A set of functions to access National Football League play-by-play data from <https://www.nfl.com/>.

This package allows data driven sports enthusiasts to use the NFL JSON API data to perform detailed analysis at game, season, and player levels. The functions within this package help parse and clean the data from NFL.com for R users. This package was built to enhance advanced sports analytics research specifically for American football with the hopes of developing metrics and insights that could potentially be useful for professional NFL teams as well as the public.

An easy package for scraping and processing Australia Rules Football (AFL) data. 'fitzRoy' provides a range of functions for accessing publicly available data from 'AFL Tables' <https://afltables.com/afl/afl_index.html>, 'Footy Wire' <https://www.footywire.com> and 'The Squiggle' <https://squiggle.com.au>. Further functions allow for easy processing, cleaning and transformation of this data into formats that can be used for analysis.

all things hockey

This package is used to pull StatsBomb data directly from the API. Currently, this is only supported on Windows computers since pulling functions use parallel computing.

Provides tools to visualise x,y-coordinates of soccer players and event data (e.g. passes, shots). Uses ggplot to draw soccer pitch and overplot expected goal maps, pass maps, average player positions, player heatmaps, individual player paths, player flow fields, and more.

A partir de los ficheros proporcionados por OPTA en formato XML permite elaborar anA!lisis y visualizaciones de grafos de pases, radar de pases, corners, tiros y mapas de calor de desde donde pasan y adonde pasan

Football / soccer related visualisations and analysis

Soccer/football analytics blog posts & data viz from the World Cup, Premier League, Copa America, and beyond. Using ggplot2, ggsoccer, & more. (Est. June 2018) ****Please look at the README for best version of the code!****

An R package for working with College Football Data. It is an R API wrapper around <https://collegefootballdata.com/> made available by the cfbscrapR team. It provides users the capability to access a plethora of endpoints, and supplement that data with additional information (Expected Points Added/Win Probability added).

Code to scrape play-by-play data from the XFL website and reshape data into more useful columns for public analysis

Main use case is to collect ESPN QBR for NFL and college football. Alternative functions include getting NFL standings and scraping NFL season-level stats.

Scrapes NCAA stats for most college sports from stats.ncaa.org

Provides numerous utilities for acquiring and analyzing baseball data from online sources such as 'Baseball Reference' <https://www.baseball-reference.com/>, 'FanGraphs' <https://www.fangraphs.com/>, and the 'MLB Stats' API <https://www.mlb.com/>.

Multi-core processing of data from Major League Baseball Advanced Media <http://gd2.mlb.com/components/game/mlb/>. Additional tools to parallel process large data sets and write them to a database.

Draw Major Leagure Stadiums in the ggplot2 framework

There are two primary purposes this package serves: 1) it facilitates the computation of openWAR, a fully open-source implementation of Wins Above Replacement (WAR) that could serve as a reference implementation for the sabermetric community; and 2) it downloads raw XML files from the MLBAM GameDay web application and processes them into play-by-play data in a tabular format. This play-by-play information is similar in spirit, though not in syntax, to play-by-play data made available by Retrosheet. Those interested in the modeling choices that we have made in our computation of openWAR should consult our JQAS or arXiv paper on that subject. This implementation of openWAR includes functions for constructing interval estimates of WAR for each player, as well as comparing openWAR point estimates to those of Baseball- Reference.com's rWAR.

With 'pitchRx', one can easily obtain Major League Baseball Advanced Media's 'Gameday' data (as well as store it in a remote database). The 'Gameday' website hosts a wealth of data in XML format, but perhaps most interesting is 'pitchfx'. Among other things, 'pitchfx' data can be used to recreate a baseball's flight path from a pitcher's hand to home plate. With pitchRx, one can easily create animations and interactive 3D 'scatterplots' of the baseball's flight path. 'pitchfx' data is also commonly used to generate a static plot of baseball locations at the moment they cross home plate. These plots, sometimes called strike-zone plots, can also refer to a plot of event probabilities over the same region. 'pitchRx' provides an easy and robust way to generate strike-zone plots using the 'ggplot2' package.

Building an SQL database of baseball play-by-play data from Retrosheet requires an ETL process and special tools. This package automates and streamlines that process.

An R package for working with NCAA Men's Basketball Play-by-Play Data. This package allows users to scrape play-by-play data into a tidy format, create assist networks games of their choosing, and examine in-game win probability charts.

This package gives users the ability to work with NCAA Basketball data in a clean and detailed manner. The functions included can retrieve and manipulate NCAA play-by-play data, giving users a variety of ways to find insights about their favorite players and teams. An especially important feature is the ability to report who is on the court at each event in the play-by-play, opening up many possible areas of analysis.

NBA data tools for R

Provides simple functions for accessing data/tables on <http://www.basketball-reference.com>.

`wncaahoopR` is an R package for working with women's NCAA Basketball play-by-play (and other) data, primarily by scraping from ESPN, but in a different way than the `ncaahoopR` package from Luke Benz (lbenz730). This package has a single function for scraping data and then makes use of the resulting `pbp` object within R to produce charts similar to those in `ncaahoopR`.

Tools for analyzing performances of cricketers based on stats in ESPN Cricinfo Statsguru. The toolset can be used for analysis of Tests,ODIs and Twenty20 matches of both batsmen and bowlers. The package can also be used to analyze team performances.

Analyzing performances of cricketers and cricket teams based on 'yaml' match data from Cricsheet <https://cricsheet.org/>.

Data on international and other major cricket matches from ESPNCricinfo <https://www.espncricinfo.com> and Cricsheet <https://cricsheet.org>. This package provides some functions to download the data into tibbles ready for analysis.

The "elite" package allows users to easily scrape data from EliteProspects in a [fairly] tidy manner.

Retrieves and processes the data exposed by the open 'NHL' API. This includes information on players, teams, games, tournaments, drafts, standings, schedules and other endpoints. A lower-level interface to access the data via URLs directly is also provided.

Add game events to a database file to use for statistical analysis of hockey games. This means we only call the 'NHL' API once for each game we want to add. We will have very fast retrieval of data once games have been added since the data is stored locally. We use the API located at <https://statsapi.web.nhl.com/api/v1/teams> with supplemental data from <https://www.nhl.com/scores/>. Other endpoints can be found at <https://gitlab.com/dword4/nhlapi>.

This package allows data driven sports enthusiasts to easily access event data for soccer games from ESPN. The functions within this package help find, parse, and clean the commentary data from ESPN for R users.

R package that calls various free soccer APIs

This repository includes all the code and data used for developing the expected league points above replacement for soccer as described in "Positional Value in Soccer: Expected League Points Added above Replacement"

Soccer club results data from 1871-2020.

