A package to help pull information from the transfermarkt website

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.

easily stream StatsBomb data into Python

An extendable Statsbomb API wrapper for data-pipelines

A Python package to parse StatsBomb JSON data to CSV

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

Convert soccer event stream data to the SPADL format and value on-the-ball player actions

Football pitch plotting library for matplotlib

Standardizing soccer tracking- and event data

Calculate the packing rate for a given pass in football (soccer)

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!****

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.

Laurie's code for Metrica tracking data.

Bayesian hierarchical models for football

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.

Train and analyse xG models on soccer event stream data

A Python package for data visualization for football analytics

Metrica Sports sample tracking and event data

Last row tracking data and code

Synchronise event and tracking data using dynamic programming

Data driven tactical and video analysis of soccer games

Free football data from StatsBomb

Spark Tools to work with Kloppy

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

A repository with scraping code and soccer dataset from understat.com.

Provides numerous functions for acquiring and analyzing major league soccer data. Data is acquired from various online resources and is mold into a tidy format to analyze in R.

A package for soccer modelling

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 high-level framework for sports data analysis

A Python library that simplifies working with video from soccer matches.

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.

Package for scraping soccer data from a variety of sources.

Programmatically interact with the American Soccer Analysis API

A collection of wrappers over soccer data from various websites / APIs.

Library from http://pena.lt/y/blog for scraping and modelling football (soccer) data

A Python plotting library for visualization of basketball data.

A package to help pull information from the transfermarkt website

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.

easily stream StatsBomb data into Python

An extendable Statsbomb API wrapper for data-pipelines

A Python package to parse StatsBomb JSON data to CSV

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

Convert soccer event stream data to the SPADL format and value on-the-ball player actions

Football pitch plotting library for matplotlib

Standardizing soccer tracking- and event data

Calculate the packing rate for a given pass in football (soccer)

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!****

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.

Laurie's code for Metrica tracking data.

Bayesian hierarchical models for football

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.

Train and analyse xG models on soccer event stream data

A Python package for data visualization for football analytics

Metrica Sports sample tracking and event data

Last row tracking data and code

Synchronise event and tracking data using dynamic programming

Data driven tactical and video analysis of soccer games

Free football data from StatsBomb

Spark Tools to work with Kloppy

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

A repository with scraping code and soccer dataset from understat.com.

Provides numerous functions for acquiring and analyzing major league soccer data. Data is acquired from various online resources and is mold into a tidy format to analyze in R.

A package for soccer modelling

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 high-level framework for sports data analysis

A Python library that simplifies working with video from soccer matches.

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.

Package for scraping soccer data from a variety of sources.

Programmatically interact with the American Soccer Analysis API

A collection of wrappers over soccer data from various websites / APIs.

Library from http://pena.lt/y/blog for scraping and modelling football (soccer) data

A Python plotting library for visualization of basketball data.

A package to help pull information from the transfermarkt website

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.

easily stream StatsBomb data into Python

An extendable Statsbomb API wrapper for data-pipelines

A Python package to parse StatsBomb JSON data to CSV

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

Convert soccer event stream data to the SPADL format and value on-the-ball player actions

Football pitch plotting library for matplotlib

Standardizing soccer tracking- and event data

Calculate the packing rate for a given pass in football (soccer)

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!****

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.

Laurie's code for Metrica tracking data.

Bayesian hierarchical models for football

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.

Train and analyse xG models on soccer event stream data

A Python package for data visualization for football analytics

Metrica Sports sample tracking and event data

Last row tracking data and code

Synchronise event and tracking data using dynamic programming

Data driven tactical and video analysis of soccer games

Free football data from StatsBomb

Spark Tools to work with Kloppy

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

A repository with scraping code and soccer dataset from understat.com.

Provides numerous functions for acquiring and analyzing major league soccer data. Data is acquired from various online resources and is mold into a tidy format to analyze in R.

A package for soccer modelling

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 high-level framework for sports data analysis

A Python library that simplifies working with video from soccer matches.

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.

Package for scraping soccer data from a variety of sources.

Programmatically interact with the American Soccer Analysis API

A collection of wrappers over soccer data from various websites / APIs.

Library from http://pena.lt/y/blog for scraping and modelling football (soccer) data

A Python plotting library for visualization of basketball data.

A package to help pull information from the transfermarkt website

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.

easily stream StatsBomb data into Python

An extendable Statsbomb API wrapper for data-pipelines

A Python package to parse StatsBomb JSON data to CSV

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

Convert soccer event stream data to the SPADL format and value on-the-ball player actions

Football pitch plotting library for matplotlib

Standardizing soccer tracking- and event data

Calculate the packing rate for a given pass in football (soccer)

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!****

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.

Laurie's code for Metrica tracking data.

Bayesian hierarchical models for football

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.

Train and analyse xG models on soccer event stream data

A Python package for data visualization for football analytics

Metrica Sports sample tracking and event data

Last row tracking data and code

Synchronise event and tracking data using dynamic programming

Data driven tactical and video analysis of soccer games

Free football data from StatsBomb

Spark Tools to work with Kloppy

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

A repository with scraping code and soccer dataset from understat.com.

Provides numerous functions for acquiring and analyzing major league soccer data. Data is acquired from various online resources and is mold into a tidy format to analyze in R.

A package for soccer modelling

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 high-level framework for sports data analysis

A Python library that simplifies working with video from soccer matches.

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.

Package for scraping soccer data from a variety of sources.

Programmatically interact with the American Soccer Analysis API

A collection of wrappers over soccer data from various websites / APIs.

Library from http://pena.lt/y/blog for scraping and modelling football (soccer) data

A Python plotting library for visualization of basketball data.

A package to help pull information from the transfermarkt website

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.

easily stream StatsBomb data into Python

An extendable Statsbomb API wrapper for data-pipelines

A Python package to parse StatsBomb JSON data to CSV

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

Convert soccer event stream data to the SPADL format and value on-the-ball player actions

Football pitch plotting library for matplotlib

Standardizing soccer tracking- and event data

Calculate the packing rate for a given pass in football (soccer)

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!****

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.

Laurie's code for Metrica tracking data.

Bayesian hierarchical models for football

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.

Train and analyse xG models on soccer event stream data

A Python package for data visualization for football analytics

Metrica Sports sample tracking and event data

Last row tracking data and code

Synchronise event and tracking data using dynamic programming

Data driven tactical and video analysis of soccer games

Free football data from StatsBomb

Spark Tools to work with Kloppy

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

A repository with scraping code and soccer dataset from understat.com.

Provides numerous functions for acquiring and analyzing major league soccer data. Data is acquired from various online resources and is mold into a tidy format to analyze in R.

A package for soccer modelling

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 high-level framework for sports data analysis

A Python library that simplifies working with video from soccer matches.

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.

Package for scraping soccer data from a variety of sources.

Programmatically interact with the American Soccer Analysis API

A collection of wrappers over soccer data from various websites / APIs.

Library from http://pena.lt/y/blog for scraping and modelling football (soccer) data

A Python plotting library for visualization of basketball data.