist_tackle_3_player_name",
"assist_tackle_3_team",
"assist_tackle_4_player_id",
"assist_tackle_4_player_name",
"assist_tackle_4_team",
# new for stat ID 80 -> tackle_with_assist
"tackle_with_assist",
"tackle_with_assist_1_player_id",
"tackle_with_assist_1_player_name",
"tackle_with_assist_1_team",
"tackle_with_assist_2_player_id",
"tackle_with_assist_2_player_name",
"tackle_with_assist_2_team",
"pass_defense_1_player_id",
"pass_defense_1_player_name",
"pass_defense_2_player_id",
"pass_defense_2_player_name",
"fumbled_1_team",
"fumbled_1_player_id",
"fumbled_1_player_name",
"fumbled_2_player_id",
"fumbled_2_player_name",
"fumbled_2_team",
"fumble_recovery_1_team",
"fumble_recovery_1_yards",
"fumble_recovery_1_player_id",
"fumble_recovery_1_player_name",
"fumble_recovery_2_team",
"fumble_recovery_2_yards",
"fumble_recovery_2_player_id",
"fumble_recovery_2_player_name",
"td_team",
"return_team",
"timeout_team",
"yards_gained",
"return_yards",
"air_yards",
"yards_after_catch",
"penalty_team",
"penalty_player_id",
"penalty_player_name",
"penalty_yards",
"kick_distance",
"defensive_two_point_attempt",
"defensive_two_point_conv",
"defensive_extra_point_attempt",
"defensive_extra_point_conv",
"penalty_fix",
"return_penalty_fix",
#new in nflfastR v4.0
"rushing_yards",
"lateral_rushing_yards",
"passing_yards",
"receiving_yards",
"lateral_receiving_yards",
# new in nflfastR v4.1
"td_player_id",
"td_player_name",
"sack_player_id",
"sack_player_name",
"half_sack_1_player_id",
"half_sack_1_player_name",
"half_sack_2_player_id",
"half_sack_2_player_name",
# new in nflfastR > v4.1
"safety_player_name",
"safety_player_id"
)
indicator_stats <- c(
"punt_blocked",
"first_down_rush",
"first_down_pass",
"first_down_penalty",
"third_down_converted",
"third_down_failed",
"fourth_down_converted",
"fourth_down_failed",
"incomplete_pass",
"interception",
"punt_inside_twenty",
"punt_in_endzone",
"punt_out_of_bounds",
"punt_downed",
"punt_fair_catch",
"kickoff_inside_twenty",
"kickoff_in_endzone",
"kickoff_out_of_bounds",
"kickoff_fair_catch",
"fumble_forced",
"fumble_not_forced",
"fumble_out_of_bounds",
"timeout",
"field_goal_missed",
"field_goal_made",
"field_goal_blocked",
"extra_point_good",
"extra_point_failed",
"extra_point_blocked",
"two_point_rush_good",
"two_point_rush_failed",
"two_point_pass_good",
"two_point_pass_failed",
"solo_tackle",
"safety",
"penalty",
"tackled_for_loss",
"extra_point_safety",
"two_point_rush_safety",
"two_point_pass_safety",
"kickoff_downed",
"two_point_pass_reception_good",
"two_point_pass_reception_failed",
"fumble_lost",
"own_kickoff_recovery",
"own_kickoff_recovery_td",
"qb_hit",
"extra_point_aborted",
"two_point_return",
"defensive_two_point_attempt",
"defensive_two_point_conv",
"defensive_extra_point_attempt",
"defensive_extra_point_conv",
"rush_attempt",
"pass_attempt",
"sack",
"touchdown",
"pass_touchdown",
"rush_touchdown",
"return_touchdown",
"extra_point_attempt",
"two_point_attempt",
"field_goal_attempt",
"kickoff_attempt",
"punt_attempt",
"fumble",
"complete_pass",
"assist_tackle",
# new for stat ID 80 -> tackle_with_assist
"tackle_with_assist",
"lateral_reception",
"lateral_rush",
"lateral_return",
"lateral_recovery",
"penalty_fix",
"yards_gained",
"return_yards",
"return_penalty_fix"
)
================================================
FILE: data-raw/variable_list.txt
================================================
#' \item{play_id}{Numeric play id that when used with game_id and drive provides the unique identifier for a single play.}
#' \item{game_id}{Ten digit identifier for NFL game.}
#' \item{old_game_id}{Legacy NFL game ID.}
#' \item{home_team}{String abbreviation for the home team.}
#' \item{away_team}{String abbreviation for the away team.}
#' \item{season_type}{'REG' or 'POST' indicating if the game belongs to regular or post season.}
#' \item{week}{Season week.}
#' \item{posteam}{String abbreviation for the team with possession.}
#' \item{posteam_type}{String indicating whether the posteam team is home or away.}
#' \item{defteam}{String abbreviation for the team on defense.}
#' \item{side_of_field}{String abbreviation for which team's side of the field the team with possession is currently on.}
#' \item{yardline_100}{Numeric distance in the number of yards from the opponent's endzone for the posteam.}
#' \item{game_date}{Date of the game.}
#' \item{quarter_seconds_remaining}{Numeric seconds remaining in the quarter.}
#' \item{half_seconds_remaining}{Numeric seconds remaining in the half.}
#' \item{game_seconds_remaining}{Numeric seconds remaining in the game.}
#' \item{game_half}{String indicating which half the play is in, either Half1, Half2, or Overtime.}
#' \item{quarter_end}{Binary indicator for whether or not the row of the data is marking the end of a quarter.}
#' \item{drive}{Numeric drive number in the game.}
#' \item{sp}{Binary indicator for whether or not a score occurred on the play.}
#' \item{qtr}{Quarter of the game (5 is overtime).}
#' \item{down}{The down for the given play.}
#' \item{goal_to_go}{Binary indicator for whether or not the posteam is in a goal down situation.}
#' \item{time}{Time at start of play provided in string format as minutes:seconds remaining in the quarter.}
#' \item{yrdln}{String indicating the current field position for a given play.}