The 'ggplot2' package provides a powerful set of tools for visualising and investigating data. The 'ggsoccer' package provides a set of functions for elegantly displaying and exploring soccer event data with 'ggplot2'. Providing extensible layers and themes, it is designed to work smoothly with a variety of popular sports data providers.

An tidyverse-friendly package for fetching data from football-data.co.uk for soccer modelling.

A collection of models and tools for soccer analytics.

A package with various functions that help people working with OPTA and ChyronHego data.

nwslR is an R package that contains datasets and analysis functionality for the National Women’s Soccer League (NWSL). Founded in 2013, the NWSL is the United States’ top professional women’s soccer league, featuring players from all over the world.

Provides tools to retrieve understat <https://understat.com/> data in a tidy format.

Last two minute report data from the NBA

The goalmodel package let you model the number of goals scored in sport games. The models are primarily aimed at modelling and predicting football (soccer) scores, but could also be applicable for similar sports, such as hockey and handball.

This packages allows you to create 2D animations of soccer tracking data in addition to do some player calculations and team possession stats.

Use this package to scrap Test Matches, One Day Internationals, Twenty-20 Internationals data of a player from ESPNCricinfo's Statsguru (<http://stats.espncricinfo.com/ci/engine/stats/index.html>) and then visualize their batting, bowling and fielding performances in the form of charts and graphs.

A utility to quickly obtain clean and tidy men's basketball play by play data. Provides functions to access live play by play and box score data from ESPN<https://www.espn.com> with shot locations when available. It is also a full NBA Stats API<https://www.nba.com/stats/> wrapper. It is also a scraping and aggregating interface for Ken Pomeroy's men's college basketball statistics website<https://kenpom.com>. It provides users with an active subscription the capability to scrape the website tables and analyze the data for themselves.

Quick calculations of common travel and schedule related information for Basketball teams (currently only NBA teams) and various different seasons (since 1947). The retrieved data includes distance travelled between games, time zone for each game, time shifts betwen games, number of rest days between games, estimated flight duration, etc. Plotting options enable users to visualize maps of flight paths between games. This package uses the game_logs() function from the really useful nbastatR package written by Bresler. A (2020) <https://github.com/abresler/nbastatR> to query seasonn schedule and player stats from publicly available sources.

This package provides functions to easily download and manipulate data from super netball matches.

Running a deep learning model to predict netball matches

NCAA Womens version of bigballR: This package gives users the ability to work with NCAA Basketball data in a clean and detailed manner. The functions included can retrieve and manipulate NCAA play-by-play data, giving users a variety of ways to find insights about their favorite players and teams. An especially important feature is the ability to report who is on the court at each event in the play-by-play, opening up many possible areas of analysis.

R package to do the equivalent work of Kloppy for python. General helpers and models for football analytics in R.

A set of functions to simulate National Football League seasons including the sophisticated tie-breaking procedures.

A utility for working with women's basketball data. A scraping and aggregating interface for the WNBA Stats API <https://stats.wnba.com/> and ESPN's <https://www.espn.com> women's college basketball and WNBA statistics. It provides users with the capability to access the game play-by-plays, box scores, standings and results to analyze the data for themselves.

An R package for working with NCAA Men's Basketball play-by-play data

Create scaled 'ggplot' representations of playing surfaces. Playing surfaces are drawn pursuant to rule-book specifications. This package should be used as a baseline plot for displaying any type of tracking data.

A minimal package for downloading data from 'GitHub' repositories of the 'nflverse' project.

ggshakeR is an analysis and visualization R package that works with publically available soccer data. The datasets (for now) include FBref, StatsBomb, and understat.

A utility to scrape and load play-by-play data and statistics from the Professional Women's Hockey League <https://www.thepwhl.com/>, formerly known as the Premier Hockey Federation (PHF) or National Women's Hockey League (NWHL). Additionally, allows access to the National Hockey League's stats API <https://www.nhl.com/>.

Allow users to obtain clean and tidy football (soccer) game, team and player data. Data is collected from a number of popular sites, including 'FBref', transfer and valuations data from 'Transfermarkt'<https://www.transfermarkt.com/> and shooting location and other match stats data from 'Understat'<https://understat.com/>. It gives users the ability to access data more efficiently, rather than having to export data tables to files before being able to complete their analysis.

A set of functions to enable users to extract chess game data from popular chess sites, including 'Lichess'<https://lichess.org/> and 'Chess.com' <https://www.chess.com/> and then perform analysis on that game data.

A set of functions to visualize National Football League analysis in 'ggplot2' plots and 'gt' tables.

This package currently provides data from the 2022 Beijing Olympics from NBC's API. The name of this package comes from the Olympic Motto: "Faster, Higher, Stronger - Together". This package is still a work in progress and new functions will hopefully be added soon! This package will likely be updated to include Paris 2024 Data when that event comes around.

Obtain Formula 1 data via the 'Jolpica API' <https://jolpi.ca> and the unofficial API <https://www.formula1.com/en/timing/f1-live> via the 'fastf1' 'Python' library <https://docs.fastf1.dev/>.

What the package does (one paragraph).

Allow users to obtain basketball statistics for the Australian basketball league 'NBL'<https://nbl.com.au/>. Stats include play-by-play, shooting locations, results and box scores for teams and players.

A set of functions to access National Football League play-by-play data from <https://www.nfl.com/>.

This package allows data driven sports enthusiasts to use the NFL JSON API data to perform detailed analysis at game, season, and player levels. The functions within this package help parse and clean the data from NFL.com for R users. This package was built to enhance advanced sports analytics research specifically for American football with the hopes of developing metrics and insights that could potentially be useful for professional NFL teams as well as the public.

An easy package for scraping and processing Australia Rules Football (AFL) data. 'fitzRoy' provides a range of functions for accessing publicly available data from 'AFL Tables' <https://afltables.com/afl/afl_index.html>, 'Footy Wire' <https://www.footywire.com> and 'The Squiggle' <https://squiggle.com.au>. Further functions allow for easy processing, cleaning and transformation of this data into formats that can be used for analysis.

all things hockey

This package is used to pull StatsBomb data directly from the API. Currently, this is only supported on Windows computers since pulling functions use parallel computing.

Provides tools to visualise x,y-coordinates of soccer players and event data (e.g. passes, shots). Uses ggplot to draw soccer pitch and overplot expected goal maps, pass maps, average player positions, player heatmaps, individual player paths, player flow fields, and more.

