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

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!****

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

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.

`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.

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.

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

Laurie's code for Metrica tracking data.

Last two minute report data from the NBA

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

Repository which contains various scripts and work with various basketball statistics

A Python package for data visualization for football analytics

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.

Make beautiful plots of player tracking data

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.

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 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.

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

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

Data analytics and modelling on basketball games

A Python plotting library for visualization of basketball data.