Package 'nflreadr'

Title: Download 'nflverse' Data
Description: A minimal package for downloading data from 'GitHub' repositories of the 'nflverse' project.
Authors: Tan Ho [aut, cre, cph] , Sebastian Carl [aut], John Edwards [ctb], Ben Baldwin [ctb], Thomas Mock [ctb], Lee Sharpe [ctb], Pranav Rajaram [ctb]
Maintainer: Tan Ho <[email protected]>
License: MIT + file LICENSE
Version: 1.4.1.05
Built: 2024-11-12 16:20:33 UTC
Source: https://github.com/nflverse/nflreadr

Help Index

Clean Home/Away in dataframes into Team/Opponent dataframes

Description

This function converts dataframes with "home_" and "away_" prefixed columns to "team_" and "opponent_", and doubles the rows. This makes sure that there's one row for each team (as opposed to one row for each game).

Usage

clean_homeaway(dataframe, invert = NULL)

Arguments

dataframe

dataframe
invert

a character vector of columns that gets inverted when referring to the away team (e.g. home spread = 1 gets converted to away_spread = -1)

Value

a dataframe with one row per team (twice as long as the input dataframe)

Examples

# a small example dataframe
s <- data.frame(
   game_id = c("2020_20_TB_GB", "2020_20_BUF_KC", "2020_21_KC_TB"),
   game_type = c("CON", "CON", "SB"),
   away_team = c("TB", "BUF", "KC"),
   away_score = c(31L, 24L, 9L),
   home_team = c("GB", "KC", "TB"),
   home_score = c(26L, 38L, 31L),
   location = c("Home", "Home", "Neutral"),
   result = c(-5L, 14L, 22L),
   spread_line = c(3, 3, -3)
 )

clean_homeaway(s, invert = c("result","spread_line"))

Create Player Merge Names

Description

Applies some name-cleaning heuristics to facilitate joins. These heuristics may include:

  • removing periods and apostrophes

  • removing common suffixes, such as Jr, Sr, II, III, IV

  • converting to lowercase

  • using ffscrapr::dp_name_mapping to do common name substitutions, such as Mitch Trubisky to Mitchell Trubisky

Usage

clean_player_names(
  player_name,
  lowercase = FALSE,
  convert_lastfirst = TRUE,
  use_name_database = TRUE,
  convert_to_ascii = rlang::is_installed("stringi")
)

Arguments

player_name

a character vector of player names
lowercase

defaults to FALSE - if TRUE, converts to lowercase
convert_lastfirst

defaults to TRUE - converts names from "Last, First" to "First Last"
use_name_database

uses internal name database to do common substitutions (Mitchell Trubisky to Mitch Trubisky etc)
convert_to_ascii

If TRUE, will transliterate to latin-ascii via the stringi package. Defaults to TRUE if the stringi package is installed.

Details

Equivalent to the operation done by ffscrapr::dp_clean_names() and uses the same player name database.

Value

a character vector of cleaned names

Examples

clean_player_names(c("A.J. Green", "Odell Beckham Jr.  ", "Le'Veon Bell Sr."))

clean_player_names(c("Trubisky,      Mitch", "Atwell, Chatarius", "Elliott, Zeke", "Elijah Moore"),
                  convert_lastfirst = TRUE)

Standardize NFL Team Abbreviations

Description

This function standardizes NFL team abbreviations to nflverse defaults. This helps for joins and plotting, especially with the new nflplotR package!

Usage

clean_team_abbrs(abbr, current_location = TRUE, keep_non_matches = TRUE)

Arguments

abbr

a character vector of abbreviations
current_location

If TRUE (the default), the abbreviation of the most recent team location will be used.
keep_non_matches

If TRUE (the default) an element of abbr that can't be matched to any of the internal mapping vectors will be kept as is. Otherwise it will be replaced with NA.

Value

A character vector with the length of abbr and cleaned team abbreviations if they are included in team_abbr_mapping or team_abbr_mapping_norelocate (depending on the value of current_location). Non matches may be replaced with NA (depending on the value of keep_non_matches).

Examples

x <- c("PIE", "LAR", "PIT", "CRD", "OAK", "SL")
# use current location and keep non matches
clean_team_abbrs(x)

# keep old location and replace non matches
clean_team_abbrs(x, current_location = FALSE, keep_non_matches = FALSE)

Clear function cache

Description

This function clears the memoised cache of all functions memoised by nflreadr.

Usage

clear_cache()

.clear_cache()

Value

A success message after clearing the cache.

Examples

clear_cache()

Load .csv / .csv.gz file from a remote connection

Description

This is a thin wrapper on data.table::fread, but memoised & cached for twenty four hours.

Usage

csv_from_url(...)

Arguments

...

Arguments passed on to data.table::fread

input

A single character string. The value is inspected and deferred to either file= (if no \n present), text= (if at least one \n is present) or cmd= (if no \n is present, at least one space is present, and it isn't a file name). Exactly one of input=, file=, text=, or cmd= should be used in the same call.

file

File name in working directory, path to file (passed through path.expand for convenience), or a URL starting http://, file://, etc. Compressed files with extension ‘.gz’ and ‘.bz2’ are supported if the R.utils package is installed.

text

The input data itself as a character vector of one or more lines, for example as returned by readLines().

cmd

A shell command that pre-processes the file; e.g. fread(cmd=paste("grep",word,"filename")). See Details.

sep

The separator between columns. Defaults to the character in the set [,\t |;:] that separates the sample of rows into the most number of lines with the same number of fields. Use NULL or "" to specify no separator; i.e. each line a single character column like base::readLines does.

sep2

The separator within columns. A list column will be returned where each cell is a vector of values. This is much faster using less working memory than strsplit afterwards or similar techniques. For each column sep2 can be different and is the first character in the same set above [,\t |;], other than sep, that exists inside each field outside quoted regions in the sample. NB: sep2 is not yet implemented.

nrows

The maximum number of rows to read. Unlike read.table, you do not need to set this to an estimate of the number of rows in the file for better speed because that is already automatically determined by fread almost instantly using the large sample of lines. nrows=0 returns the column names and typed empty columns determined by the large sample; useful for a dry run of a large file or to quickly check format consistency of a set of files before starting to read any of them.

header

Does the first data line contain column names? Defaults according to whether every non-empty field on the first data line is type character. If so, or TRUE is supplied, any empty column names are given a default name.