A partir de los ficheros proporcionados por OPTA en formato XML permite elaborar anA!lisis y visualizaciones de grafos de pases, radar de pases, corners, tiros y mapas de calor de desde donde pasan y adonde pasan

Football / soccer related visualisations and analysis

Soccer/football analytics blog posts & data viz from the World Cup, Premier League, Copa America, and beyond. Using ggplot2, ggsoccer, & more. (Est. June 2018) ****Please look at the README for best version of the code!****

An R package for working with College Football Data. It is an R API wrapper around <https://collegefootballdata.com/> made available by the cfbscrapR team. It provides users the capability to access a plethora of endpoints, and supplement that data with additional information (Expected Points Added/Win Probability added).

Code to scrape play-by-play data from the XFL website and reshape data into more useful columns for public analysis

Main use case is to collect ESPN QBR for NFL and college football. Alternative functions include getting NFL standings and scraping NFL season-level stats.

Scrapes NCAA stats for most college sports from stats.ncaa.org

Provides numerous utilities for acquiring and analyzing baseball data from online sources such as 'Baseball Reference' <https://www.baseball-reference.com/>, 'FanGraphs' <https://www.fangraphs.com/>, and the 'MLB Stats' API <https://www.mlb.com/>.

Multi-core processing of data from Major League Baseball Advanced Media <http://gd2.mlb.com/components/game/mlb/>. Additional tools to parallel process large data sets and write them to a database.

Draw Major Leagure Stadiums in the ggplot2 framework

There are two primary purposes this package serves: 1) it facilitates the computation of openWAR, a fully open-source implementation of Wins Above Replacement (WAR) that could serve as a reference implementation for the sabermetric community; and 2) it downloads raw XML files from the MLBAM GameDay web application and processes them into play-by-play data in a tabular format. This play-by-play information is similar in spirit, though not in syntax, to play-by-play data made available by Retrosheet. Those interested in the modeling choices that we have made in our computation of openWAR should consult our JQAS or arXiv paper on that subject. This implementation of openWAR includes functions for constructing interval estimates of WAR for each player, as well as comparing openWAR point estimates to those of Baseball- Reference.com's rWAR.

With 'pitchRx', one can easily obtain Major League Baseball Advanced Media's 'Gameday' data (as well as store it in a remote database). The 'Gameday' website hosts a wealth of data in XML format, but perhaps most interesting is 'pitchfx'. Among other things, 'pitchfx' data can be used to recreate a baseball's flight path from a pitcher's hand to home plate. With pitchRx, one can easily create animations and interactive 3D 'scatterplots' of the baseball's flight path. 'pitchfx' data is also commonly used to generate a static plot of baseball locations at the moment they cross home plate. These plots, sometimes called strike-zone plots, can also refer to a plot of event probabilities over the same region. 'pitchRx' provides an easy and robust way to generate strike-zone plots using the 'ggplot2' package.

Building an SQL database of baseball play-by-play data from Retrosheet requires an ETL process and special tools. This package automates and streamlines that process.

An R package for working with NCAA Men's Basketball Play-by-Play Data. This package allows users to scrape play-by-play data into a tidy format, create assist networks games of their choosing, and examine in-game win probability charts.

This package gives users the ability to work with NCAA Basketball data in a clean and detailed manner. The functions included can retrieve and manipulate NCAA play-by-play data, giving users a variety of ways to find insights about their favorite players and teams. An especially important feature is the ability to report who is on the court at each event in the play-by-play, opening up many possible areas of analysis.

NBA data tools for R

Provides simple functions for accessing data/tables on <http://www.basketball-reference.com>.

`wncaahoopR` is an R package for working with women's NCAA Basketball play-by-play (and other) data, primarily by scraping from ESPN, but in a different way than the `ncaahoopR` package from Luke Benz (lbenz730). This package has a single function for scraping data and then makes use of the resulting `pbp` object within R to produce charts similar to those in `ncaahoopR`.

Tools for analyzing performances of cricketers based on stats in ESPN Cricinfo Statsguru. The toolset can be used for analysis of Tests,ODIs and Twenty20 matches of both batsmen and bowlers. The package can also be used to analyze team performances.

Analyzing performances of cricketers and cricket teams based on 'yaml' match data from Cricsheet <https://cricsheet.org/>.

Data on international and other major cricket matches from ESPNCricinfo <https://www.espncricinfo.com> and Cricsheet <https://cricsheet.org>. This package provides some functions to download the data into tibbles ready for analysis.

The "elite" package allows users to easily scrape data from EliteProspects in a [fairly] tidy manner.

Retrieves and processes the data exposed by the open 'NHL' API. This includes information on players, teams, games, tournaments, drafts, standings, schedules and other endpoints. A lower-level interface to access the data via URLs directly is also provided.

Add game events to a database file to use for statistical analysis of hockey games. This means we only call the 'NHL' API once for each game we want to add. We will have very fast retrieval of data once games have been added since the data is stored locally. We use the API located at <https://statsapi.web.nhl.com/api/v1/teams> with supplemental data from <https://www.nhl.com/scores/>. Other endpoints can be found at <https://gitlab.com/dword4/nhlapi>.

This package allows data driven sports enthusiasts to easily access event data for soccer games from ESPN. The functions within this package help find, parse, and clean the commentary data from ESPN for R users.

R package that calls various free soccer APIs

This repository includes all the code and data used for developing the expected league points above replacement for soccer as described in "Positional Value in Soccer: Expected League Points Added above Replacement"

Soccer club results data from 1871-2020.

The 'ggplot2' package provides a powerful set of tools for visualising and investigating data. The 'ggsoccer' package provides a set of functions for elegantly displaying and exploring soccer event data with 'ggplot2'. Providing extensible layers and themes, it is designed to work smoothly with a variety of popular sports data providers.

An tidyverse-friendly package for fetching data from football-data.co.uk for soccer modelling.

A collection of models and tools for soccer analytics.

A package with various functions that help people working with OPTA and ChyronHego data.

nwslR is an R package that contains datasets and analysis functionality for the National Women’s Soccer League (NWSL). Founded in 2013, the NWSL is the United States’ top professional women’s soccer league, featuring players from all over the world.

Provides tools to retrieve understat <https://understat.com/> data in a tidy format.

Last two minute report data from the NBA

The goalmodel package let you model the number of goals scored in sport games. The models are primarily aimed at modelling and predicting football (soccer) scores, but could also be applicable for similar sports, such as hockey and handball.

This packages allows you to create 2D animations of soccer tracking data in addition to do some player calculations and team possession stats.

Use this package to scrap Test Matches, One Day Internationals, Twenty-20 Internationals data of a player from ESPNCricinfo's Statsguru (<http://stats.espncricinfo.com/ci/engine/stats/index.html>) and then visualize their batting, bowling and fielding performances in the form of charts and graphs.