#' \item{ydstogo}{Numeric yards in distance from either the first down marker or the endzone in goal down situations.}
#' \item{ydsnet}{Numeric value for total yards gained on the given drive.}
#' \item{desc}{Detailed string description for the given play.}
#' \item{play_type}{String indicating the type of play: pass (includes sacks), run (includes scrambles), punt, field_goal, kickoff, extra_point, qb_kneel, qb_spike, no_play (timeouts and penalties), and missing for rows indicating end of play.}
#' \item{yards_gained}{Numeric yards gained (or lost) by the possessing team, excluding yards gained via fumble recoveries and laterals.}
#' \item{shotgun}{Binary indicator for whether or not the play was in shotgun formation.}
#' \item{no_huddle}{Binary indicator for whether or not the play was in no_huddle formation.}
#' \item{qb_dropback}{Binary indicator for whether or not the QB dropped back on the play (pass attempt, sack, or scrambled).}
#' \item{qb_kneel}{Binary indicator for whether or not the QB took a knee.}
#' \item{qb_spike}{Binary indicator for whether or not the QB spiked the ball.}
#' \item{qb_scramble}{Binary indicator for whether or not the QB scrambled.}
#' \item{pass_length}{String indicator for pass length: short or deep.}
#' \item{pass_location}{String indicator for pass location: left, middle, or right.}
#' \item{air_yards}{Numeric value for distance in yards perpendicular to the line of scrimmage at where the targeted receiver either caught or didn't catch the ball.}
#' \item{yards_after_catch}{Numeric value for distance in yards perpendicular to the yard line where the receiver made the reception to where the play ended.}
#' \item{run_location}{String indicator for location of run: left, middle, or right.}
#' \item{run_gap}{String indicator for line gap of run: end, guard, or tackle}
#' \item{field_goal_result}{String indicator for result of field goal attempt: made, missed, or blocked.}
#' \item{kick_distance}{Numeric distance in yards for kickoffs, field goals, and punts.}
#' \item{extra_point_result}{String indicator for the result of the extra point attempt: good, failed, blocked, safety (touchback in defensive endzone is 1 point apparently), or aborted.}
#' \item{two_point_conv_result}{String indicator for result of two point conversion attempt: success, failure, safety (touchback in defensive endzone is 1 point apparently), or return.}
#' \item{home_timeouts_remaining}{Numeric timeouts remaining in the half for the home team.}
#' \item{away_timeouts_remaining}{Numeric timeouts remaining in the half for the away team.}
#' \item{timeout}{Binary indicator for whether or not a timeout was called by either team.}
#' \item{timeout_team}{String abbreviation for which team called the timeout.}
#' \item{td_team}{String abbreviation for which team scored the touchdown.}
#' \item{td_player_name}{String name of the player who scored a touchdown.}
#' \item{td_player_id}{Unique identifier of the player who scored a touchdown.}
#' \item{posteam_timeouts_remaining}{Number of timeouts remaining for the possession team.}
#' \item{defteam_timeouts_remaining}{Number of timeouts remaining for the team on defense.}
#' \item{total_home_score}{Score for the home team at the end of the play.}
#' \item{total_away_score}{Score for the away team at the end of the play.}
#' \item{posteam_score}{Score the posteam at the start of the play.}
#' \item{defteam_score}{Score the defteam at the start of the play.}
#' \item{score_differential}{Score differential between the posteam and defteam at the start of the play.}
#' \item{posteam_score_post}{Score for the posteam at the end of the play.}
#' \item{defteam_score_post}{Score for the defteam at the end of the play.}
#' \item{score_differential_post}{Score differential between the posteam and defteam at the end of the play.}
#' \item{no_score_prob}{Predicted probability of no score occurring for the rest of the half based on the expected points model.}
#' \item{opp_fg_prob}{Predicted probability of the defteam scoring a FG next.}
#' \item{opp_safety_prob}{Predicted probability of the defteam scoring a safety next.}
#' \item{opp_td_prob}{Predicted probability of the defteam scoring a TD next.}
#' \item{fg_prob}{Predicted probability of the posteam scoring a FG next.}
#' \item{safety_prob}{Predicted probability of the posteam scoring a safety next.}
#' \item{td_prob}{Predicted probability of the posteam scoring a TD next.}
#' \item{extra_point_prob}{Predicted probability of the posteam scoring an extra point.}
#' \item{two_point_conversion_prob}{Predicted probability of the posteam scoring the two point conversion.}
#' \item{ep}{Using the scoring event probabilities, the estimated expected points with respect to the possession team for the given play.}
#' \item{epa}{Expected points added (EPA) by the posteam for the given play.}
#' \item{total_home_epa}{Cumulative total EPA for the home team in the game so far.}
#' \item{total_away_epa}{Cumulative total EPA for the away team in the game so far.}
#' \item{total_home_rush_epa}{Cumulative total rushing EPA for the home team in the game so far.}
#' \item{total_away_rush_epa}{Cumulative total rushing EPA for the away team in the game so far.}
#' \item{total_home_pass_epa}{Cumulative total passing EPA for the home team in the game so far.}
#' \item{total_away_pass_epa}{Cumulative total passing EPA for the away team in the game so far.}