na.strings

A character vector of strings which are to be interpreted as NA values. By default, ",," for columns of all types, including type character is read as NA for consistency. ,"", is unambiguous and read as an empty string. To read ,NA, as NA, set na.strings="NA". To read ,, as blank string "", set na.strings=NULL. When they occur in the file, the strings in na.strings should not appear quoted since that is how the string literal ,"NA", is distinguished from ,NA,, for example, when na.strings="NA".

stringsAsFactors

Convert all or some character columns to factors? Acceptable inputs are TRUE, FALSE, or a decimal value between 0.0 and 1.0. For stringsAsFactors = FALSE, all string columns are stored as character vs. all stored as factor when TRUE. When stringsAsFactors = p for 0 <= p <= 1, string columns col are stored as factor if uniqueN(col)/nrow < p.

verbose

Be chatty and report timings?

skip

If 0 (default) start on the first line and from there finds the first row with a consistent number of columns. This automatically avoids irregular header information before the column names row. skip>0 means ignore the first skip rows manually. skip="string" searches for "string" in the file (e.g. a substring of the column names row) and starts on that line (inspired by read.xls in package gdata).

select

A vector of column names or numbers to keep, drop the rest. select may specify types too in the same way as colClasses; i.e., a vector of colname=type pairs, or a list of type=col(s) pairs. In all forms of select, the order that the columns are specified determines the order of the columns in the result.

drop

Vector of column names or numbers to drop, keep the rest.

colClasses

As in utils::read.csv; i.e., an unnamed vector of types corresponding to the columns in the file, or a named vector specifying types for a subset of the columns by name. The default, NULL means types are inferred from the data in the file. Further, data.table supports a named list of vectors of column names or numbers where the list names are the class names; see examples. The list form makes it easier to set a batch of columns to be a particular class. When column numbers are used in the list form, they refer to the column number in the file not the column number after select or drop has been applied. If type coercion results in an error, introduces NAs, or would result in loss of accuracy, the coercion attempt is aborted for that column with warning and the column's type is left unchanged. If you really desire data loss (e.g. reading 3.14 as integer) you have to truncate such columns afterwards yourself explicitly so that this is clear to future readers of your code.

integer64

"integer64" (default) reads columns detected as containing integers larger than 2^31 as type bit64::integer64. Alternatively, "double"|"numeric" reads as utils::read.csv does; i.e., possibly with loss of precision and if so silently. Or, "character".

dec

The decimal separator as in utils::read.csv. When "auto" (the default), an attempt is made to decide whether "." or "," is more suitable for this input. See details.

col.names

A vector of optional names for the variables (columns). The default is to use the header column if present or detected, or if not "V" followed by the column number. This is applied after check.names and before key and index.

check.names

default is FALSE. If TRUE then the names of the variables in the data.table are checked to ensure that they are syntactically valid variable names. If necessary they are adjusted (by make.names) so that they are, and also to ensure that there are no duplicates.

encoding

default is "unknown". Other possible options are "UTF-8" and "Latin-1". Note: it is not used to re-encode the input, rather enables handling of encoded strings in their native encoding.

quote

By default ("\""), if a field starts with a double quote, fread handles embedded quotes robustly as explained under Details. If it fails, then another attempt is made to read the field as is, i.e., as if quotes are disabled. By setting quote="", the field is always read as if quotes are disabled. It is not expected to ever need to pass anything other than \"\" to quote; i.e., to turn it off.

strip.white

Logical, default TRUE, in which case leading and trailing whitespace is stripped from unquoted "character" fields. "numeric" fields are always stripped of leading and trailing whitespace.

fill

logical or integer (default is FALSE). If TRUE then in case the rows have unequal length, number of columns is estimated and blank fields are implicitly filled. If an integer is provided it is used as an upper bound for the number of columns. If fill=Inf then the whole file is read for detecting the number of columns.

blank.lines.skip

logical, default is FALSE. If TRUE blank lines in the input are ignored.

key

Character vector of one or more column names which is passed to setkey. Only valid when argument data.table=TRUE. Where applicable, this should refer to column names given in col.names.

index

Character vector or list of character vectors of one or more column names which is passed to setindexv. As with key, comma-separated notation like index="x,y,z" is accepted for convenience. Only valid when argument data.table=TRUE. Where applicable, this should refer to column names given in col.names.

showProgress

TRUE displays progress on the console if the ETA is greater than 3 seconds. It is produced in fread's C code where the very nice (but R level) txtProgressBar and tkProgressBar are not easily available.

data.table

TRUE returns a data.table. FALSE returns a data.frame. The default for this argument can be changed with options(datatable.fread.datatable=FALSE).

nThread

The number of threads to use. Experiment to see what works best for your data on your hardware.

logical01

If TRUE a column containing only 0s and 1s will be read as logical, otherwise as integer.

keepLeadingZeros

If TRUE a column containing numeric data with leading zeros will be read as character, otherwise leading zeros will be removed and converted to numeric.

yaml

If TRUE, fread will attempt to parse (using yaml.load) the top of the input as YAML, and further to glean parameters relevant to improving the performance of fread on the data itself. The entire YAML section is returned as parsed into a list in the yaml_metadata attribute. See Details.

autostart

Deprecated and ignored with warning. Please use skip instead.

tmpdir

Directory to use as the tmpdir argument for any tempfile calls, e.g. when the input is a URL or a shell command. The default is tempdir() which can be controlled by setting TMPDIR before starting the R session; see base::tempdir.

tz

Relevant to datetime values which have no Z or UTC-offset at the end, i.e. unmarked datetime, as written by utils::write.csv. The default tz="UTC" reads unmarked datetime as UTC POSIXct efficiently. tz="" reads unmarked datetime as type character (slowly) so that as.POSIXct can interpret (slowly) the character datetimes in local timezone; e.g. by using "POSIXct" in colClasses=. Note that fwrite() by default writes datetime in UTC including the final Z and therefore fwrite's output will be read by fread consistently and quickly without needing to use tz= or colClasses=. If the TZ environment variable is set to "UTC" (or "" on non-Windows where unset vs ‘""' is significant) then the R session’s timezone is already UTC and tz="" will result in unmarked datetimes being read as UTC POSIXct. For more information, please see the news items from v1.13.0 and v1.14.0.