A utility to quickly obtain clean and tidy men's basketball play by play data. Provides functions to access live play by play and box score data from ESPN<https://www.espn.com> with shot locations when available. It is also a full NBA Stats API<https://www.nba.com/stats/> wrapper. It is also a scraping and aggregating interface for Ken Pomeroy's men's college basketball statistics website<https://kenpom.com>. It provides users with an active subscription the capability to scrape the website tables and analyze the data for themselves.

Quick calculations of common travel and schedule related information for Basketball teams (currently only NBA teams) and various different seasons (since 1947). The retrieved data includes distance travelled between games, time zone for each game, time shifts betwen games, number of rest days between games, estimated flight duration, etc. Plotting options enable users to visualize maps of flight paths between games. This package uses the game_logs() function from the really useful nbastatR package written by Bresler. A (2020) <https://github.com/abresler/nbastatR> to query seasonn schedule and player stats from publicly available sources.

This package provides functions to easily download and manipulate data from super netball matches.

Running a deep learning model to predict netball matches

NCAA Womens version of bigballR: This package gives users the ability to work with NCAA Basketball data in a clean and detailed manner. The functions included can retrieve and manipulate NCAA play-by-play data, giving users a variety of ways to find insights about their favorite players and teams. An especially important feature is the ability to report who is on the court at each event in the play-by-play, opening up many possible areas of analysis.

R package to do the equivalent work of Kloppy for python. General helpers and models for football analytics in R.

A set of functions to simulate National Football League seasons including the sophisticated tie-breaking procedures.

A utility for working with women's basketball data. A scraping and aggregating interface for the WNBA Stats API <https://stats.wnba.com/> and ESPN's <https://www.espn.com> women's college basketball and WNBA statistics. It provides users with the capability to access the game play-by-plays, box scores, standings and results to analyze the data for themselves.

An R package for working with NCAA Men's Basketball play-by-play data

Create scaled 'ggplot' representations of playing surfaces. Playing surfaces are drawn pursuant to rule-book specifications. This package should be used as a baseline plot for displaying any type of tracking data.

A minimal package for downloading data from 'GitHub' repositories of the 'nflverse' project.

ggshakeR is an analysis and visualization R package that works with publically available soccer data. The datasets (for now) include FBref, StatsBomb, and understat.

A utility to scrape and load play-by-play data and statistics from the Professional Women's Hockey League <https://www.thepwhl.com/>, formerly known as the Premier Hockey Federation (PHF) or National Women's Hockey League (NWHL). Additionally, allows access to the National Hockey League's stats API <https://www.nhl.com/>.

Allow users to obtain clean and tidy football (soccer) game, team and player data. Data is collected from a number of popular sites, including 'FBref', transfer and valuations data from 'Transfermarkt'<https://www.transfermarkt.com/> and shooting location and other match stats data from 'Understat'<https://understat.com/>. It gives users the ability to access data more efficiently, rather than having to export data tables to files before being able to complete their analysis.

A set of functions to enable users to extract chess game data from popular chess sites, including 'Lichess'<https://lichess.org/> and 'Chess.com' <https://www.chess.com/> and then perform analysis on that game data.

A set of functions to visualize National Football League analysis in 'ggplot2' plots and 'gt' tables.

This package currently provides data from the 2022 Beijing Olympics from NBC's API. The name of this package comes from the Olympic Motto: "Faster, Higher, Stronger - Together". This package is still a work in progress and new functions will hopefully be added soon! This package will likely be updated to include Paris 2024 Data when that event comes around.

Obtain Formula 1 data via the 'Jolpica API' <https://jolpi.ca> and the unofficial API <https://www.formula1.com/en/timing/f1-live> via the 'fastf1' 'Python' library <https://docs.fastf1.dev/>.

What the package does (one paragraph).

Allow users to obtain basketball statistics for the Australian basketball league 'NBL'<https://nbl.com.au/>. Stats include play-by-play, shooting locations, results and box scores for teams and players.

A set of functions to access National Football League play-by-play data from <https://www.nfl.com/>.

This package allows data driven sports enthusiasts to use the NFL JSON API data to perform detailed analysis at game, season, and player levels. The functions within this package help parse and clean the data from NFL.com for R users. This package was built to enhance advanced sports analytics research specifically for American football with the hopes of developing metrics and insights that could potentially be useful for professional NFL teams as well as the public.

An easy package for scraping and processing Australia Rules Football (AFL) data. 'fitzRoy' provides a range of functions for accessing publicly available data from 'AFL Tables' <https://afltables.com/afl/afl_index.html>, 'Footy Wire' <https://www.footywire.com> and 'The Squiggle' <https://squiggle.com.au>. Further functions allow for easy processing, cleaning and transformation of this data into formats that can be used for analysis.

all things hockey

This package is used to pull StatsBomb data directly from the API. Currently, this is only supported on Windows computers since pulling functions use parallel computing.

Provides tools to visualise x,y-coordinates of soccer players and event data (e.g. passes, shots). Uses ggplot to draw soccer pitch and overplot expected goal maps, pass maps, average player positions, player heatmaps, individual player paths, player flow fields, and more.

A partir de los ficheros proporcionados por OPTA en formato XML permite elaborar anA!lisis y visualizaciones de grafos de pases, radar de pases, corners, tiros y mapas de calor de desde donde pasan y adonde pasan

Football / soccer related visualisations and analysis

Soccer/football analytics blog posts & data viz from the World Cup, Premier League, Copa America, and beyond. Using ggplot2, ggsoccer, & more. (Est. June 2018) ****Please look at the README for best version of the code!****

An R package for working with College Football Data. It is an R API wrapper around <https://collegefootballdata.com/> made available by the cfbscrapR team. It provides users the capability to access a plethora of endpoints, and supplement that data with additional information (Expected Points Added/Win Probability added).

Code to scrape play-by-play data from the XFL website and reshape data into more useful columns for public analysis

Main use case is to collect ESPN QBR for NFL and college football. Alternative functions include getting NFL standings and scraping NFL season-level stats.

Scrapes NCAA stats for most college sports from stats.ncaa.org

Provides numerous utilities for acquiring and analyzing baseball data from online sources such as 'Baseball Reference' <https://www.baseball-reference.com/>, 'FanGraphs' <https://www.fangraphs.com/>, and the 'MLB Stats' API <https://www.mlb.com/>.

Multi-core processing of data from Major League Baseball Advanced Media <http://gd2.mlb.com/components/game/mlb/>. Additional tools to parallel process large data sets and write them to a database.