#' \item{air_epa}{EPA from the air yards alone. For completions this represents the actual value provided through the air. For incompletions this represents the hypothetical value that could've been added through the air if the pass was completed.}
#' \item{yac_epa}{EPA from the yards after catch alone. For completions this represents the actual value provided after the catch. For incompletions this represents the difference between the hypothetical air_epa and the play's raw observed EPA (how much the incomplete pass cost the posteam).}
#' \item{comp_air_epa}{EPA from the air yards alone only for completions.}
#' \item{comp_yac_epa}{EPA from the yards after catch alone only for completions.}
#' \item{total_home_comp_air_epa}{Cumulative total completions air EPA for the home team in the game so far.}
#' \item{total_away_comp_air_epa}{Cumulative total completions air EPA for the away team in the game so far.}
#' \item{total_home_comp_yac_epa}{Cumulative total completions yac EPA for the home team in the game so far.}
#' \item{total_away_comp_yac_epa}{Cumulative total completions yac EPA for the away team in the game so far.}
#' \item{total_home_raw_air_epa}{Cumulative total raw air EPA for the home team in the game so far.}
#' \item{total_away_raw_air_epa}{Cumulative total raw air EPA for the away team in the game so far.}
#' \item{total_home_raw_yac_epa}{Cumulative total raw yac EPA for the home team in the game so far.}
#' \item{total_away_raw_yac_epa}{Cumulative total raw yac EPA for the away team in the game so far.}
#' \item{wp}{Estimated win probabiity for the posteam given the current situation at the start of the given play.}
#' \item{def_wp}{Estimated win probability for the defteam.}
#' \item{home_wp}{Estimated win probability for the home team.}
#' \item{away_wp}{Estimated win probability for the away team.}
#' \item{wpa}{Win probability added (WPA) for the posteam.}
#' \item{vegas_wpa}{Win probability added (WPA) for the posteam: spread_adjusted model.}
#' \item{vegas_home_wpa}{Win probability added (WPA) for the home team: spread_adjusted model.}
#' \item{home_wp_post}{Estimated win probability for the home team at the end of the play.}
#' \item{away_wp_post}{Estimated win probability for the away team at the end of the play.}
#' \item{vegas_wp}{Estimated win probabiity for the posteam given the current situation at the start of the given play, incorporating pre-game Vegas line.}
#' \item{vegas_home_wp}{Estimated win probability for the home team incorporating pre-game Vegas line.}
#' \item{total_home_rush_wpa}{Cumulative total rushing WPA for the home team in the game so far.}
#' \item{total_away_rush_wpa}{Cumulative total rushing WPA for the away team in the game so far.}
#' \item{total_home_pass_wpa}{Cumulative total passing WPA for the home team in the game so far.}
#' \item{total_away_pass_wpa}{Cumulative total passing WPA for the away team in the game so far.}
#' \item{air_wpa}{WPA through the air (same logic as air_epa).}
#' \item{yac_wpa}{WPA from yards after the catch (same logic as yac_epa).}
#' \item{comp_air_wpa}{The air_wpa for completions only.}
#' \item{comp_yac_wpa}{The yac_wpa for completions only.}
#' \item{total_home_comp_air_wpa}{Cumulative total completions air WPA for the home team in the game so far.}
#' \item{total_away_comp_air_wpa}{Cumulative total completions air WPA for the away team in the game so far.}
#' \item{total_home_comp_yac_wpa}{Cumulative total completions yac WPA for the home team in the game so far.}
#' \item{total_away_comp_yac_wpa}{Cumulative total completions yac WPA for the away team in the game so far.}
#' \item{total_home_raw_air_wpa}{Cumulative total raw air WPA for the home team in the game so far.}
#' \item{total_away_raw_air_wpa}{Cumulative total raw air WPA for the away team in the game so far.}
#' \item{total_home_raw_yac_wpa}{Cumulative total raw yac WPA for the home team in the game so far.}
#' \item{total_away_raw_yac_wpa}{Cumulative total raw yac WPA for the away team in the game so far.}
#' \item{punt_blocked}{Binary indicator for if the punt was blocked.}
#' \item{first_down_rush}{Binary indicator for if a running play converted the first down.}
#' \item{first_down_pass}{Binary indicator for if a passing play converted the first down.}
#' \item{first_down_penalty}{Binary indicator for if a penalty converted the first down.}
#' \item{third_down_converted}{Binary indicator for if the first down was converted on third down.}
#' \item{third_down_failed}{Binary indicator for if the posteam failed to convert first down on third down.}
#' \item{fourth_down_converted}{Binary indicator for if the first down was converted on fourth down.}
#' \item{fourth_down_failed}{Binary indicator for if the posteam failed to convert first down on fourth down.}
#' \item{incomplete_pass}{Binary indicator for if the pass was incomplete.}
#' \item{touchback}{Binary indicator for if a touchback occurred on the play.}
#' \item{interception}{Binary indicator for if the pass was intercepted.}
#' \item{punt_inside_twenty}{Binary indicator for if the punt ended inside the twenty yard line.}
#' \item{punt_in_endzone}{Binary indicator for if the punt was in the endzone.}
#' \item{punt_out_of_bounds}{Binary indicator for if the punt went out of bounds.}
