all things hockey

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

Baseball data and analysis in Python

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/>.

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.

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.

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`.

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"

A collection of models and tools for soccer analytics.

Laurie's code for Metrica tracking data.

Bayesian hierarchical models for football

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

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.

Repository which contains various scripts and work with various basketball statistics

Train and analyse xG models on soccer event stream data

Synchronise event and tracking data using dynamic programming

Data driven tactical and video analysis of soccer games

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.

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.

A package for soccer modelling

Retrieve Sports data in Python

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 multi-entity Transformer for multi-agent spatiotemporal modeling.

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

Python package for accessing and analyzing Formula 1 results, schedules, timing data and telemetry.

What the package does (one paragraph).

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)