Draw Major Leagure Stadiums in the ggplot2 framework

There are two primary purposes this package serves: 1) it facilitates the computation of openWAR, a fully open-source implementation of Wins Above Replacement (WAR) that could serve as a reference implementation for the sabermetric community; and 2) it downloads raw XML files from the MLBAM GameDay web application and processes them into play-by-play data in a tabular format. This play-by-play information is similar in spirit, though not in syntax, to play-by-play data made available by Retrosheet. Those interested in the modeling choices that we have made in our computation of openWAR should consult our JQAS or arXiv paper on that subject. This implementation of openWAR includes functions for constructing interval estimates of WAR for each player, as well as comparing openWAR point estimates to those of Baseball- Reference.com's rWAR.

With 'pitchRx', one can easily obtain Major League Baseball Advanced Media's 'Gameday' data (as well as store it in a remote database). The 'Gameday' website hosts a wealth of data in XML format, but perhaps most interesting is 'pitchfx'. Among other things, 'pitchfx' data can be used to recreate a baseball's flight path from a pitcher's hand to home plate. With pitchRx, one can easily create animations and interactive 3D 'scatterplots' of the baseball's flight path. 'pitchfx' data is also commonly used to generate a static plot of baseball locations at the moment they cross home plate. These plots, sometimes called strike-zone plots, can also refer to a plot of event probabilities over the same region. 'pitchRx' provides an easy and robust way to generate strike-zone plots using the 'ggplot2' package.

Building an SQL database of baseball play-by-play data from Retrosheet requires an ETL process and special tools. This package automates and streamlines that process.

An R package for working with NCAA Men's Basketball Play-by-Play Data. This package allows users to scrape play-by-play data into a tidy format, create assist networks games of their choosing, and examine in-game win probability charts.

This package gives users the ability to work with NCAA Basketball data in a clean and detailed manner. The functions included can retrieve and manipulate NCAA play-by-play data, giving users a variety of ways to find insights about their favorite players and teams. An especially important feature is the ability to report who is on the court at each event in the play-by-play, opening up many possible areas of analysis.

NBA data tools for R

Provides simple functions for accessing data/tables on <http://www.basketball-reference.com>.

`wncaahoopR` is an R package for working with women's NCAA Basketball play-by-play (and other) data, primarily by scraping from ESPN, but in a different way than the `ncaahoopR` package from Luke Benz (lbenz730). This package has a single function for scraping data and then makes use of the resulting `pbp` object within R to produce charts similar to those in `ncaahoopR`.

Tools for analyzing performances of cricketers based on stats in ESPN Cricinfo Statsguru. The toolset can be used for analysis of Tests,ODIs and Twenty20 matches of both batsmen and bowlers. The package can also be used to analyze team performances.

Analyzing performances of cricketers and cricket teams based on 'yaml' match data from Cricsheet <https://cricsheet.org/>.

Data on international and other major cricket matches from ESPNCricinfo <https://www.espncricinfo.com> and Cricsheet <https://cricsheet.org>. This package provides some functions to download the data into tibbles ready for analysis.

The "elite" package allows users to easily scrape data from EliteProspects in a [fairly] tidy manner.

Retrieves and processes the data exposed by the open 'NHL' API. This includes information on players, teams, games, tournaments, drafts, standings, schedules and other endpoints. A lower-level interface to access the data via URLs directly is also provided.

Add game events to a database file to use for statistical analysis of hockey games. This means we only call the 'NHL' API once for each game we want to add. We will have very fast retrieval of data once games have been added since the data is stored locally. We use the API located at <https://statsapi.web.nhl.com/api/v1/teams> with supplemental data from <https://www.nhl.com/scores/>. Other endpoints can be found at <https://gitlab.com/dword4/nhlapi>.

This package allows data driven sports enthusiasts to easily access event data for soccer games from ESPN. The functions within this package help find, parse, and clean the commentary data from ESPN for R users.

R package that calls various free soccer APIs

This repository includes all the code and data used for developing the expected league points above replacement for soccer as described in "Positional Value in Soccer: Expected League Points Added above Replacement"

Soccer club results data from 1871-2020.

The 'ggplot2' package provides a powerful set of tools for visualising and investigating data. The 'ggsoccer' package provides a set of functions for elegantly displaying and exploring soccer event data with 'ggplot2'. Providing extensible layers and themes, it is designed to work smoothly with a variety of popular sports data providers.

An tidyverse-friendly package for fetching data from football-data.co.uk for soccer modelling.

A collection of models and tools for soccer analytics.

A package with various functions that help people working with OPTA and ChyronHego data.

nwslR is an R package that contains datasets and analysis functionality for the National Women’s Soccer League (NWSL). Founded in 2013, the NWSL is the United States’ top professional women’s soccer league, featuring players from all over the world.

Provides tools to retrieve understat <https://understat.com/> data in a tidy format.

Last two minute report data from the NBA

The goalmodel package let you model the number of goals scored in sport games. The models are primarily aimed at modelling and predicting football (soccer) scores, but could also be applicable for similar sports, such as hockey and handball.

This packages allows you to create 2D animations of soccer tracking data in addition to do some player calculations and team possession stats.

Use this package to scrap Test Matches, One Day Internationals, Twenty-20 Internationals data of a player from ESPNCricinfo's Statsguru (<http://stats.espncricinfo.com/ci/engine/stats/index.html>) and then visualize their batting, bowling and fielding performances in the form of charts and graphs.

A utility to quickly obtain clean and tidy men's basketball play by play data. Provides functions to access live play by play and box score data from ESPN<https://www.espn.com> with shot locations when available. It is also a full NBA Stats API<https://www.nba.com/stats/> wrapper. It is also a scraping and aggregating interface for Ken Pomeroy's men's college basketball statistics website<https://kenpom.com>. It provides users with an active subscription the capability to scrape the website tables and analyze the data for themselves.

Quick calculations of common travel and schedule related information for Basketball teams (currently only NBA teams) and various different seasons (since 1947). The retrieved data includes distance travelled between games, time zone for each game, time shifts betwen games, number of rest days between games, estimated flight duration, etc. Plotting options enable users to visualize maps of flight paths between games. This package uses the game_logs() function from the really useful nbastatR package written by Bresler. A (2020) <https://github.com/abresler/nbastatR> to query seasonn schedule and player stats from publicly available sources.

This package provides functions to easily download and manipulate data from super netball matches.

Running a deep learning model to predict netball matches

NCAA Womens version of bigballR: This package gives users the ability to work with NCAA Basketball data in a clean and detailed manner. The functions included can retrieve and manipulate NCAA play-by-play data, giving users a variety of ways to find insights about their favorite players and teams. An especially important feature is the ability to report who is on the court at each event in the play-by-play, opening up many possible areas of analysis.

R package to do the equivalent work of Kloppy for python. General helpers and models for football analytics in R.

A set of functions to simulate National Football League seasons including the sophisticated tie-breaking procedures.

