Probabilistic models comparing Fast4 and traditional tennis
Sciendo (a De Gruyter company)
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Tennis matches are hierarchies made up of sets containing games which, in turn, contain points. Traditional tennis games and tiebreakers could theoretically be infinite in length because a player needs to be at least 2 points ahead of the opponent to win. Fast4 tennis is a newer format of tennis that has been used at a number of levels of the sport including professional tennis where it has been used in Next Generation Finals events since 2017. The purpose of the current investigation is to compare the traditional tennis format to Fast4 tennis in terms of the probability of different players winning matches and the duration of matches. Probabilistic models of Fast4 tennis games and tiebreakers were developed. These models allowed the probability of winning games and tiebreakers to be compared between the two formats of tennis for a range of probabilities of players winning points. The models were then used within a series of simulations to determine the probability of winning sets and matches as well as the durations of games, tiebreakers, sets and matches in the two formats. Each component of the two formats of tennis was simulated 100,000 times revealing a reduced impact of serve, greater chance of upsets and shorter matches in Fast 4 tennis than in traditional tennis. The probability of players of differing abilities winning matches as well as the duration of tennis matches should be considered by those making decisions on the format of matches to be applied in tennis tournaments as well as by those preparing to compete in such tournaments.
International Journal of Computer Science in Sport;
Simmonds, E. and O'Donoghue, P.G. (2018) 'Probabilistic models comparing Fast4 and traditional tennis', International Journal of Computer Science in Sport, 17(2), pp.141-162. DOI: 10.2478/ijcss-2018-0008.
Dynodwr Gwrthrych Digidol (DOI)https://doi.org/10.2478/ijcss-2018-0008
Article published in International Journal of Computer Science in Sport on 31 December 2016, available open access at: https://doi.org/10.2478/ijcss-2018-0008.
Cardiff Metropolitan University (Grant ID: Cardiff Metropolian (Internal))
- Sport Research Groups 
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