Value

a dataframe as created by data.table::fread()

Examples

try({ # prevents cran errors
  csv_from_url("https://github.com/nflverse/nflverse-data/releases/download/test/combines.csv")
})

Data Dictionary: Combine

Description

A dataframe containing the data dictionary for load_combine()

Usage

dictionary_combine

Format

An object of class data.frame with 18 rows and 3 columns.

See Also

vignette("Data Dictionary - Combine")

https://nflreadr.nflverse.com/articles/dictionary_combine.html

Data Dictionary: Contracts

Description

A dataframe containing the data dictionary for load_contracts()

Usage

dictionary_contracts

Format

An object of class data.frame with 15 rows and 3 columns.

See Also

vignette("Data Dictionary - Contracts")

https://nflreadr.nflverse.com/articles/dictionary_contracts.html

Data Dictionary: Depth Charts

Description

A dataframe containing the data dictionary for load_depth_charts()

Usage

dictionary_depth_charts

Format

An object of class data.frame with 13 rows and 3 columns.

See Also

vignette("Data Dictionary - Depth Charts")

https://nflreadr.nflverse.com/articles/dictionary_depth_charts.html

Data Dictionary: Draft Picks

Description

A dataframe containing the data dictionary for load_draft_picks()

Usage

dictionary_draft_picks

Format

An object of class data.frame with 36 rows and 3 columns.

See Also

vignette("Data Dictionary - Draft Picks")

https://nflreadr.nflverse.com/articles/dictionary_draft_picks.html

Data Dictionary: ESPN QBR

Description

A dataframe containing the data dictionary for load_espn_qbr()

Usage

dictionary_espn_qbr

Format

An object of class data.frame with 23 rows and 3 columns.

See Also

vignette("Data Dictionary - ESPN QBR")

https://nflreadr.nflverse.com/articles/dictionary_espn_qbr.html

Data Dictionary: Expected Fantasy Points

Description

A dataframe containing the data dictionary for load_ff_opportunity()

Usage

dictionary_ff_opportunity

Format

An object of class data.frame with 218 rows and 4 columns.

See Also

vignette("Data Dictionary - Expected Fantasy Points")

https://nflreadr.nflverse.com/articles/dictionary_ff_opportunity.html

Data Dictionary: Fantasy Player IDs

Description

A dataframe containing the data dictionary for load_ff_playerids()

Usage

dictionary_ff_playerids

Format

An object of class data.frame with 35 rows and 3 columns.

See Also

vignette("Data Dictionary - FF Player IDs")

https://nflreadr.nflverse.com/articles/dictionary_ff_playerids.html

Data Dictionary: Fantasy Football Rankings

Description

A dataframe containing the data dictionary for load_ff_rankings()

Usage

dictionary_ff_rankings

Format

An object of class data.frame with 25 rows and 3 columns.

See Also

vignette("Data Dictionary - FF Rankings")

https://nflreadr.nflverse.com/articles/dictionary_ff_rankings.html

Data Dictionary: FTN Charting Data

Description

A dataframe containing the data dictionary for load_ftn_charting()

Usage

dictionary_ftn_charting

Format

An object of class data.frame with 28 rows and 5 columns.

See Also

vignette("Data Dictionary - FTN Charting")

https://nflreadr.nflverse.com/articles/dictionary_ftn_charting.html

Other ftn_charting: load_ftn_charting()

Data Dictionary: Injuries

Description

A dataframe containing the data dictionary for load_injuries()

Usage

dictionary_injuries

Format

An object of class data.frame with 16 rows and 3 columns.

See Also

vignette("Data Dictionary - Injuries")

https://nflreadr.nflverse.com/articles/dictionary_injuries.html

Data Dictionary: Next Gen Stats

Description

A dataframe containing the data dictionary for load_nextgen_stats()

Usage

dictionary_nextgen_stats

Format

An object of class data.frame with 51 rows and 3 columns.

See Also

vignette("Data Dictionary - Next Gen Stats")

https://nflreadr.nflverse.com/articles/dictionary_nextgen_stats.html

Data Dictionary: Participation

Description

A dataframe containing the data dictionary for load_participation()

Usage

dictionary_participation

Format

An object of class data.frame with 19 rows and 3 columns.

See Also

vignette("Data Dictionary - Participation")

https://nflreadr.nflverse.com/articles/dictionary_participation.html

Data Dictionary: Play by Play

Description

A dataframe containing the data dictionary for load_pbp()

Usage

dictionary_pbp

Format

An object of class data.frame with 372 rows and 3 columns.

See Also

vignette("Data Dictionary - PBP")

https://nflreadr.nflverse.com/articles/dictionary_pbp.html

Data Dictionary: PFR Passing

Description

A dataframe containing the data dictionary for load_pfr_passing()

Usage

dictionary_pfr_passing

Format

An object of class data.frame with 28 rows and 3 columns.

See Also

https://nflreadr.nflverse.com/articles/dictionary_pfr_passing.html

vignette("Data Dictionary - PFR Passing")

Data Dictionary: Player Stats

Description

A dataframe containing the data dictionary for load_player_stats()

Usage

dictionary_player_stats

Format

An object of class data.frame with 48 rows and 2 columns.

See Also

vignette("Data Dictionary - Player Stats")

https://nflreadr.nflverse.com/articles/dictionary_player_stats.html

Data Dictionary: Player Stats Defense

Description

A dataframe containing the data dictionary for load_player_stats()

Usage

dictionary_player_stats_def

Format

An object of class data.frame with 22 rows and 3 columns.

See Also

vignette("Data Dictionary - Player Stats Defense")

https://nflreadr.nflverse.com/articles/dictionary_player_stats_def.html

dictionary_roster_status

Description

A dictionary translating the shorthand roster status to more verbose explanations of what each status indicates.

Usage

dictionary_roster_status

Format

An object of class data.frame with 19 rows and 2 columns.

Data Dictionary: Rosters

Description

A dataframe containing the data dictionary for load_rosters()

Usage

dictionary_rosters

Format

An object of class data.frame with 25 rows and 3 columns.

See Also

vignette("Data Dictionary - Rosters")

https://nflreadr.nflverse.com/articles/dictionary_rosters.html

Data Dictionary: Schedules

Description

A dataframe containing the data dictionary for load_schedules()

Usage

dictionary_schedules

Format

An object of class data.frame with 45 rows and 3 columns.