A utility for working with women's basketball data. A scraping and aggregating interface for the WNBA Stats API <https://stats.wnba.com/> and ESPN's <https://www.espn.com> women's college basketball and WNBA statistics. It provides users with the capability to access the game play-by-plays, box scores, standings and results to analyze the data for themselves.

An R package for working with NCAA Men's Basketball play-by-play data

Create scaled 'ggplot' representations of playing surfaces. Playing surfaces are drawn pursuant to rule-book specifications. This package should be used as a baseline plot for displaying any type of tracking data.

A minimal package for downloading data from 'GitHub' repositories of the 'nflverse' project.

ggshakeR is an analysis and visualization R package that works with publically available soccer data. The datasets (for now) include FBref, StatsBomb, and understat.

A utility to scrape and load play-by-play data and statistics from the Professional Women's Hockey League <https://www.thepwhl.com/>, formerly known as the Premier Hockey Federation (PHF) or National Women's Hockey League (NWHL). Additionally, allows access to the National Hockey League's stats API <https://www.nhl.com/>.

Allow users to obtain clean and tidy football (soccer) game, team and player data. Data is collected from a number of popular sites, including 'FBref', transfer and valuations data from 'Transfermarkt'<https://www.transfermarkt.com/> and shooting location and other match stats data from 'Understat'<https://understat.com/>. It gives users the ability to access data more efficiently, rather than having to export data tables to files before being able to complete their analysis.

A set of functions to enable users to extract chess game data from popular chess sites, including 'Lichess'<https://lichess.org/> and 'Chess.com' <https://www.chess.com/> and then perform analysis on that game data.

A set of functions to visualize National Football League analysis in 'ggplot2' plots and 'gt' tables.

This package currently provides data from the 2022 Beijing Olympics from NBC's API. The name of this package comes from the Olympic Motto: "Faster, Higher, Stronger - Together". This package is still a work in progress and new functions will hopefully be added soon! This package will likely be updated to include Paris 2024 Data when that event comes around.

Obtain Formula 1 data via the 'Jolpica API' <https://jolpi.ca> and the unofficial API <https://www.formula1.com/en/timing/f1-live> via the 'fastf1' 'Python' library <https://docs.fastf1.dev/>.

What the package does (one paragraph).

Allow users to obtain basketball statistics for the Australian basketball league 'NBL'<https://nbl.com.au/>. Stats include play-by-play, shooting locations, results and box scores for teams and players.

A set of functions to access National Football League play-by-play data from <https://www.nfl.com/>.

This package allows data driven sports enthusiasts to use the NFL JSON API data to perform detailed analysis at game, season, and player levels. The functions within this package help parse and clean the data from NFL.com for R users. This package was built to enhance advanced sports analytics research specifically for American football with the hopes of developing metrics and insights that could potentially be useful for professional NFL teams as well as the public.

An easy package for scraping and processing Australia Rules Football (AFL) data. 'fitzRoy' provides a range of functions for accessing publicly available data from 'AFL Tables' <https://afltables.com/afl/afl_index.html>, 'Footy Wire' <https://www.footywire.com> and 'The Squiggle' <https://squiggle.com.au>. Further functions allow for easy processing, cleaning and transformation of this data into formats that can be used for analysis.

all things hockey

This package is used to pull StatsBomb data directly from the API. Currently, this is only supported on Windows computers since pulling functions use parallel computing.

Provides tools to visualise x,y-coordinates of soccer players and event data (e.g. passes, shots). Uses ggplot to draw soccer pitch and overplot expected goal maps, pass maps, average player positions, player heatmaps, individual player paths, player flow fields, and more.

A partir de los ficheros proporcionados por OPTA en formato XML permite elaborar anA!lisis y visualizaciones de grafos de pases, radar de pases, corners, tiros y mapas de calor de desde donde pasan y adonde pasan

Football / soccer related visualisations and analysis

Soccer/football analytics blog posts & data viz from the World Cup, Premier League, Copa America, and beyond. Using ggplot2, ggsoccer, & more. (Est. June 2018) ****Please look at the README for best version of the code!****

An R package for working with College Football Data. It is an R API wrapper around <https://collegefootballdata.com/> made available by the cfbscrapR team. It provides users the capability to access a plethora of endpoints, and supplement that data with additional information (Expected Points Added/Win Probability added).

Code to scrape play-by-play data from the XFL website and reshape data into more useful columns for public analysis

Main use case is to collect ESPN QBR for NFL and college football. Alternative functions include getting NFL standings and scraping NFL season-level stats.

Scrapes NCAA stats for most college sports from stats.ncaa.org

Provides numerous utilities for acquiring and analyzing baseball data from online sources such as 'Baseball Reference' <https://www.baseball-reference.com/>, 'FanGraphs' <https://www.fangraphs.com/>, and the 'MLB Stats' API <https://www.mlb.com/>.

Multi-core processing of data from Major League Baseball Advanced Media <http://gd2.mlb.com/components/game/mlb/>. Additional tools to parallel process large data sets and write them to a database.

Draw Major Leagure Stadiums in the ggplot2 framework

There are two primary purposes this package serves: 1) it facilitates the computation of openWAR, a fully open-source implementation of Wins Above Replacement (WAR) that could serve as a reference implementation for the sabermetric community; and 2) it downloads raw XML files from the MLBAM GameDay web application and processes them into play-by-play data in a tabular format. This play-by-play information is similar in spirit, though not in syntax, to play-by-play data made available by Retrosheet. Those interested in the modeling choices that we have made in our computation of openWAR should consult our JQAS or arXiv paper on that subject. This implementation of openWAR includes functions for constructing interval estimates of WAR for each player, as well as comparing openWAR point estimates to those of Baseball- Reference.com's rWAR.

With 'pitchRx', one can easily obtain Major League Baseball Advanced Media's 'Gameday' data (as well as store it in a remote database). The 'Gameday' website hosts a wealth of data in XML format, but perhaps most interesting is 'pitchfx'. Among other things, 'pitchfx' data can be used to recreate a baseball's flight path from a pitcher's hand to home plate. With pitchRx, one can easily create animations and interactive 3D 'scatterplots' of the baseball's flight path. 'pitchfx' data is also commonly used to generate a static plot of baseball locations at the moment they cross home plate. These plots, sometimes called strike-zone plots, can also refer to a plot of event probabilities over the same region. 'pitchRx' provides an easy and robust way to generate strike-zone plots using the 'ggplot2' package.

Building an SQL database of baseball play-by-play data from Retrosheet requires an ETL process and special tools. This package automates and streamlines that process.

An R package for working with NCAA Men's Basketball Play-by-Play Data. This package allows users to scrape play-by-play data into a tidy format, create assist networks games of their choosing, and examine in-game win probability charts.

