Comparing Thirty30 Tennis with Traditional Tennis

  • Peter O'Donoghue Cardiff Metropolitan University
  • Mark Milne STATS
Keywords: Probabilistic model, scoreline effect, rule changes

Abstract

Thirty30 is a shorter format of tennis where games start at 30-30. This means that a greater proportion of points are game points or break points than would be the case in traditional tennis. The purpose of the current paper is to compare the probability of players of different abilities winning games, sets and matches between Thirty30 tennis and traditional tennis. This is done using probabilistic models of each format of tennis. The results show that there is reduced dominance of the serve and a greater probability of upsets in Thirty30 tennis than in traditional tennis. The models are also experimented with, adjusting the probability of winning points where the point is a game point or a break point. The paper shows that such scoreline effects have a greater impact in Thirty30 tennis than they do in traditional tennis. This has implications for player preparation for Thirty30 tennis.

References

Born, P., & Vogt, T. (2018). Video analysis and video feedback in tennis: Using mobile devices to benefit digital teaching and learning. ITF Coaching and Sport Science Review, 75, 29-30.

Brams, S.J., & Ismail, M.S. (2018). Making rules fairer. SIAM Review, 60(1), 181-202, doi: 10.1137/16M1074540

Cowden, R.G. (2016). Competitive Performance Correlates of Mental Toughness in Tennis. Perceptual and motor skills, 123(1), 341-360. doi:

1177/0031512516659902

Croucher, J.S. (1982). The effect of the tennis tie-breaker. Research Quarterly for Exercise and Sport, 53, 336-339.

Croucher, J.S. (1986). The conditional probability of winning games of tennis. Research Quarterly in Exercise and Sport, 57, 23-26.

Cui, Y., Gómez, M-Á., Gonçalves, B., Lui, H., & Sampaio, J. (2017). Effects of experience and relative quality in Tennis Match Performance during Four Grand Slams. International Journal of Performance Analysis in Sport, 17, 783-801. doi: 10.1080/24748668.2017.1399325

Delgado-García, G., Vanrenterghem, J., Muñoz-García, A., Ruiz-Malagón, E.J., Mañas-Bastidas, A., & Soto-Hermoso, V.M. (2019). Probabilistic structure of errors in forehand and backhand groundstrokes of advanced tennis players. International Journal of Performance Analysis in Sport, 19, 698-710. doi: 10.1080/24748668.2019.1647733

Fernandez-Fernandez, J., Sanz-Rivas, D., & Mendez-Villanueva, A. (2009). A review of the activity profile and physiological demands of tennis match play. Strength and Conditioning Journal, 31(4), 15-26.

Fischer, G. (1980). Exercise in probability and statistics, or the probability of winning at tennis. American Journal of Physics, 48, 14-19.

Fitzpatrick, A., Stone, J.A., Choppin, S., & Kelley, J. (2019). Important performance characteristics in elite clay and grass court tennis match-play. International Journal of Performance Analysis in Sport, 19, 942-952. doi: 10.1080/24748668.2019.1685804

Gale, D. (1971). Optimal strategy for serving in tennis. Mathematics Magazine, 5, 197-9.

Gerchak, Y., & Kilgour, D.M. (2017). Serving strategy in tennis: accuracy v power. Mathematics Magazine, 90(3), 188-196.

Gescheit, D. T., Duffield, R., Skein, M., Brydon, N., Cormack, S. J., & Reid, M. (2016). Effects of consecutive days of match play on technical performance in tennis. Journal of Sports Sciences, 35, 1988-1994. doi: 10.1080/02640414.2016.1244352

Kilit, B., Şenel, Ö., Arslan, E., & Can, S. (2016). Physiological Responses and Match Characteristics in Professional Tennis Players during a One-Hour Simulated Tennis Match. Journal of Human Kinetics, 51, 83-92.

Klaasen, F.J.G.M., & Magnus, J.R. (2001). Are points in tennis independent and identically distributed? Evidence from a dynamic binary panel data model. Journal of the American Statistical Association, 96, 500-509.

Knight, G., & O’Donoghue, P.G. (2011). The probability of winning break points in Grand Slam men’s singles tennis. European Journal of sports Science, 12(6), 462-468. doi: 10.1080/17461391.2011.577239

Kovalchik, S.A., Sackmann, J., & Reid, M. (2017). Player, Official, or Machine?: Uses of the Challenge System in Professional Tennis. International Journal of Performance Analysis in Sport, 17, 961-969.