See Also

vignette("Data Dictionary - Schedules")

https://nflreadr.nflverse.com/articles/dictionary_schedules.html

Data Dictionary: Snap Counts

Description

A dataframe containing the data dictionary for load_snap_counts()

Usage

dictionary_snap_counts

Format

An object of class data.frame with 16 rows and 3 columns.

See Also

vignette("Data Dictionary - Snap Counts")

https://nflreadr.nflverse.com/articles/dictionary_snap_counts.html

Data Dictionary: Trades

Description

A dataframe containing the data dictionary for load_trades()

Usage

dictionary_trades

Format

An object of class data.frame with 11 rows and 3 columns.

See Also

vignette("Data Dictionary - Trades")

https://nflreadr.nflverse.com/articles/dictionary_trades.html

Get Current Week

Description

A helper function that returns the upcoming NFL regular season week based on either the nflverse schedules file (as found in load_schedules()) or some date-based heuristics (number of weeks since the first Monday of September)

Usage

get_current_week(use_date = FALSE)

Arguments

use_date

a logical to determine whether to use date-based heuristics to determine current week, default FALSE (i.e. uses schedule file)

Details

Note that the date heuristic will count a new week starting on Thursdays, while the schedule-based method will count a new week after the last game of the previous week, e.g. after MNF is completed. Tan and Ben argued for a while about this.

Value

current nfl regular season week as a numeric

See Also

Other Date utils: most_recent_season()

Examples

{
  
    try({ # schedules file as per default requires online access
    get_current_week()
    })
  
  # using the date method works offline
  get_current_week(use_date = TRUE)
}

Coalescing join

Description

EXPERIMENTAL! This function joins two dataframes together by key, and then coalesces any columns that have shared names (i.e. fills in NAs). A utility function primarily used internally within nflverse to help build player IDs

Usage

join_coalesce(
  x,
  y,
  by = NULL,
  type = c("left", "inner", "full"),
  ...,
  by.x = NULL,
  by.y = NULL,
  sort = TRUE,
  incomparables = c(NA, NaN)
)

Arguments

x, y

dataframes. Will be coerced to data.table
by

keys to join on, as a plain or named character vector
type

one of "left" (all rows of x and matching rows of y), "inner" (matching rows of x and y), "full" (all rows of x and y)
...

other args passed to merge.data.frame()
by.x, by.y

alternate form of keys to join on - if provided, will override by.
sort

whether to sort output by the join keys
incomparables

keys to NOT match on, i.e. NA should not match on NA.

Value

a data.frame joining x and y dataframes together, with every column from both x and y and patching NA values in x with those in y.

Examples

x <- data.frame(id1 = c(NA_character_,letters[1:4]), a = c(1,NA,3,NA,5), b = 1:5 * 10)
y <- data.frame(id2 = c(letters[3:11],NA_character_), a = -(1:10), c = 1:10 * 100)

join_coalesce(x,y, by = c("id1"="id2"))
join_coalesce(x,y, by.x = "id1", by.y = "id2")
join_coalesce(x,y, by = c("id1"="id2"), type = "inner")
join_coalesce(x,y, by = c("id1"="id2"), type = "full")

Load Combine Data from PFR

Description

Loads combine data since 2000 courtesy of PFR.

Usage

load_combine(
  seasons = TRUE,
  file_type = getOption("nflreadr.prefer", default = "rds")
)

Arguments

seasons

a numeric vector of seasons to return, default TRUE returns all available data
file_type

One of c("rds", "qs", "csv", "parquet"). Can also be set globally with options(nflreadr.prefer)

Value

A tibble of NFL combine data provided by Pro Football Reference.

See Also

Issues with this data should be filed here: https://github.com/nflverse/nflverse-data

https://nflreadr.nflverse.com/articles/dictionary_combine.html for a web version of the dictionary

dictionary_combine for the data dictionary as bundled within the package

Examples

try({ # prevents cran errors
  load_combine()
})

Load Historical Player Contracts from OverTheCap.com

Description

Loads player contracts from OverTheCap.com

Usage

load_contracts(file_type = getOption("nflreadr.prefer", default = "rds"))

Arguments

file_type

One of "rds", "qs", "csv", or "parquet". Can also be set globally with options(nflreadr.prefer)

Value

A tibble of active and non-active NFL player contracts.

See Also

https://overthecap.com/contract-history for a web version of the data

https://nflreadr.nflverse.com/articles/dictionary_contracts.html for a web version of the dictionary

dictionary_contracts for the data dictionary as bundled within the package

Issues with this data should be filed here: https://github.com/nflverse/rotc

Examples

try({ # prevents cran errors
  load_contracts()
})

Load Weekly Depth Charts

Description

Loads depth charts for each NFL team for each week back to 2001.

Usage

load_depth_charts(
  seasons = most_recent_season(),
  file_type = getOption("nflreadr.prefer", default = "rds")
)

Arguments

seasons

a numeric vector specifying what seasons to return, if TRUE returns all available data. Defaults to latest season.
file_type

One of c("rds", "qs", "csv", "parquet"). Can also be set globally with options(nflreadr.prefer)

Value

A tibble of week-level depth charts for each team.

See Also

https://nflreadr.nflverse.com/articles/dictionary_depth_charts.html for a web version of the dictionary

dictionary_depth_charts for the data dictionary as bundled within the package

Issues with this data should be filed here: https://github.com/nflverse/nflverse-data

Examples

try({ # prevents cran errors
  load_depth_charts(2020)
})

Load Draft Picks from PFR

Description

Loads every draft pick since 1980 courtesy of PFR.

Usage

load_draft_picks(
  seasons = TRUE,
  file_type = getOption("nflreadr.prefer", default = "rds")
)

Arguments

seasons

a numeric vector of seasons to return, default TRUE returns all available data
file_type

One of c("rds", "qs", "csv", "parquet"). Can also be set globally with options(nflreadr.prefer)

Value

A tibble of NFL draft picks provided by Pro Football Reference.

