In-game win probability models for Canadian football

Hill, Stephen E.

doi:10.1080/2573234x.2021.2015252

Cited by 1 publication

(1 citation statement)

References 32 publications

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“…Thus, improved methods for obtaining this matrix constitute an active area of research but improving upon them is beyond the scope of this paper (Kaplan et al. 2014 ; Hill 2021 ; Hvattum and Arntzen 2010 ; Lock and Nettleton 2014 ). As a simple yet effective reference model, we adapt the “Independent Poisson Model” from Ley et al.…”

Section: Methodsmentioning

confidence: 99%

Phylourny: efficiently calculating elimination tournament win probabilities via phylogenetic methods

2023

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The prediction of knockout tournaments represents an area of large public interest and active academic as well as industrial research. Here, we show how one can leverage the computational analogies between calculating the phylogenetic likelihood score used in the area of molecular evolution to efficiently calculate, instead of approximate via simulations, the exact per-team tournament win probabilities, given a pairwise win probability matrix between all teams. We implement and make available our method as open-source code and show that it is two orders of magnitude faster than simulations and two or more orders of magnitude faster than calculating the exact per-team win probabilities naïvely, without taking into account the substantial computational savings induced by the tournament tree structure. Furthermore, we showcase novel prediction approaches that now become feasible due to this order of magnitude improvement in calculating tournament win probabilities. We demonstrate how to quantify prediction uncertainty by calculating 100,000 distinct tournament win probabilities for a tournament with 16 teams under slight variations of a reasonable pairwise win probability matrix within one minute on a standard laptop. We also conduct an analogous analysis for a tournament with 64 teams.

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