#' \item{punt_downed}{Binary indicator for if the punt was downed.}
#' \item{punt_fair_catch}{Binary indicator for if the punt was caught with a fair catch.}
#' \item{kickoff_inside_twenty}{Binary indicator for if the kickoff ended inside the twenty yard line.}
#' \item{kickoff_in_endzone}{Binary indicator for if the kickoff was in the endzone.}
#' \item{kickoff_out_of_bounds}{Binary indicator for if the kickoff went out of bounds.}
#' \item{kickoff_downed}{Binary indicator for if the kickoff was downed.}
#' \item{kickoff_fair_catch}{Binary indicator for if the kickoff was caught with a fair catch.}
#' \item{fumble_forced}{Binary indicator for if the fumble was forced.}
#' \item{fumble_not_forced}{Binary indicator for if the fumble was not forced.}
#' \item{fumble_out_of_bounds}{Binary indicator for if the fumble went out of bounds.}
#' \item{solo_tackle}{Binary indicator if the play had a solo tackle (could be multiple due to fumbles).}
#' \item{safety}{Binary indicator for whether or not a safety occurred.}
#' \item{penalty}{Binary indicator for whether or not a penalty occurred.}
#' \item{tackled_for_loss}{Binary indicator for whether or not a tackle for loss on a run play occurred.}
#' \item{fumble_lost}{Binary indicator for if the fumble was lost.}
#' \item{own_kickoff_recovery}{Binary indicator for if the kicking team recovered the kickoff.}
#' \item{own_kickoff_recovery_td}{Binary indicator for if the kicking team recovered the kickoff and scored a TD.}
#' \item{qb_hit}{Binary indicator if the QB was hit on the play.}
#' \item{rush_attempt}{Binary indicator for if the play was a run.}
#' \item{pass_attempt}{Binary indicator for if the play was a pass attempt (includes sacks).}
#' \item{sack}{Binary indicator for if the play ended in a sack.}
#' \item{touchdown}{Binary indicator for if the play resulted in a TD.}
#' \item{pass_touchdown}{Binary indicator for if the play resulted in a passing TD.}
#' \item{rush_touchdown}{Binary indicator for if the play resulted in a rushing TD.}
#' \item{return_touchdown}{Binary indicator for if the play resulted in a return TD.}
#' \item{extra_point_attempt}{Binary indicator for extra point attempt.}
#' \item{two_point_attempt}{Binary indicator for two point conversion attempt.}
#' \item{field_goal_attempt}{Binary indicator for field goal attempt.}
#' \item{kickoff_attempt}{Binary indicator for kickoff.}
#' \item{punt_attempt}{Binary indicator for punts.}
#' \item{fumble}{Binary indicator for if a fumble occurred.}
#' \item{complete_pass}{Binary indicator for if the pass was completed.}
#' \item{assist_tackle}{Binary indicator for if an assist tackle occurred.}
#' \item{lateral_reception}{Binary indicator for if a lateral occurred on the reception.}
#' \item{lateral_rush}{Binary indicator for if a lateral occurred on a run.}
#' \item{lateral_return}{Binary indicator for if a lateral occurred on a return.}
#' \item{lateral_recovery}{Binary indicator for if a lateral occurred on a fumble recovery.}
#' \item{passer_player_id}{Unique identifier for the player that attempted the pass.}
#' \item{passer_player_name}{String name for the player that attempted the pass.}
#' \item{passing_yards}{Numeric yards by the passer_player_name, including yards gained in pass plays with laterals. This should equal official passing statistics.}
#' \item{receiver_player_id}{Unique identifier for the receiver that was targeted on the pass.}
#' \item{receiver_player_name}{String name for the targeted receiver.}
#' \item{receiving_yards}{Numeric yards by the receiver_player_name, excluding yards gained in pass plays with laterals. This should equal official receiving statistics but could miss yards gained in pass plays with laterals. Please see the description of `lateral_receiver_player_name` for further information.}
#' \item{rusher_player_id}{Unique identifier for the player that attempted the run.}
#' \item{rusher_player_name}{String name for the player that attempted the run.}
#' \item{rushing_yards}{Numeric yards by the rusher_player_name, excluding yards gained in rush plays with laterals. This should equal official rushing statistics but could miss yards gained in rush plays with laterals. Please see the description of `lateral_rusher_player_name` for further information.}
#' \item{lateral_receiver_player_id}{Unique identifier for the player that received the last(!) lateral on a pass play.}
#' \item{lateral_receiver_player_name}{String name for the player that received the last(!) lateral on a pass play. If there were multiple laterals in the same play, this will only be the last player who received a lateral. Please see }}\preformatted{future::plan("multisession")
load_pbp(2018:2020)
build_nflfastR_pbp(c("2018_21_NE_LA", "2019_21_SF_KC"))
}\if{html}{\out{
}}
We recommend choosing a default parallel processing method and saving it
as an environment variable in the R user profile to make sure all futures
will be resolved with the chosen method by default.
This can be done by following the below given steps.
First, run the following line and the file \code{.Renviron} should be opened automatically.
If you haven't saved any environment variables yet, this will be an empty file.
\if{html}{\out{}}\preformatted{usethis::edit_r_environ()
}\if{html}{\out{
}}
In the opened file \code{.Renviron} add the next line, then save the file and restart your R session.