See Also

https://nflreadr.nflverse.com/articles/dictionary_draft_picks.html for the web data dictionary

dictionary_draft_picks for the data dictionary as bundled within the package

Issues with this data should be filed here: https://github.com/nflverse/nflverse-data

Examples

try({ # prevents cran errors
  load_draft_picks()
})

Load ESPN's QBR

Description

Load ESPN's QBR

Usage

load_espn_qbr(
  seasons = most_recent_season(),
  summary_type = c("season", "week"),
  file_type = getOption("nflreadr.prefer", default = "rds")
)

Arguments

seasons

a numeric vector of seasons to return, data available since 2006. Defaults to latest season available. TRUE will select all seasons.
summary_type

One of "season" or "week", defaults to "season"
file_type

One of c("rds", "qs", "csv", "parquet"). Can also be set globally with options(nflreadr.prefer)

Value

a tibble of ESPN QBR data, summarized according to summary_type

See Also

https://nflreadr.nflverse.com/articles/dictionary_espn_qbr.html for a web version of the dictionary

dictionary_espn_qbr for the data dictionary as bundled within the package

Issues with this data should be filed here: https://github.com/nflverse/espnscrapeR-data

Examples

load_espn_qbr(2020)

Load Expected Fantasy Points

Description

This function downloads precomputed expected points data from ffopportunity automated releases.

Usage

load_ff_opportunity(
  seasons = most_recent_season(),
  stat_type = c("weekly", "pbp_pass", "pbp_rush"),
  model_version = c("latest", "v1.0.0")
)

Arguments

seasons

a numeric vector of seasons to return, defaults to most recent season. If set to TRUE, returns all available data.
stat_type

one of "weekly", "pbp_pass", "pbp_rush"
model_version

one of "latest" or "v1.0.0"

Value

Precomputed expected fantasy points data from the ffopportunity automated releases.

See Also

https://ffopportunity.ffverse.com for more on the package, data, and modelling

https://nflreadr.nflverse.com/articles/dictionary_ff_opportunity.html for the web data dictionary

dictionary_ff_opportunity for the data dictionary bundled as a package data frame

Issues with this data should be filed here: https://github.com/ffverse/ffopportunity

Examples

try({ # prevents cran errors
  load_ff_opportunity()
  load_ff_opportunity(seasons = 2021, stat_type = "pbp_pass", model_version = "v1.0.0")
  })

Load Fantasy Player IDs

Description

Accesses DynastyProcess.com's database of fantasy football player IDs, which help connect nflverse to various other platforms and IDs.

Usage

load_ff_playerids()

Value

a dataframe of player IDs

See Also

https://nflreadr.nflverse.com/articles/dictionary_ff_playerids.html for the web data dictionary

Issues with this data should be filed here: https://github.com/dynastyprocess/data

Examples

try({ # prevents cran errors
load_ff_playerids()
})

Load Latest FantasyPros Rankings

Description

Accesses DynastyProcess.com's repository of the latest FP expert consensus rankings - updated on a weekly basis.

Usage

load_ff_rankings(type = c("draft", "week", "all"))

Arguments

type

one of "draft" (preseason), "week" (this week, inseason), or "all" (full archive)

Value

a dataframe of expert consensus rankings

See Also

https://nflreadr.nflverse.com/articles/dictionary_ff_rankings.html for the web data dictionary

https://www.fantasypros.com for the source of data

Issues with this data should be filed here: https://github.com/dynastyprocess/data

Examples

try({ # prevents cran errors
load_ff_rankings()
})

Load any rds/csv/csv.gz/parquet/qs file from a remote URL

Description

Load any rds/csv/csv.gz/parquet/qs file from a remote URL

Usage

load_from_url(url, ..., seasons = TRUE, nflverse = FALSE)

Arguments

url

a vector of URLs to load into memory. If more than one URL provided, will row-bind them.
...

named arguments that will be added as attributes to the data, e.g. nflverse_type = "pbp"
seasons

a numeric vector of years that will be used to filter the dataframe's season column. If TRUE (default), does not filter.
nflverse

TRUE to add nflverse_data classing and attributes.

Value

a dataframe, possibly of type nflverse_data

Examples

try({ # prevents cran errors
  urls <- c("https://github.com/nflverse/nflverse-data/releases/download/rosters/roster_2020.csv",
            "https://github.com/nflverse/nflverse-data/releases/download/rosters/roster_2021.csv")
 load_from_url(urls, nflverse = TRUE, nflverse_type = "rosters for 2020 & 2021")
})

Load FTN Charting Data

Description

FTN Data manually charts plays and has graciously provided a subset of their charting data to be published via the nflverse. Data is available from the 2022 season onwards and is charted within 48 hours following each game. This data is released under the CC-BY-SA 4.0 Creative Commons license and attribution must be made to FTN Data via nflverse

Usage

load_ftn_charting(
  seasons = most_recent_season(),
  file_type = getOption("nflreadr.prefer", default = "rds")
)

Arguments

seasons

a numeric vector of seasons to return, defaults to most recent season. If set to TRUE, returns all available data. Data available from 2022 onwards.
file_type

One of c("rds", "qs", "csv", "parquet"). Can also be set globally with options(nflreadr.prefer)

Value

Play-level manual charting data from FTN Data

Author(s)

FTN Data

Source

FTNData.com

See Also

https://www.ftndata.com

vignette("Data Dictionary - FTN Charting")

https://nflreadr.nflverse.com/articles/dictionary_ftn_charting.html for the web data dictionary

Other ftn_charting: dictionary_ftn_charting

Examples

try({ # prevents cran errors
  load_ftn_charting()
  })

Load Injury Reports

Description

Data collected from an API for weekly injury report data.

Usage

load_injuries(
  seasons = most_recent_season(),
  file_type = getOption("nflreadr.prefer", default = "rds")
)

Arguments

seasons

a numeric vector of seasons to return, data available since 2009. Defaults to latest season available.
file_type

One of c("rds", "qs", "csv", "parquet"). Can also be set globally with options(nflreadr.prefer)

Value

a tibble of season-level injury report data.

See Also

https://nflreadr.nflverse.com/articles/dictionary_injuries.html for a web version of the dictionary

dictionary_injuries for the data dictionary as bundled within the package

Issues with this data should be filed here: https://github.com/nflverse/nflverse-data

Examples

try({# prevents cran errors
    load_injuries(2020)
})

Load Player Level Weekly NFL Next Gen Stats

Description

Loads player level weekly stats provided by NFL Next Gen Stats starting with the 2016 season. Three different stat types are available and the current season's data updates every night. NGS will only provide data for players above a minimum number of pass/rush/rec attempts.