Maraga, N., Duffield, R., Gescheit, D., Perri, T., & Reid, M. (2018). Playing not once, not twice but three times in a day: the effect of fatigue on performance in junior tennis players. International Journal of Performance Analysis in Sport, 18, 104-114. doi: 10.1080/24748668.2018.1452110

McHale, I.G. (2010). Assessing the fairness of the golf handicapping system in the UK. Journal of Sports Sciences, 28(10), 1033-41. doi: 10.1080/02640414.2010.495992

Mendez-Villanueva, A., Fernandez-Fernandez, J., Bishop, D., Fernandez-Garcia, B., & Terrados, N. (2007). Activity patterns, blood lactate concentrations and ratings of perceived exertion during a professional singles tennis tournament. British Journal of Sports Medicine, 41, 296-300.

Milne, M.J. (2018). Thirty30: where every point counts. Retrived from https://thirty30tennis.com

Morris, C. (1977). The most important points in tennis. In Ladany, S.P. & Machol, R.E. (Eds.), Optimal Strategies in Sport (pp. 131-140). New York: North Holland.

Newton, P.K., & Aslam, K. (2006). Monte Carlo tennis. SIAM Review, 48, 722-742.

O’Donoghue, P. G. (2001). The most important points in Grand Slam singles tennis. Research Quarterly for Exercise and Sport, 72, 125-131.

O’Donoghue, P.G. (2012). Break points in Grand Slam men’s singles tennis. International Journal of Performance Analysis in Sport, 12, 156-165.

doi: 10.1080/24748668.2012.11868591

O’Donoghue, P.G. (2013). Rare events in tennis. International Journal of Performance Analysis in Sport, 13, 535-552. doi: 10.1080/24748668.2013.11868668

O’Donoghue, P.G., & Ingram, B. (2001). A notational analysis of elite tennis strategy. Journal of Sports Sciences, 19, 107-115. doi: 10.1080/026404101300036299

O’Donoghue, P.G.; & Simmonds, E. (2019). Probability of winning and match length in Tiebreak Ten tennis. International Journal of Performance Analysis in Sport, 19, 402-416. doi: 10.1080/24748668.2019.1615296

Pollard, G.H. (1983). An analysis of classical and tie-breaker tennis. Australian Journal of Statistics, 25(3), 496-505.

Pollard, G.H. (2002). An effect of the variation of the assumption that the probability of winning a point in tennis is constant. Proceedings of the 6th Australian Conference on Mathematics and Computers in Sport (pp. 221-226). Sydney: University of Technology.

Pollard, G., & Barnett, T. (2018). Some new ‘Short Games’ within a set of tennis. International Journal of Computer Science in Sport, 17(1), 67-76.

doi: 10.2478/ijcss-2018-0003

Pollard G. H., & Noble, K. (2003). Scoring to remove long matches, increase tournament fairness and reduce injuries. Journal of Medicine and Science in Tennis, 8(3), 12-13.

Reid, M., Morgan, S., & Whiteside, D. (2016). Matchplay characteristics of Grand Slam tennis: implications for training and conditioning. Journal of Sports Sciences, 34(19), 1791-1798. doi: 10.1080/02640414.2016.1139161

Simmonds, E., & O’Donoghue, P.G. (2018). Probabilistic models comparing Fast4 and traditional tennis. International Journal of Computer Science in Sport, 17(2), 141-162. doi: 10.2478/ijcss-2018-0008

Söğüt, M. (2018). Stature: does it really make a difference in match-play outcomes among professional tennis players?. International Journal of Performance Analysis in Sport, 18, 255-261. doi: 10.1080/24748668.2018.1466259

Standard. (2016). Rains wreaks havoc at Wimbledon but ‘People’s Sunday’ still unlikely. Retrieved from https://www.standard.co.uk/sport/tennis/rain-wreaks-havoc-on-day-three-of-wimbledon-but-peoples-sunday-remains-unlikely-a3284391.html

Torres, C.R. (2014). The Bloomsburg Companion to Philosophy of Sport. London, UK: Bloomsburg Publishing.

Williams, J. (2008). Rule changes in sport and the role of notation. In Hughes, M. & Franks, I.M. (Eds.), The Essentials of Performance Analysis: an introduction (pp.226-242). London: Routledge.

Wright, B., Rodenberg, M.R., & Sackmann, J. (2013). Incentives in Best of N Contests: Quasi-Simpson’s Paradox in Tennis. International Journal of Performance Analysis in Sport, 13(3), 790-802. doi: 10.1080/24748668.2013.11868689

Published
2020-12-23
How to Cite
O’Donoghue, P., & Milne, M. (2020). Comparing Thirty30 Tennis with Traditional Tennis. International Journal of Racket Sports Science, 2(2), 18-28. Retrieved from https://journal.racketsportscience.org/index.php/ijrss/article/view/12