Package: sport 0.2.2

sport: Sequential Pairwise Online Rating Techniques

Calculates ratings for two-player or multi-player challenges. Methods included in package such as are able to estimate ratings (players strengths) and their evolution in time, also able to predict output of challenge. Algorithms are based on Bayesian Approximation Method, and they don't involve any matrix inversions nor likelihood estimation. Parameters are updated sequentially, and computation doesn't require any additional RAM to make estimation feasible. Additionally, base of the package is written in C++ what makes sport computation even faster. Methods used in the package refer to Mark E. Glickman (1999) <https://www.glicko.net/research/glicko.pdf>; Mark E. Glickman (2001) <doi:10.1080/02664760120059219>; Ruby C. Weng, Chih-Jen Lin (2011) <https://www.jmlr.org/papers/volume12/weng11a/weng11a.pdf>; W. Penny, Stephen J. Roberts (1999) <doi:10.1109/IJCNN.1999.832603>.

Authors:Dawid Kałędkowski [aut, cre]

sport_0.2.2.tar.gz
sport_0.2.2.zip(r-4.7)sport_0.2.2.zip(r-4.6)sport_0.2.2.zip(r-4.5)
sport_0.2.2.tgz(r-4.6-x86_64)sport_0.2.2.tgz(r-4.6-arm64)sport_0.2.2.tgz(r-4.5-x86_64)sport_0.2.2.tgz(r-4.5-arm64)
sport_0.2.2.tar.gz(r-4.7-arm64)sport_0.2.2.tar.gz(r-4.7-x86_64)sport_0.2.2.tar.gz(r-4.6-arm64)sport_0.2.2.tar.gz(r-4.6-x86_64)
sport_0.2.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html
DESCRIPTION |NEWS
card.svg |card.png
sport/json (API)

# Install 'sport' in R:
install.packages('sport', repos = c('https://gogonzo.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/gogonzo/sport/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • gpheats - Heat results of Speedway Grand-Prix
  • gpsquads - Turnament results of Speedway Grand-Prix

On CRAN:

Conda:

cpp

6.11 score 25 stars 26 scripts 529 downloads 4 exports 19 dependencies

Last updated from:8617cfcbfd. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK165
linux-devel-x86_64OK172
source / vignettesOK186
linux-release-arm64OK160
linux-release-x86_64OK281
macos-release-arm64OK138
macos-release-x86_64OK252
macos-oldrel-arm64OK133
macos-oldrel-x86_64OK260
windows-develOK125
windows-releaseOK128
windows-oldrelOK131
wasm-releaseOK112

Exports:bbt_rundbl_runglicko_runglicko2_run

Dependencies:clicpp11data.tablefarverggplot2gluegtableisobandlabelinglifecycleR6RColorBrewerRcpprlangS7scalesvctrsviridisLitewithr

The theory of the online update algorithms
Theory | Bayesian update rule | Players nested within team | Glicko rating system | Glicko2 rating system | Bayesian Bradley Terry | Dynamic Bayesian Logit | Additional controls | lambda | kappa | weight

Last update: 2026-03-16
Started: 2020-01-01

sport an R package for online update algorithms
About | Package Usage | Available Data | Estimate dynamic ratings | Output | Advanced sport | Formula | Controlling update size by weight | Avoiding excessive RD shrinkage with kappa | Control output uncertainty by lambda | Players nested within teams

Last update: 2025-08-22
Started: 2018-09-10