Usage

load_nextgen_stats(
  seasons = TRUE,
  stat_type = c("passing", "receiving", "rushing"),
  file_type = getOption("nflreadr.prefer", default = "rds")
)

Arguments

seasons

a numeric vector specifying what seasons to return, if TRUE returns all available data
stat_type

one of "passing", "receiving", or "rushing"
file_type

One of c("rds", "qs", "csv", "parquet"). Can also be set globally with options(nflreadr.prefer)

Value

A tibble of week-level player statistics provided by NFL Next Gen Stats. Regular season summary is given for week == 0.

See Also

https://nextgenstats.nfl.com/stats/passing for stat_type = "passing"

https://nextgenstats.nfl.com/stats/receiving for stat_type = "receiving"

https://nextgenstats.nfl.com/stats/rushing for stat_type = "rushing"

https://nflreadr.nflverse.com/articles/dictionary_nextgen_stats.html for a web version of the data dictionary

dictionary_nextgen_stats for the data dictionary as bundled within the package

Issues with this data should be filed here: https://github.com/nflverse/nflverse-data

Examples

try({ # prevents cran errors
  load_nextgen_stats(stat_type = "passing")
  load_nextgen_stats(stat_type = "receiving")
  load_nextgen_stats(stat_type = "rushing")
})

Load Officials

Description

Loads data on which officials are assigned to oversee a specific game. Data available from 2015 onwards.

Usage

load_officials(
  seasons = TRUE,
  file_type = getOption("nflreadr.prefer", default = "rds")
)

Arguments

seasons

a numeric vector specifying what seasons to return, if TRUE returns all available data
file_type

One of c("rds", "qs", "csv", "parquet"). Can also be set globally with options(nflreadr.prefer)

Value

A tibble with one row per game per official.

See Also

Issues with this data should be filed here: https://github.com/nflverse/nflreadr and it will be triaged appropriately.

Examples

try({ # prevents cran errors
  load_officials()
})

Load Participation Data

Description

Loads participation data from the nflverse-data repository

Usage

load_participation(
  seasons = most_recent_season(),
  include_pbp = FALSE,
  file_type = getOption("nflreadr.prefer", default = "rds")
)

Arguments

seasons

A numeric vector of 4-digit years associated with given NFL seasons - defaults to latest season. If set to TRUE, returns all available data since 2016.
include_pbp

a logical: download and join pbp to this data?
file_type

One of c("rds", "qs", "csv", "parquet"). Can also be set globally with options(nflreadr.prefer)

Value

A dataframe of participation data, optionally merged with play by play

Examples

try({ # prevents cran errors
  load_participation(seasons = 2020, include_pbp = TRUE)
})

Load Play By Play

Description

Loads play by play seasons from the nflverse-data repository

Usage

load_pbp(
  seasons = most_recent_season(),
  file_type = getOption("nflreadr.prefer", default = "rds")
)

Arguments

seasons

A numeric vector of 4-digit years associated with given NFL seasons - defaults to latest season. If set to TRUE, returns all available data since 1999.
file_type

One of c("rds", "qs", "csv", "parquet"). Can also be set globally with options(nflreadr.prefer)

Value

The complete nflfastR dataset as returned by nflfastR::build_nflfastR_pbp() (see below) for all given seasons

See Also

https://nflreadr.nflverse.com/articles/dictionary_pbp.html for a web version of the data dictionary

dictionary_pbp for the data dictionary bundled as a package dataframe

https://www.nflfastr.com/reference/build_nflfastR_pbp.html for the nflfastR function nflfastR::build_nflfastR_pbp()

Issues with this data should be filed here: https://github.com/nflverse/nflverse-pbp

Examples

try({ # prevents cran errors
  load_pbp(2019:2020)
})

Load Advanced Stats from PFR

Description

Loads player level season stats provided by Pro Football Reference starting with the 2018 season, primarily to augment existing nflverse data.

Usage

load_pfr_advstats(
  seasons = most_recent_season(),
  stat_type = c("pass", "rush", "rec", "def"),
  summary_level = c("week", "season"),
  file_type = getOption("nflreadr.prefer", default = "rds")
)

Arguments

seasons

a numeric vector specifying what seasons to return, if TRUE returns all available data
stat_type

one of "pass", "rush", "rec", "def"
summary_level

one of "week" (default) or "season" - some data is only available at the season level
file_type

One of c("rds", "qs", "csv", "parquet"). Can also be set globally with options(nflreadr.prefer)

Value

A tibble of player statistics provided by Pro Football Reference that supplements data in nflverse

See Also

https://nflreadr.nflverse.com/articles/dictionary_pfr_passing.html for the web data dictionary

https://www.pro-football-reference.com/years/2021/passing_advanced.htm

Issues with this data should be filed here: https://github.com/nflverse/nflverse-data

Examples

try({ # prevents cran errors
  load_pfr_advstats()
})

Load Player Level Weekly Stats

Description

Load Player Level Weekly Stats

Usage

load_player_stats(
  seasons = most_recent_season(),
  stat_type = c("offense", "defense", "kicking"),
  file_type = getOption("nflreadr.prefer", default = "rds")
)

Arguments

seasons

a numeric vector of seasons to return, defaults to most recent season. If set to TRUE, returns all available data.
stat_type

one of "offense", "defense", or "kicking"
file_type

One of c("rds", "qs", "csv", "parquet"). Can also be set globally with options(nflreadr.prefer)

Value

A tibble of week-level player statistics that aims to match NFL official box scores.

See Also

https://nflreadr.nflverse.com/articles/dictionary_player_stats.html for a web version of the data dictionary

dictionary_player_stats for the data dictionary

Issues with this data should be filed here: https://github.com/nflverse/nflverse-pbp

Examples

try({ # prevents cran errors
  load_player_stats()
  load_player_stats(stat_type = "kicking")
})

Load Players

Description

Load a dataframe of player-level information, including IDs and other mostly-immutable data (birthdates, college, draft position etc.)

Usage

load_players(file_type = getOption("nflreadr.prefer", default = "rds"))

Arguments

file_type

One of c("rds", "qs", "csv", "parquet"). Can also be set globally with options(nflreadr.prefer)

Value

A tibble with one row per player.

See Also

Issues with this data should be filed here: https://github.com/nflverse/nflreadr and it will be triaged appropriately.