Please note that this example sets "multisession" as default. For most users
this should be the appropriate plan but please make sure it truly is.
\if{html}{\out{}}\preformatted{R_FUTURE_PLAN="multisession"
}\if{html}{\out{
}}
After the session is freshly restarted please check if the above method worked
by running the next line. If the output is \code{FALSE} you successfully set up a
default non-sequential \code{\link[future:plan]{future::plan()}}. If the output is \code{TRUE} all functions
will behave like they were called with \code{\link[purrr:map]{purrr::map()}} and NOT in multisession.
\if{html}{\out{}}\preformatted{inherits(future::plan(), "sequential")
}\if{html}{\out{
}}
For more information on possible plans please see
\href{https://github.com/futureverse/future/blob/develop/README.md}{the future package Readme}.
For more information on \code{.Renviron} please see
\href{https://rstats.wtf/r-startup.html}{this book chapter}.
}
\subsection{Get Progress Updates while Functions are Running}{
Most nflfastR functions are able to show progress updates
using \code{\link[progressr:progressor]{progressr::progressor()}} if they are turned on before the function is
called. There are at least two basic ways to do this by either activating
progress updates globally (for the current session) with
\if{html}{\out{}}\preformatted{progressr::handlers(global = TRUE)
}\if{html}{\out{
}}
or by piping the function call into \code{\link[progressr:with_progress]{progressr::with_progress()}}:
\if{html}{\out{}}\preformatted{load_pbp(2018:2020) |>
progressr::with_progress()
}\if{html}{\out{
}}
Just like in the previous section, it is possible to activate global
progression handlers by default. This can be done by following the below given steps.
First, run the following line and the file \code{.Rprofile} should be opened automatically.
If you haven't saved any code yet, this will be an empty file.
\if{html}{\out{}}\preformatted{usethis::edit_r_profile()
}\if{html}{\out{
}}
In the opened file \code{.Rprofile} add the next line, then save the file and restart your R
session. All code in this file will be executed when a new R session starts.
The part \verb{if (require("progressr"))} makes sure this will only run if the
package progressr is installed to avoid crashing R sessions.
\if{html}{\out{}}\preformatted{if (requireNamespace("progressr", quietly = TRUE)) progressr::handlers(global = TRUE)
}\if{html}{\out{
}}
After the session is freshly restarted please check if the above method worked
by running the next line. If the output is \code{TRUE} you successfully activated
global progression handlers for all sessions.
\if{html}{\out{}}\preformatted{progressr::handlers(global = NA)
}\if{html}{\out{
}}
For more information how to work with progress handlers please see \link[progressr:progressr]{progressr::progressr}.
For more information on \code{.Rprofile} please see
\href{https://rstats.wtf/r-startup.html}{this book chapter}.
}
}
\seealso{
Useful links:
\itemize{
\item \url{https://nflfastr.com/}
\item \url{https://github.com/nflverse/nflfastR}
\item Report bugs at \url{https://github.com/nflverse/nflfastR/issues}
}
}
\author{
\strong{Maintainer}: Ben Baldwin \email{bbaldwin206@gmail.com}
Authors:
\itemize{
\item Sebastian Carl \email{mrcaseb@gmail.com}
}
Other contributors:
\itemize{
\item Lee Sharpe [contributor]
\item Maksim Horowitz \email{maksim.horowitz@gmail.com} [contributor]
\item Ron Yurko \email{ryurko@stat.cmu.edu} [contributor]
\item Samuel Ventura \email{samventura22@gmail.com} [contributor]
\item Tan Ho [contributor]
\item John Edwards \email{edwards1860@gmail.com} [contributor]
}
}
================================================
FILE: man/reexports.Rd
================================================
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/nflfastR-package.R
\docType{import}
\name{reexports}
\alias{reexports}
\alias{load_pbp}
\alias{load_player_stats}
\alias{load_team_stats}
\alias{load_schedules}
\alias{load_rosters}
\alias{nflverse_sitrep}
\alias{most_recent_season}
\title{Objects exported from other packages}
\keyword{internal}
\description{
These objects are imported from other packages. Follow the links
below to see their documentation.
\describe{
\item{nflreadr}{\code{\link[nflreadr]{load_pbp}}, \code{\link[nflreadr]{load_player_stats}}, \code{\link[nflreadr]{load_rosters}}, \code{\link[nflreadr]{load_schedules}}, \code{\link[nflreadr]{load_team_stats}}, \code{\link[nflreadr:latest_season]{most_recent_season}}, \code{\link[nflreadr:sitrep]{nflverse_sitrep}}}
}}
================================================
FILE: man/report.Rd
================================================
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/report.R
\name{report}
\alias{report}
\title{Get a Situation Report on System, nflverse Package Versions and Dependencies}
\usage{
report(...)
}
\arguments{
\item{...}{
Arguments passed on to \code{\link[nflreadr:sitrep]{nflreadr::nflverse_sitrep}}
\describe{
\item{\code{pkg}}{a character vector naming installed packages, or \code{NULL}
(the default) meaning all nflverse packages. The function checks internally
if all packages are installed and informs if that is not the case.}
\item{\code{recursive}}{a logical indicating whether dependencies of \code{pkg} and their
dependencies (and so on) should be included.
Can also be a character vector listing the types of dependencies, a subset
of \code{c("Depends", "Imports", "LinkingTo", "Suggests", "Enhances")}.