This package gives users the ability to work with NCAA Basketball data in a clean and detailed manner. The functions included can retrieve and manipulate NCAA play-by-play data, giving users a variety of ways to find insights about their favorite players and teams. An especially important feature is the ability to report who is on the court at each event in the play-by-play, opening up many possible areas of analysis.

NBA data tools for R

Provides simple functions for accessing data/tables on <http://www.basketball-reference.com>.

`wncaahoopR` is an R package for working with women's NCAA Basketball play-by-play (and other) data, primarily by scraping from ESPN, but in a different way than the `ncaahoopR` package from Luke Benz (lbenz730). This package has a single function for scraping data and then makes use of the resulting `pbp` object within R to produce charts similar to those in `ncaahoopR`.

Tools for analyzing performances of cricketers based on stats in ESPN Cricinfo Statsguru. The toolset can be used for analysis of Tests,ODIs and Twenty20 matches of both batsmen and bowlers. The package can also be used to analyze team performances.

Analyzing performances of cricketers and cricket teams based on 'yaml' match data from Cricsheet <https://cricsheet.org/>.

Data on international and other major cricket matches from ESPNCricinfo <https://www.espncricinfo.com> and Cricsheet <https://cricsheet.org>. This package provides some functions to download the data into tibbles ready for analysis.

The "elite" package allows users to easily scrape data from EliteProspects in a [fairly] tidy manner.

Retrieves and processes the data exposed by the open 'NHL' API. This includes information on players, teams, games, tournaments, drafts, standings, schedules and other endpoints. A lower-level interface to access the data via URLs directly is also provided.

Add game events to a database file to use for statistical analysis of hockey games. This means we only call the 'NHL' API once for each game we want to add. We will have very fast retrieval of data once games have been added since the data is stored locally. We use the API located at <https://statsapi.web.nhl.com/api/v1/teams> with supplemental data from <https://www.nhl.com/scores/>. Other endpoints can be found at <https://gitlab.com/dword4/nhlapi>.

This package allows data driven sports enthusiasts to easily access event data for soccer games from ESPN. The functions within this package help find, parse, and clean the commentary data from ESPN for R users.

R package that calls various free soccer APIs

This repository includes all the code and data used for developing the expected league points above replacement for soccer as described in "Positional Value in Soccer: Expected League Points Added above Replacement"

Soccer club results data from 1871-2020.

The 'ggplot2' package provides a powerful set of tools for visualising and investigating data. The 'ggsoccer' package provides a set of functions for elegantly displaying and exploring soccer event data with 'ggplot2'. Providing extensible layers and themes, it is designed to work smoothly with a variety of popular sports data providers.

An tidyverse-friendly package for fetching data from football-data.co.uk for soccer modelling.

A collection of models and tools for soccer analytics.

A package with various functions that help people working with OPTA and ChyronHego data.

nwslR is an R package that contains datasets and analysis functionality for the National Women’s Soccer League (NWSL). Founded in 2013, the NWSL is the United States’ top professional women’s soccer league, featuring players from all over the world.

Provides tools to retrieve understat <https://understat.com/> data in a tidy format.

Last two minute report data from the NBA

The goalmodel package let you model the number of goals scored in sport games. The models are primarily aimed at modelling and predicting football (soccer) scores, but could also be applicable for similar sports, such as hockey and handball.

This packages allows you to create 2D animations of soccer tracking data in addition to do some player calculations and team possession stats.

Use this package to scrap Test Matches, One Day Internationals, Twenty-20 Internationals data of a player from ESPNCricinfo's Statsguru (<http://stats.espncricinfo.com/ci/engine/stats/index.html>) and then visualize their batting, bowling and fielding performances in the form of charts and graphs.

A utility to quickly obtain clean and tidy men's basketball play by play data. Provides functions to access live play by play and box score data from ESPN<https://www.espn.com> with shot locations when available. It is also a full NBA Stats API<https://www.nba.com/stats/> wrapper. It is also a scraping and aggregating interface for Ken Pomeroy's men's college basketball statistics website<https://kenpom.com>. It provides users with an active subscription the capability to scrape the website tables and analyze the data for themselves.

Quick calculations of common travel and schedule related information for Basketball teams (currently only NBA teams) and various different seasons (since 1947). The retrieved data includes distance travelled between games, time zone for each game, time shifts betwen games, number of rest days between games, estimated flight duration, etc. Plotting options enable users to visualize maps of flight paths between games. This package uses the game_logs() function from the really useful nbastatR package written by Bresler. A (2020) <https://github.com/abresler/nbastatR> to query seasonn schedule and player stats from publicly available sources.

This package provides functions to easily download and manipulate data from super netball matches.

Running a deep learning model to predict netball matches

NCAA Womens version of bigballR: This package gives users the ability to work with NCAA Basketball data in a clean and detailed manner. The functions included can retrieve and manipulate NCAA play-by-play data, giving users a variety of ways to find insights about their favorite players and teams. An especially important feature is the ability to report who is on the court at each event in the play-by-play, opening up many possible areas of analysis.

R package to do the equivalent work of Kloppy for python. General helpers and models for football analytics in R.

A set of functions to simulate National Football League seasons including the sophisticated tie-breaking procedures.

A utility for working with women's basketball data. A scraping and aggregating interface for the WNBA Stats API <https://stats.wnba.com/> and ESPN's <https://www.espn.com> women's college basketball and WNBA statistics. It provides users with the capability to access the game play-by-plays, box scores, standings and results to analyze the data for themselves.

An R package for working with NCAA Men's Basketball play-by-play data

Create scaled 'ggplot' representations of playing surfaces. Playing surfaces are drawn pursuant to rule-book specifications. This package should be used as a baseline plot for displaying any type of tracking data.

A minimal package for downloading data from 'GitHub' repositories of the 'nflverse' project.

ggshakeR is an analysis and visualization R package that works with publically available soccer data. The datasets (for now) include FBref, StatsBomb, and understat.

A utility to scrape and load play-by-play data and statistics from the Professional Women's Hockey League <https://www.thepwhl.com/>, formerly known as the Premier Hockey Federation (PHF) or National Women's Hockey League (NWHL). Additionally, allows access to the National Hockey League's stats API <https://www.nhl.com/>.

Allow users to obtain clean and tidy football (soccer) game, team and player data. Data is collected from a number of popular sites, including 'FBref', transfer and valuations data from 'Transfermarkt'<https://www.transfermarkt.com/> and shooting location and other match stats data from 'Understat'<https://understat.com/>. It gives users the ability to access data more efficiently, rather than having to export data tables to files before being able to complete their analysis.