Examples

try({ # prevents cran errors
  load_players()
})

Load Rosters

Description

Load Rosters

Usage

load_rosters(
  seasons = most_recent_season(roster = TRUE),
  file_type = getOption("nflreadr.prefer", default = "rds")
)

Arguments

seasons

a numeric vector of seasons to return, defaults to returning this year's data if it is March or later. If set to TRUE, will return all available data. Data available back to 1920.
file_type

One of c("rds", "qs", "csv", "parquet"). Can also be set globally with options(nflreadr.prefer)

Value

A tibble of season-level roster data.

See Also

https://nflreadr.nflverse.com/articles/dictionary_rosters.html for a web version of the data dictionary

dictionary_rosters for the data dictionary as a dataframe

Issues with this data should be filed here: https://github.com/nflverse/nflverse-data

Examples

try({ # prevents cran errors
  load_rosters(2020)
})

Load Weekly Rosters

Description

Returns week level rosters (rather than latest for a given season as returned by load_rosters())

Usage

load_rosters_weekly(
  seasons = most_recent_season(roster = TRUE),
  file_type = getOption("nflreadr.prefer", default = "rds")
)

Arguments

seasons

a numeric vector of seasons to return, defaults to returning this year's data if it is March or later. If set to TRUE, will return all available data. Data available back to 2002.
file_type

One of c("rds", "qs", "csv", "parquet"). Can also be set globally with options(nflreadr.prefer)

Value

A tibble of weekly roster data.

See Also

Issues with this data should be filed here: https://github.com/nflverse/nflverse-data

Examples

try({ # prevents cran errors
  load_rosters_weekly(2020)
})

Load Game/Schedule Data

Description

This returns game/schedule information as maintained by Lee Sharpe.

Usage

load_schedules(seasons = TRUE)

Arguments

seasons

a numeric vector of seasons to return, default TRUE returns all available data.

Value

A tibble of game information for past and/or future games.

See Also

https://nflreadr.nflverse.com/articles/dictionary_schedules.html for a web version of the data dictionary

dictionary_schedules for the data dictionary as a dataframe

Issues with this data should be filed here: https://github.com/nflverse/nfldata

Examples

try({ # prevents cran errors
 load_schedules(2020)
})

Load Snap Counts from PFR

Description

Loads game level snap counts stats provided by Pro Football Reference starting with the 2012 season.

Usage

load_snap_counts(
  seasons = most_recent_season(),
  file_type = getOption("nflreadr.prefer", default = "rds")
)

Arguments

seasons

a numeric vector specifying what seasons to return, if TRUE returns all available data
file_type

One of c("rds", "qs", "csv", "parquet"). Can also be set globally with options(nflreadr.prefer)

Value

A tibble of game-level snap counts provided by Pro Football Reference.

See Also

https://nflreadr.nflverse.com/articles/dictionary_snap_counts.html for the web data dictionary

dictionary_snap_counts for the data dictionary as bundled within the package

Issues with this data should be filed here: https://github.com/nflverse/nflverse-pfr

Examples

try({ # prevents CRAN errors
  load_snap_counts()
  })

Load NFL Team Graphics, Colors, and Logos

Description

Loads team graphics, colors, and logos - useful for plots!

Usage

load_teams(current = TRUE)

Arguments

current

If TRUE (the default), returns a standardized list of current teams only, with abbreviations as per team_abbr_mapping.

Value

A tibble of team-level image URLs and hex color codes.

See Also

Issues with this data should be filed here: https://github.com/nflverse/nflverse-pbp

Examples

try({ # prevents cran errors
  load_teams()
})

Load Trades

Description

This returns a table of historical trades as maintained by Lee Sharpe.

Usage

load_trades(seasons = TRUE)

Arguments

seasons

a numeric vector of seasons to return, default TRUE returns all available data.

Value

A tibble of game information for past and/or future games.

See Also

https://nflreadr.nflverse.com/articles/dictionary_trades.html for a web version of the dictionary

dictionary_trades for the data dictionary as bundled within the package

Issues with this data should be filed here: https://github.com/nflverse/nfldata

Examples

load_trades(2020)

Get Latest Season

Description

A helper function to choose the most recent season available for a given dataset

Usage

most_recent_season(roster = FALSE)

get_latest_season(roster = FALSE)

get_current_season(roster = FALSE)

Arguments

roster

Either TRUE or FALSE. If TRUE, will return current year after March 15th, otherwise previous year. If FALSE, will return current year on or after Thursday following Labor Day, i.e. Thursday after the first Monday in September. Otherwise previous year.

Value

most recent season (a four digit numeric)

See Also

Other Date utils: get_current_week()

nflverse Timezone

Description

A character string defining the default timezone for data across the nflverse

Usage

nflverse_data_timezone

Format

An object of class character of length 1.

Bulk download utilities via piggyback

Description

This function downloads or updates data from the nflverse-data repository releases, creating subfolders that match the release structure.

Usage

nflverse_download(
  ...,
  folder_path = getOption("nflreadr.download_path", default = "."),
  file_type = getOption("nflreadr.prefer", default = "rds"),
  use_hive = file_type %in% c("parquet", "csv"),
  .token = "default"
)

Arguments

...

releases to download, provided in either unquoted or character format (i.e. pbp or "pbp" are both fine). Available release names can be listed with nflverse_releases()
folder_path

a folder in which subfolders will be created for each release - defaults to path specified in options(nflreadr.download_path) or "." (the current working directory)
file_type

one of c("rds","parquet", "csv", "qs") - defaults to file type specified in options(nflreadr.prefer) or "rds"
use_hive

whether to create hive-style partition folders for each season, e.g. "~/pbp/.season=2021/pbp.csv"
.token

a GitHub API token, "default" uses gh::gh_token()

Examples

try({
  ## could also set options like
  # options(nflreadr.download_path = tempdir(), nflreadr.prefer = "parquet")

  nflverse_download(combine, contracts, folder_path = tempdir(), file_type = "parquet")

  list.files(tempdir(),pattern = ".parquet$") # check that files were downloaded!
})

Compute nflverse Game Identifiers

Description

Compute nflverse Game Identifiers

Usage

nflverse_game_id(season, week, away, home)

Arguments

season

4 digit season between 1999 and the output of most_recent_season()
week

Numeric or character giving the week, between 1 and 22.
home, away

Valid NFL team abbreviation as it can be found in team_abbr_mapping

Value

A character vector

Examples

nflverse_game_id(2022, 2, "LAC", "KC")

List all available nflverse releases

Description

This functions lists all nflverse data releases that are available in the nflverse-data repo. Release names can be used for downloads in nflverse_download().