Character string \code{"all"} is shorthand for that vector, character string
\code{"most"} for the same vector without \code{"Enhances"}, character string \code{"strong"}
(default) for the first three elements of that vector.}
\item{\code{redact_path}}{a logical indicating whether options that contain "path"
in the name should be redacted, default = TRUE}
}}
}
\description{
\ifelse{html}{\href{https://lifecycle.r-lib.org/articles/stages.html#deprecated}{\figure{lifecycle-deprecated.svg}{options: alt='[Deprecated]'}}}{\strong{[Deprecated]}}
This function was deprecated. Please use \code{\link[nflreadr:sitrep]{nflreadr::nflverse_sitrep}}.
This function gives a quick overview of the versions of R and
the operating system as well as the versions of nflverse packages, options,
and their dependencies. It's primarily designed to help you get a quick
idea of what's going on when you're helping someone else debug a problem.
}
\details{
See \code{\link[nflreadr:sitrep]{nflreadr::nflverse_sitrep}} for details.
}
\examples{
\donttest{
\dontshow{
# set CRAN mirror to avoid failing checks in weird scenarios
old_ops <- options(repos = c("CRAN" = "https://cran.rstudio.com/"))
}
# report(recursive = FALSE)
nflverse_sitrep(pkg = "nflreadr", recursive = TRUE)
\dontshow{
# restore old options
options(old_ops)
}
}
}
\keyword{internal}
================================================
FILE: man/save_raw_pbp.Rd
================================================
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/save_raw_pbp.R
\name{save_raw_pbp}
\alias{save_raw_pbp}
\title{Download Raw PBP Data to Local Filesystem}
\usage{
save_raw_pbp(
game_ids,
dir = getOption("nflfastR.raw_directory", default = NULL)
)
}
\arguments{
\item{game_ids}{A vector of nflverse game IDs.}
\item{dir}{Path to local directory (defaults to option "nflfastR.raw_directory").
nflfastR will download the raw game files split by season into one sub
directory per season.}
}
\value{
The function returns a data frame with one row for each downloaded file and
the following columns:
\itemize{
\item \code{success} if the HTTP request was successfully performed, regardless of the
response status code. This is \code{FALSE} in case of a network error, or in case
you tried to resume from a server that did not support this. A value of \code{NA}
means the download was interrupted while in progress.
\item \code{status_code} the HTTP status code from the request. A successful download is
usually \code{200} for full requests or \code{206} for resumed requests. Anything else
could indicate that the downloaded file contains an error page instead of the
requested content.
\item \code{resumefrom} the file size before the request, in case a download was resumed.
\item \code{url} final url (after redirects) of the request.
\item \code{destfile} downloaded file on disk.
\item \code{error} if \code{success == FALSE} this column contains an error message.
\item \code{type} the \code{Content-Type} response header value.
\item \code{modified} the \code{Last-Modified} response header value.
\item \code{time} total elapsed download time for this file in seconds.
\item \code{headers} vector with http response headers for the request.
}
}
\description{
The functions \code{\link[=build_nflfastR_pbp]{build_nflfastR_pbp()}} and \code{\link[=fast_scraper]{fast_scraper()}} support loading
raw pbp data from local file systems instead of Github servers.
This function is intended to help setting this up. It loads raw pbp data
and saves it in the given directory split by season in subdirectories.
}
\examples{
\donttest{
# CREATE LOCAL TEMP DIRECTORY
local_dir <- tempdir()
# LOAD AND SAVE A GAME TO TEMP DIRECTORY
save_raw_pbp("2021_20_BUF_KC", dir = local_dir)
# REMOVE THE DIRECTORY
unlink(file.path(local_dir, 2021))
}
}
\seealso{
\code{\link[=build_nflfastR_pbp]{build_nflfastR_pbp()}}, \code{\link[=missing_raw_pbp]{missing_raw_pbp()}}
}
================================================
FILE: man/stat_ids.Rd
================================================
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/data_documentation.R
\docType{data}
\name{stat_ids}
\alias{stat_ids}
\title{NFL Stat IDs and their Meanings}
\format{
A data frame including NFL stat IDs, names and descriptions used in
an nflfastR dataset.
}
\source{
\url{http://www.nflgsis.com/gsis/Documentation/Partners/StatIDs.html}
}
\usage{
stat_ids
}
\description{
NFL Stat IDs and their Meanings
}
\examples{
\donttest{
stat_ids
}
}
\keyword{datasets}
================================================
FILE: man/teams_colors_logos.Rd
================================================
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/data_documentation.R
\docType{data}
\name{teams_colors_logos}
\alias{teams_colors_logos}
\title{NFL Team names, colors and logo urls.}
\format{
A data frame with 36 rows and 10 variables containing NFL team level
information, including franchises in multiple cities:
\describe{
\item{team_abbr}{Team abbreviation}
\item{team_name}{Complete Team name}
\item{team_id}{Team id used in the roster function}
\item{team_nick}{Nickname}
\item{team_conf}{Conference}
\item{team_division}{Division}
\item{team_color}{Primary color}
\item{team_color2}{Secondary color}
\item{team_color3}{Tertiary color}
\item{team_color4}{Quaternary color}
\item{team_logo_wikipedia}{Url to Team logo on wikipedia}
\item{team_logo_espn}{Url to higher quality logo on espn}
\item{team_wordmark}{Url to team wordmarks}
\item{team_conference_logo}{Url to AFC and NFC logos}
\item{team_league_logo}{Url to NFL logo}
}
The primary and secondary colors have been taken from nfl.com with some modifications
for better team distinction and most recent team color themes.
