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winning: Contest Win Probabilities and Ability Calibration

Solves the horse race problem in both directions. Infers relative ability from win probabilities (or betting dividends) for contests whose entrants share a common performance distribution, with dead heats handled exactly, by the lattice fixed-point algorithm of Cotton (2021) <doi:10.1137/19M1276261>. Also computes all N win probabilities of a factor-structured Gaussian race (multinomial probit with low-rank-plus-diagonal covariance) in one shared-lattice pass of O(Q*N*L) operations, and inverts observed shares to abilities by a damped Newton method with analytic slopes. A dependency-free base-R port of the reference python package 'winning'. Performances are times: lowest wins.

Version: 0.3.0
Suggests: mvtnorm, testthat (≥ 3.0.0)
Published: 2026-09-09
DOI: 10.32614/CRAN.package.winning
Author: Peter Cotton [aut, cre]
Maintainer: Peter Cotton <peter.cotton at microprediction.com>
BugReports: https://github.com/microprediction/winning/issues
License: MIT + file LICENSE
URL: https://github.com/microprediction/winning
NeedsCompilation: no
Materials: README
CRAN checks: winning results

Documentation:

Reference manual: winning.html , winning.pdf

Downloads:

Package source: winning_0.3.0.tar.gz
Windows binaries: r-devel: winning_0.3.0.zip, r-release: not available, r-oldrel: winning_0.3.0.zip
macOS binaries: r-release (arm64): not available, r-oldrel (arm64): winning_0.3.0.tgz, r-release (x86_64): winning_0.3.0.tgz, r-oldrel (x86_64): winning_0.3.0.tgz

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.