Python API wrapper for stats.nba.com with a focus on NBA and WNBA applications

API interface for stats.nba.com

A Python package to scrape the NBA api and return a play by play file

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`.

python package to clean up ETL functions using nba_scraper output as input

Last two minute report data from the NBA

Repository which contains various scripts and work with various basketball statistics

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.

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.

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 multi-entity Transformer for multi-agent spatiotemporal modeling.

A look-ahead multi-entity Transformer for modeling coordinated agents.

Adding players on court to play-by-play data

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.

Plot functions and example of data extraction for short charts from Euroleague basketball data

Data analytics and modelling on basketball games

Gambling Odds To Outcome probabilities Conversion (goto_conversion)

A collection of open-source sports biomechanics datasets collected by MLSE's Sport Performance Lab.

Python API wrapper for stats.nba.com with a focus on NBA and WNBA applications

API interface for stats.nba.com

A Python package to scrape the NBA api and return a play by play file

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`.

python package to clean up ETL functions using nba_scraper output as input

Last two minute report data from the NBA

Repository which contains various scripts and work with various basketball statistics

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.

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.

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 multi-entity Transformer for multi-agent spatiotemporal modeling.

A look-ahead multi-entity Transformer for modeling coordinated agents.

Adding players on court to play-by-play data

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.

Plot functions and example of data extraction for short charts from Euroleague basketball data

Data analytics and modelling on basketball games

Gambling Odds To Outcome probabilities Conversion (goto_conversion)

A collection of open-source sports biomechanics datasets collected by MLSE's Sport Performance Lab.

Python API wrapper for stats.nba.com with a focus on NBA and WNBA applications

API interface for stats.nba.com

A Python package to scrape the NBA api and return a play by play file

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`.

python package to clean up ETL functions using nba_scraper output as input

Last two minute report data from the NBA

Repository which contains various scripts and work with various basketball statistics

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.

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.

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 multi-entity Transformer for multi-agent spatiotemporal modeling.

A look-ahead multi-entity Transformer for modeling coordinated agents.

Adding players on court to play-by-play data

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.

Plot functions and example of data extraction for short charts from Euroleague basketball data

Data analytics and modelling on basketball games

Gambling Odds To Outcome probabilities Conversion (goto_conversion)

A collection of open-source sports biomechanics datasets collected by MLSE's Sport Performance Lab.

Python API wrapper for stats.nba.com with a focus on NBA and WNBA applications

API interface for stats.nba.com

A Python package to scrape the NBA api and return a play by play file

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`.

python package to clean up ETL functions using nba_scraper output as input

Last two minute report data from the NBA

Repository which contains various scripts and work with various basketball statistics

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.

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.

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 multi-entity Transformer for multi-agent spatiotemporal modeling.

A look-ahead multi-entity Transformer for modeling coordinated agents.

Adding players on court to play-by-play data

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.

Plot functions and example of data extraction for short charts from Euroleague basketball data

Data analytics and modelling on basketball games

Gambling Odds To Outcome probabilities Conversion (goto_conversion)

A collection of open-source sports biomechanics datasets collected by MLSE's Sport Performance Lab.

Python API wrapper for stats.nba.com with a focus on NBA and WNBA applications

API interface for stats.nba.com

A Python package to scrape the NBA api and return a play by play file

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`.

python package to clean up ETL functions using nba_scraper output as input

Last two minute report data from the NBA

Repository which contains various scripts and work with various basketball statistics

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.

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.

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 multi-entity Transformer for multi-agent spatiotemporal modeling.

A look-ahead multi-entity Transformer for modeling coordinated agents.

Adding players on court to play-by-play data

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.

Plot functions and example of data extraction for short charts from Euroleague basketball data

Data analytics and modelling on basketball games

Gambling Odds To Outcome probabilities Conversion (goto_conversion)

A collection of open-source sports biomechanics datasets collected by MLSE's Sport Performance Lab.