The tertiary and quaternary colors are taken from Lee Sharpe's teamcolors.csv
who has taken them from the \code{teamcolors} package created by Ben Baumer and
Gregory Matthews. The Wikipeadia logo urls are taken from Lee Sharpe's logos.csv
Team wordmarks from nfl.com
}
\usage{
teams_colors_logos
}
\description{
NFL Team names, colors and logo urls.
}
\examples{
\donttest{
teams_colors_logos
}
}
\keyword{datasets}
================================================
FILE: man/update_db.Rd
================================================
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/helper_database_functions.R
\name{update_db}
\alias{update_db}
\title{Update or Create a nflfastR Play-by-Play Database}
\usage{
update_db(
dbdir = getOption("nflfastR.dbdirectory", default = "."),
dbname = "pbp_db",
tblname = "nflfastR_pbp",
force_rebuild = FALSE,
db_connection = NULL
)
}
\arguments{
\item{dbdir}{Directory in which the database is or shall be located. Can also
be set globally with \code{options(nflfastR.dbdirectory)}}
\item{dbname}{File name of an existing or desired SQLite database within \code{dbdir}}
\item{tblname}{The name of the play by play data table within the database}
\item{force_rebuild}{Hybrid parameter (logical or numeric) to rebuild parts
of or the complete play by play data table within the database (please see details for further information)}
\item{db_connection}{A \code{DBIConnection} object, as returned by
\code{\link[DBI:dbConnect]{DBI::dbConnect()}} (please see details for further information)}
}
\description{
\code{update_db} updates or creates a database with \code{nflfastR}
play by play data of all completed games since 1999.
}
\details{
This function creates and updates a data table with the name \code{tblname}
within a SQLite database (other drivers via \code{db_connection}) located in
\code{dbdir} and named \code{dbname}.
The data table combines all play by play data for every available game back
to the 1999 season and adds the most recent completed games as soon as they
are available for \code{nflfastR}.
The argument \code{force_rebuild} is of hybrid type. It can rebuild the play
by play data table either for the whole nflfastR era (with \code{force_rebuild = TRUE})
or just for specified seasons (e.g. \code{force_rebuild = c(2019, 2020)}).
Please note the following behavior:
\itemize{
\item \code{force_rebuild = TRUE}: The data table with the name \code{tblname}
will be removed completely and rebuilt from scratch. This is helpful when
new columns are added during the Off-Season.
\item \code{force_rebuild = c(2019, 2020)}: The data table with the name \code{tblname}
will be preserved and only rows from the 2019 and 2020 seasons will be
deleted and re-added. This is intended to be used for ongoing seasons because
the NFL fixes bugs in the underlying data during the week and we recommend
rebuilding the current season every Thursday during the season.
}
The parameter \code{db_connection} is intended for advanced users who want
to use other DBI drivers, such as MariaDB, Postgres or odbc. Please note that
the arguments \code{dbdir} and \code{dbname} are dropped in case a \code{db_connection}
is provided but the argument \code{tblname} will still be used to write the
data table into the database.
}
================================================
FILE: man/update_pbp_db.Rd
================================================
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/database.R
\name{update_pbp_db}
\alias{update_pbp_db}
\title{Update or Create a nflverse Play-by-Play Data Table in a Connected Database}
\usage{
update_pbp_db(conn, ..., name = "nflverse_pbp", seasons = most_recent_season())
}
\arguments{
\item{conn}{A \code{DBIConnection} object, as returned by \code{\link[DBI:dbConnect]{DBI::dbConnect()}}}
\item{...}{These dots are for future extensions and must be empty.}
\item{name}{The table name, passed on to \code{\link[DBI:dbQuoteIdentifier]{dbQuoteIdentifier()}}. Options are:
\itemize{
\item a character string with the unquoted DBMS table name,
e.g. \code{"table_name"},
\item a call to \code{\link[DBI:Id]{Id()}} with components to the fully qualified table name,
e.g. \code{Id(schema = "my_schema", table = "table_name")}
\item a call to \code{\link[DBI:SQL]{SQL()}} with the quoted and fully qualified table name
given verbatim, e.g. \code{SQL('"my_schema"."table_name"')}
}}
\item{seasons}{Hybrid argument (logical or numeric) to update parts
of or the complete play by play table within the database.
It can update the play by play data table either for the whole nflfastR era
(with \code{seasons = TRUE}) or just for specified seasons
(e.g. \code{seasons = 2024:2025}).
Defaults to \link{most_recent_season}. Please see details for further information.}
}
\value{
Always returns the database connection invisibly.
}
\description{
The nflfastR play-by-play era dates back to 1999. To analyze all the data
efficiently, there is practically no alternative to working with a database.
This function helps to create and maintain a table containing all
play-by-play data of the nflfastR era in a connected database.
Primarily, the preprocessed data from \link{load_pbp} is written to the database
and, if necessary, supplemented with the latest games using
\link{build_nflfastR_pbp}.
}
\details{
\subsection{The \code{seasons} argument}{
The \code{seasons} argument controls how the table in the connected database is
handled.
With \code{seasons = TRUE}, the table in argument \code{name} will be removed completely
(by calling \link[DBI:dbRemoveTable]{DBI::dbRemoveTable}) and all seasons of the nflfastR era will be
added to a fresh table. This is helpful when new columns are added during the
offseason.
