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  • Spearing_Tawn__RankingEliteSwimmers_21_05_2020

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Ranking elite swimmers using extreme value theory.

Research output: Contribution to journalJournal article

Forthcoming

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Ranking elite swimmers using extreme value theory. / Spearing, Harry; Tawn, Jonathan; Paulden, Tim ; Irons, David; Bennett, Grace.

In: Journal of the Royal Statistical Society: Series A Statistics in Society, 20.05.2020.

Research output: Contribution to journalJournal article

Harvard

Spearing, H, Tawn, J, Paulden, T, Irons, D & Bennett, G 2020, 'Ranking elite swimmers using extreme value theory.', Journal of the Royal Statistical Society: Series A Statistics in Society.

APA

Spearing, H., Tawn, J., Paulden, T., Irons, D., & Bennett, G. (Accepted/In press). Ranking elite swimmers using extreme value theory. Journal of the Royal Statistical Society: Series A Statistics in Society.

Vancouver

Spearing H, Tawn J, Paulden T, Irons D, Bennett G. Ranking elite swimmers using extreme value theory. Journal of the Royal Statistical Society: Series A Statistics in Society. 2020 May 20.

Author

Spearing, Harry ; Tawn, Jonathan ; Paulden, Tim ; Irons, David ; Bennett, Grace. / Ranking elite swimmers using extreme value theory. In: Journal of the Royal Statistical Society: Series A Statistics in Society. 2020.

Bibtex

@article{80545161a857457faf4438fefebfad23,
title = "Ranking elite swimmers using extreme value theory.",
abstract = "The International Swimming Federation (FINA) uses a very simple points system with the aim to rank swimmers across all Olympic events. The points acquired is a function of the ratio of the recorded time and the current world record for that event. With some world records considered better than others however, bias is introduced between events, with some being much harder to attain points where the world record is hard to beat. A model based on extreme value theory will be introduced, where swim-times are modelled through their rate of occurrence, and with the distribution of the best times following a generalised Pareto distribution. Within this framework, the strength of a particular swim is judged based on its position compared to the whole distribution of swim-times, rather than just the world record. This model also accounts for the date of the swim, as training methods improve over the years, as well as changes in technology, such as full body suits. The parameters of the generalised Pareto distribution, for each of the 34 individual Olympic events, will be shown to vary with a covariate, leading to a novel single unied description of swim quality over all events and time. This structure, which allows information to be shared across all strokes, distances, and genders, improves the predictive power as well as the modelrobustness compared to equivalent independent models. A by-product of the model is that it is possible to estimate other features of interest, such as the ultimate possible time, the distribution of new world records for any event, and to correct swim times for the effect of full body suits. The methods will be illustrated using a dataset of the best 500 swim-times for each event in the period 2001-2018.",
keywords = "Elite swimming, extreme value theory, Poisson processes, ranking, smoothing splines, sports modelling, statistical modelling, ultimate performance",
author = "Harry Spearing and Jonathan Tawn and Tim Paulden and David Irons and Grace Bennett",
year = "2020",
month = may
day = "20",
language = "English",
journal = "Journal of the Royal Statistical Society: Series A Statistics in Society",
issn = "0964-1998",
publisher = "Wiley",

}

RIS

TY - JOUR

T1 - Ranking elite swimmers using extreme value theory.

AU - Spearing, Harry

AU - Tawn, Jonathan

AU - Paulden, Tim

AU - Irons, David

AU - Bennett, Grace

PY - 2020/5/20

Y1 - 2020/5/20

N2 - The International Swimming Federation (FINA) uses a very simple points system with the aim to rank swimmers across all Olympic events. The points acquired is a function of the ratio of the recorded time and the current world record for that event. With some world records considered better than others however, bias is introduced between events, with some being much harder to attain points where the world record is hard to beat. A model based on extreme value theory will be introduced, where swim-times are modelled through their rate of occurrence, and with the distribution of the best times following a generalised Pareto distribution. Within this framework, the strength of a particular swim is judged based on its position compared to the whole distribution of swim-times, rather than just the world record. This model also accounts for the date of the swim, as training methods improve over the years, as well as changes in technology, such as full body suits. The parameters of the generalised Pareto distribution, for each of the 34 individual Olympic events, will be shown to vary with a covariate, leading to a novel single unied description of swim quality over all events and time. This structure, which allows information to be shared across all strokes, distances, and genders, improves the predictive power as well as the modelrobustness compared to equivalent independent models. A by-product of the model is that it is possible to estimate other features of interest, such as the ultimate possible time, the distribution of new world records for any event, and to correct swim times for the effect of full body suits. The methods will be illustrated using a dataset of the best 500 swim-times for each event in the period 2001-2018.

AB - The International Swimming Federation (FINA) uses a very simple points system with the aim to rank swimmers across all Olympic events. The points acquired is a function of the ratio of the recorded time and the current world record for that event. With some world records considered better than others however, bias is introduced between events, with some being much harder to attain points where the world record is hard to beat. A model based on extreme value theory will be introduced, where swim-times are modelled through their rate of occurrence, and with the distribution of the best times following a generalised Pareto distribution. Within this framework, the strength of a particular swim is judged based on its position compared to the whole distribution of swim-times, rather than just the world record. This model also accounts for the date of the swim, as training methods improve over the years, as well as changes in technology, such as full body suits. The parameters of the generalised Pareto distribution, for each of the 34 individual Olympic events, will be shown to vary with a covariate, leading to a novel single unied description of swim quality over all events and time. This structure, which allows information to be shared across all strokes, distances, and genders, improves the predictive power as well as the modelrobustness compared to equivalent independent models. A by-product of the model is that it is possible to estimate other features of interest, such as the ultimate possible time, the distribution of new world records for any event, and to correct swim times for the effect of full body suits. The methods will be illustrated using a dataset of the best 500 swim-times for each event in the period 2001-2018.

KW - Elite swimming

KW - extreme value theory

KW - Poisson processes

KW - ranking

KW - smoothing splines

KW - sports modelling

KW - statistical modelling

KW - ultimate performance

M3 - Journal article

JO - Journal of the Royal Statistical Society: Series A Statistics in Society

JF - Journal of the Royal Statistical Society: Series A Statistics in Society

SN - 0964-1998

ER -