Usage

nflverse_releases(.token = "default")

Arguments

.token

a GitHub API token, "default" uses gh::gh_token()

Value

A dataframe containing release names, release descriptions, and other relevant release information.

Examples

try( # avoids cran failures, can skip in normal usage
nflverse_releases()
)

Get a Situation Report on System, nflverse/ffverse Package Versions and Dependencies

Description

This function gives a quick overview of the versions of R and the operating system as well as the versions of nflverse/ffverse 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.

Usage

nflverse_sitrep(
  pkg = c("nflreadr", "nflfastR", "nflseedR", "nfl4th", "nflplotR", "nflverse"),
  recursive = TRUE,
  redact_path = TRUE
)

ffverse_sitrep(
  pkg = c("ffscrapr", "ffsimulator", "ffpros", "ffopportunity"),
  recursive = TRUE,
  redact_path = TRUE
)

.sitrep(
  pkg,
  recursive = TRUE,
  redact_path = TRUE,
  dev_repos = c("https://nflverse.r-universe.dev", "https://ffverse.r-universe.dev")
)

Arguments

pkg

a character vector naming installed packages, or NULL (the default) meaning all nflverse packages. The function checks internally if all packages are installed and informs if that is not the case.
recursive

a logical indicating whether dependencies of pkg and their dependencies (and so on) should be included. Can also be a character vector listing the types of dependencies, a subset of c("Depends", "Imports", "LinkingTo", "Suggests", "Enhances"). Character string "all" is shorthand for that vector, character string "most" for the same vector without "Enhances", character string "strong" (default) for the first three elements of that vector.
redact_path

a logical indicating whether options that contain "path" in the name should be redacted, default = TRUE
dev_repos

Developmental cran-like repos to check, e.g. r-universe repos

Examples

try({
nflverse_sitrep()
ffverse_sitrep()
.sitrep("cachem")
})

Load .parquet file from a remote connection

Description

Retrieves a parquet file from URL. This function is cached

Usage

parquet_from_url(url)

Arguments

url

a character url

Value

a dataframe as parsed by arrow::read_parquet()

Examples

try({
  parquet_from_url(
    "https://github.com/nflverse/nflverse-data/releases/download/player_stats/player_stats.parquet"
  )
})

Alternate player name mappings

Description

A named character vector mapping common alternate names, re-exported from ffscrapr.

Usage

player_name_mapping

Format

A named character vector

name attribute

The "alternate" name.

value attribute

The "correct" name.

Details

You can suggest additions to this table by opening an issue in ffscrapr.

Examples

player_name_mapping[c("Chatarius Atwell", "Robert Kelley")]

Progressively

Description

This function helps add progress-reporting to any function - given function f() and progressor p(), it will return a new function that calls f() and then (on exiting) will call p() after every iteration. This is inspired by purrr's safely, quietly, and possibly function decorators.

Usage

progressively(f, p = NULL)

Arguments

f

a function to add progressor functionality to.
p

a function such as one created by progressr::progressor() - also accepts purrr-style lambda functions.

Value

a function that does the same as f but it calls p() after iteration.

See Also

https://nflreadr.nflverse.com/articles/exporting_nflreadr.html for vignette on exporting nflreadr in packages

Examples

try({ # prevents cran errors

urls <- rep("https://github.com/nflverse/nflverse-data/releases/download/test/combines.csv",3)

lapply(urls, progressively(read.csv, ~cli::cli_progress_step('Loading...')))

read_rosters <- function(urls){
  p <- progressr::progressor(along = urls)
  lapply(urls, progressively(read.csv, p))
}

progressr::with_progress(read_rosters())

})

Load .qs file from a remote connection

Description

Load .qs file from a remote connection

Usage

qs_from_url(url)

Arguments

url

a character url

Value

a dataframe as parsed by qs::qdeserialize()

Examples

try({
  qs_from_url(
    "https://github.com/nflverse/nflverse-data/releases/download/player_stats/player_stats.qs"
  )
})

Load raw filedata from a remote connection

Description

This function allows you to retrieve data from a URL into raw format, which can then be passed into the appropriate file-reading function. Data is memoised/cached for 24 hours.

Usage

raw_from_url(url)

Arguments

url

a character url

Value

a raw vector

Examples

try({ # prevents CRAN errors
head(raw_from_url(
  "https://github.com/nflverse/nflverse-data/releases/download/test/combines.rds"
  ),
50)
})

Load .rds file from a remote connection

Description

Load .rds file from a remote connection

Usage

rds_from_url(url)

Arguments

url

a character url

Value

a dataframe as created by readRDS()

Examples

try({ # prevents cran errors
  rds_from_url("https://github.com/nflverse/nflverse-data/releases/download/test/combines.rds")
})

Statistical Mode

Description

Computes the statistical mode, i.e. the value that appears most often in a vector. Returns the first match, if TRUE for multiple values.

Usage

stat_mode(x, ..., na.rm = FALSE)

Arguments

x

A vector of data values.
...

Further arguments, currently unused.
na.rm

a logical evaluating to TRUE or FALSE indicating whether NA values should be stripped before the computation proceeds.

Value

The statistical mode with the same type as the input vector x.

Examples

vector_numeric <- sample(1:5, 15, TRUE)
vector_numeric
stat_mode(vector_numeric)

vector_character <- sample(LETTERS[1:5], 15, TRUE)
vector_character
stat_mode(vector_character)

Alternate team abbreviation mappings

Description

A named character vector mapping common alternate team abbreviations.

Usage

team_abbr_mapping

Format

A named character vector

name attribute

The "alternate" name.

value attribute

The "correct" name.

Details

You can suggest additions to this table by opening an issue in nflreadr.

See Also

team_abbr_mapping_norelocate for the same thing but relocations stay in their original cities.

Examples

team_abbr_mapping[c("STL", "OAK","CRD","BLT", "CLV")]

Alternate team abbreviation mappings, no relocation

Description

A named character vector mapping common alternate team abbreviations, but does not follow relocations to their current city.

Usage

team_abbr_mapping_norelocate

Format

A named character vector

name attribute

The "alternate" name.

value attribute

The "correct" name.

Details

You can suggest additions to this table by opening an issue in nflreadr.

Examples

team_abbr_mapping_norelocate[c("STL", "OAK","CRD","BLT", "CLV")]