A set of functions to enable users to extract chess game data from popular chess sites, including 'Lichess'<https://lichess.org/> and 'Chess.com' <https://www.chess.com/> and then perform analysis on that game data.

A set of functions to visualize National Football League analysis in 'ggplot2' plots and 'gt' tables.

This package currently provides data from the 2022 Beijing Olympics from NBC's API. The name of this package comes from the Olympic Motto: "Faster, Higher, Stronger - Together". This package is still a work in progress and new functions will hopefully be added soon! This package will likely be updated to include Paris 2024 Data when that event comes around.

Obtain Formula 1 data via the 'Jolpica API' <https://jolpi.ca> and the unofficial API <https://www.formula1.com/en/timing/f1-live> via the 'fastf1' 'Python' library <https://docs.fastf1.dev/>.

What the package does (one paragraph).

Allow users to obtain basketball statistics for the Australian basketball league 'NBL'<https://nbl.com.au/>. Stats include play-by-play, shooting locations, results and box scores for teams and players.

A set of functions to access National Football League play-by-play data from <https://www.nfl.com/>.

This package allows data driven sports enthusiasts to use the NFL JSON API data to perform detailed analysis at game, season, and player levels. The functions within this package help parse and clean the data from NFL.com for R users. This package was built to enhance advanced sports analytics research specifically for American football with the hopes of developing metrics and insights that could potentially be useful for professional NFL teams as well as the public.

An easy package for scraping and processing Australia Rules Football (AFL) data. 'fitzRoy' provides a range of functions for accessing publicly available data from 'AFL Tables' <https://afltables.com/afl/afl_index.html>, 'Footy Wire' <https://www.footywire.com> and 'The Squiggle' <https://squiggle.com.au>. Further functions allow for easy processing, cleaning and transformation of this data into formats that can be used for analysis.

all things hockey

This package is used to pull StatsBomb data directly from the API. Currently, this is only supported on Windows computers since pulling functions use parallel computing.

Provides tools to visualise x,y-coordinates of soccer players and event data (e.g. passes, shots). Uses ggplot to draw soccer pitch and overplot expected goal maps, pass maps, average player positions, player heatmaps, individual player paths, player flow fields, and more.

A partir de los ficheros proporcionados por OPTA en formato XML permite elaborar anA!lisis y visualizaciones de grafos de pases, radar de pases, corners, tiros y mapas de calor de desde donde pasan y adonde pasan

Football / soccer related visualisations and analysis

Soccer/football analytics blog posts & data viz from the World Cup, Premier League, Copa America, and beyond. Using ggplot2, ggsoccer, & more. (Est. June 2018) ****Please look at the README for best version of the code!****

An R package for working with College Football Data. It is an R API wrapper around <https://collegefootballdata.com/> made available by the cfbscrapR team. It provides users the capability to access a plethora of endpoints, and supplement that data with additional information (Expected Points Added/Win Probability added).

Code to scrape play-by-play data from the XFL website and reshape data into more useful columns for public analysis

Main use case is to collect ESPN QBR for NFL and college football. Alternative functions include getting NFL standings and scraping NFL season-level stats.

Scrapes NCAA stats for most college sports from stats.ncaa.org

Provides numerous utilities for acquiring and analyzing baseball data from online sources such as 'Baseball Reference' <https://www.baseball-reference.com/>, 'FanGraphs' <https://www.fangraphs.com/>, and the 'MLB Stats' API <https://www.mlb.com/>.

Multi-core processing of data from Major League Baseball Advanced Media <http://gd2.mlb.com/components/game/mlb/>. Additional tools to parallel process large data sets and write them to a database.

Draw Major Leagure Stadiums in the ggplot2 framework

There are two primary purposes this package serves: 1) it facilitates the computation of openWAR, a fully open-source implementation of Wins Above Replacement (WAR) that could serve as a reference implementation for the sabermetric community; and 2) it downloads raw XML files from the MLBAM GameDay web application and processes them into play-by-play data in a tabular format. This play-by-play information is similar in spirit, though not in syntax, to play-by-play data made available by Retrosheet. Those interested in the modeling choices that we have made in our computation of openWAR should consult our JQAS or arXiv paper on that subject. This implementation of openWAR includes functions for constructing interval estimates of WAR for each player, as well as comparing openWAR point estimates to those of Baseball- Reference.com's rWAR.

With 'pitchRx', one can easily obtain Major League Baseball Advanced Media's 'Gameday' data (as well as store it in a remote database). The 'Gameday' website hosts a wealth of data in XML format, but perhaps most interesting is 'pitchfx'. Among other things, 'pitchfx' data can be used to recreate a baseball's flight path from a pitcher's hand to home plate. With pitchRx, one can easily create animations and interactive 3D 'scatterplots' of the baseball's flight path. 'pitchfx' data is also commonly used to generate a static plot of baseball locations at the moment they cross home plate. These plots, sometimes called strike-zone plots, can also refer to a plot of event probabilities over the same region. 'pitchRx' provides an easy and robust way to generate strike-zone plots using the 'ggplot2' package.

Building an SQL database of baseball play-by-play data from Retrosheet requires an ETL process and special tools. This package automates and streamlines that process.

An R package for working with NCAA Men's Basketball Play-by-Play Data. This package allows users to scrape play-by-play data into a tidy format, create assist networks games of their choosing, and examine in-game win probability charts.

This package gives users the ability to work with NCAA Basketball data in a clean and detailed manner. The functions included can retrieve and manipulate NCAA play-by-play data, giving users a variety of ways to find insights about their favorite players and teams. An especially important feature is the ability to report who is on the court at each event in the play-by-play, opening up many possible areas of analysis.

NBA data tools for R

Provides simple functions for accessing data/tables on <http://www.basketball-reference.com>.

`wncaahoopR` is an R package for working with women's NCAA Basketball play-by-play (and other) data, primarily by scraping from ESPN, but in a different way than the `ncaahoopR` package from Luke Benz (lbenz730). This package has a single function for scraping data and then makes use of the resulting `pbp` object within R to produce charts similar to those in `ncaahoopR`.

Tools for analyzing performances of cricketers based on stats in ESPN Cricinfo Statsguru. The toolset can be used for analysis of Tests,ODIs and Twenty20 matches of both batsmen and bowlers. The package can also be used to analyze team performances.

Analyzing performances of cricketers and cricket teams based on 'yaml' match data from Cricsheet <https://cricsheet.org/>.

Data on international and other major cricket matches from ESPNCricinfo <https://www.espncricinfo.com> and Cricsheet <https://cricsheet.org>. This package provides some functions to download the data into tibbles ready for analysis.

The "elite" package allows users to easily scrape data from EliteProspects in a [fairly] tidy manner.