With a numerical vector, e.g. \code{seasons = 2024:2025}, the table in argument
\code{name} will be preserved and only rows from the given seasons will be deleted
and re-added (by calling \link[DBI:dbAppendTable]{DBI::dbAppendTable}). This is intended to be used
for ongoing seasons because the NFL fixes bugs in the underlying data during
the week and we recommend rebuilding the current season every Thursday during
the season.
The default behavior is \code{seasons = most_recent_season()}, which means that
only the most recent season is updated or added.
To keep the table, and thus also the schema, but update all play-by-play
data of the nflfastR era, set
\if{html}{\out{}}\preformatted{seasons = seq(1999, most_recent_season())
}\if{html}{\out{
}}
If \code{seasons} contains multiple seasons, it is possible to control whether the
seasons are loaded individually and written to the database, or whether
multiple seasons should be processed in chunks. The latter is more efficient
because fewer write operations are required, but at the same time, the data
must first be stored in memory. The option \verb{“nflfastR.db_chunk_size”} can
be used to control how many seasons are loaded together in a chunk and
written to the database. With the following option, for example, 5 seasons
are always loaded together and written to the database.
\if{html}{\out{}}\preformatted{options("nflfastR.db_chunk_size" = 5L)
}\if{html}{\out{
}}
}
}
\examples{
\donttest{
con <- DBI::dbConnect(duckdb::duckdb())
try({# to avoid CRAN test problems
update_pbp_db(con, seasons = 2024)
})
}
}
================================================
FILE: nflfastR.Rproj
================================================
Version: 1.0
ProjectId: e1e14382-386c-49b3-9b3f-206a4cc98503
RestoreWorkspace: Default
SaveWorkspace: Default
AlwaysSaveHistory: Default
EnableCodeIndexing: Yes
UseSpacesForTab: Yes
NumSpacesForTab: 2
Encoding: UTF-8
RnwWeave: Sweave
LaTeX: pdfLaTeX
AutoAppendNewline: Yes
StripTrailingWhitespace: Yes
BuildType: Package
PackageUseDevtools: Yes
PackageInstallArgs: --no-multiarch --with-keep.source
PackageRoxygenize: rd,collate,namespace
UseNativePipeOperator: Yes
================================================
FILE: pkgdown/_pkgdown.yml
================================================
url: https://nflfastr.com/
template:
bootstrap: 5
light-switch: true
bslib:
font_scale: 1.1
base_font: {google: "Roboto"}
heading_font: {google: "Kanit"}
code_font: {google: "Fira Code"}
opengraph:
image:
src: man/figures/card.png
alt: "nflfastR social preview card"
twitter:
site: "@nflfastR"
card: summary_large_image
toc:
depth: 3
authors:
Sebastian Carl:
href: https://mrcaseb.com
Ben Baldwin:
href: https://bsky.app/profile/rbsdm.com
Lee Sharpe:
href: https://twitter.com/LeeSharpeNFL
Maksim Horowitz:
href: https://twitter.com/bklynmaks
Ron Yurko:
href: https://twitter.com/Stat_Ron
Samuel Ventura:
href: https://twitter.com/stat_sam
Tan Ho:
href: https://tanho.ca
John Edwards:
href: https://johnbedwards.io
home:
title: An R package to quickly obtain clean and tidy NFL play by play data
links:
- text: nflverse Discord Chat
href: https://discord.gg/5Er2FBnnQa
- text: nflfastR Beginner's Guide
href: articles/beginners_guide.html
- text: nflfastR stats landing page
href: https://rbsdm.com/stats/
- text: Lee Sharpe's nfl game data
href: https://nflgamedata.com
navbar:
bg: dark
type: light
structure:
left: [home, intro, reference, news, articles]
right: [search, lightswitch, stats, games, discord, github, more]
components:
games:
icon: "fas fa-football-ball fa-lg"
href: http://nflgamedata.com/
aria-label: Games
stats:
icon: "fas fa-chart-line fa-lg"
href: https://rbsdm.com/stats/
aria-label: Stats
reference:
text: "Functions"
href: reference/index.html
discord:
icon: "fab fa-discord fa-lg"
href: https://discord.com/invite/5Er2FBnnQa
aria-label: Discord
articles:
text: "Articles"
menu:
- text: A beginner’s guide to nflfastR
href: articles/beginners_guide.html
- text: Field Descriptions
href: articles/field_descriptions.html
- text: Stats Variable Descriptions
href: articles/stats_variables.html
- text: nflfastR models
href: https://www.opensourcefootball.com/posts/2020-09-28-nflfastr-ep-wp-and-cp-models/
- text: Open Source Football
href: https://www.opensourcefootball.com/
more:
text: "Packages & More"
menu:
- text: "nflverse Packages"
- text: nflfastR
href: https://nflfastr.com
- text: nflseedR
href: https://nflseedr.com
- text: nfl4th
href: https://www.nfl4th.com
- text: nflreadr
href: https://nflreadr.nflverse.com/
- text: nflplotR
href: https://nflplotr.nflverse.com/
- text: nflverse
href: https://nflverse.nflverse.com/
- text: "Open Source Football"
href: https://www.opensourcefootball.com
- text: "nflverse Data"
- text: nflverse GitHub
href: https://github.com/nflverse
- text: ffverse
- text: "ffverse.com"
href: https://www.ffverse.com
reference:
- title: Main Functions
contents:
- build_nflfastR_pbp
- update_db
- update_pbp_db
- title: Load Functions
desc: >
These functions access precomputed data using the nflreadr package.
See