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Set-To-Set Performance Variation in Tennis Grand Slams: Play with Consistency and Risks

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Set-To-Set Performance Variation in Tennis Grand Slams: Play with Consistency and Risks Journal of Human Kinetics volume 73/2020, 153-163 DOI: 10.2478/hukin-2019-0140 153 Section III – Sports Training Set-to-set Performance Variation in Tennis Grand Slams: Play with Consistency and Risks by Yixiong Cui1, Haoyang Liu1, Miguel-Ángel Gómez2, Hongyou Liu3, Bruno Gonçalves4 The study analysed the set-to-set variation in performance using match statistics of 146 completed main-draw matches in Australian Open and US Open 2016-2017 men’s singles. Comparisons of technical-tactical and physical performance variables were done between different sets; and the within-match coefficients of variation (CV) of these variables were contrasted between match winning and losing players. All comparisons were realized via standardized (Cohen’s d) mean differences and uncertainty in the true differences was assessed using non-clinical magnitude-based inferences. Results showed that there was possibly to very likely decreases in the serve, net and running related variables (mean difference, ±90%CL: -0.16, ±0.14 to -0.45, ±0.24, small) and an increase in the return and winner related variables (0.17, ±0.24 to 0.24, ±0.14, small) in the last sets when compared to the initial sets, indicating the influence of match fatigue and the player’s choice of match tactics and pacing strategy. Besides, winning players were revealed to have lower CV values in most of performance variables (-0.16, ±0.24 to -0.82, ±0.23, small to moderate) except for the second serve, winner, and physical performance variables (0.25, ±0.26 to 1.6, ±0.25, small to large), indicating that they would sacrifice the consistency to gain more aggressiveness and to dominate the match. Key words: performance profile, match statistics, analysis, winner. Introduction The complexity and dynamics of tennis 2014), noise of the audience (Dube and Tatz, 1991) determine that player’s game strategy and and even the line-calling bias (Carboch et al., technical-tactical performance are critically 2016). Therefore, adjusting to the constant change influenced by a range of contextual constraints of those constraints and making correspondent (Filipcic et al., 2017; Ojala and Häkkinen, 2013; tactical decisions should be an essential attribute Pereira et al., 2018). The available research already reinforced in the development of professional evidenced that those constraints might originated tennis players (Murray and Hunfalvay, 2017; from the differences of the match location Triolet et al., 2013). (O'Donoghue and Ingram, 2001), players’ qualities Players are required to perceive, interpret (Cui et al., 2017, 2019), weather conditions and anticipate the before-mentioned factors (Morante and Brotherhood, 2007), score-line efficiently and react with proper techniques (O'Donoghue, 2012), spatial-temporal (Cowden, 2016; Murray and Hunfalvay, 2017). relationships among players (Carvalho et al., 2013; However, it is difficult to maintain consistently Martinez-Gallego et al., 2013), physiological this ability under a highly intensive and fatigue (Gomes et al., 2011; Reid and Duffield, competitive match situation, given that their 1 - AI Sports Engineering Lab, School of Sports Engineering, Beijing Sport University, Beijing, China. 2 – Facultad de Actividad Física y del Deporte (INEF),Universidad Politécnica de Madrid, Madrid, Spain. 3 - School of Physical Education & Sports Science, South China Normal University, Guangzhou, China. 4 – Department of Sport and Health, University of Évora, Évora, Portugal. Authors submitted their contribution to the article to the editorial board. Accepted for printing in the Journal of Human Kinetics vol. 73/2020 in July 2020. 154 Set-to-set performance variation in tennis grand slams: play with consistency and risks physical and physiological status is significantly eventually achieve greater consistency in impaired by match fatigue (Davey et al., 2002; performance and better adaptation to complex Gomes et al., 2011; Hornery et al., 2007). match constraints through well-oriented training Consequently, it would seem to be of interest for (Seifert et al., 2013). coaches, fitness trainers and players to customize Therefore, the aims of the current study were: training routines and refine match strategies if (i) to analyse the set-based differences in more game-based evidence is unveiled. technical-tactical and physical performance of However, most existing literature exclusively professional male players during hard-court focused on the general match performance of Grand Slams; and (ii) to explore the within-player players (Ma et al., 2013; Reid et al., 2016), failing to set-to-set variation in performance considering evaluate how different technical, tactical and the match outcome. It was hypothesized that physical variables changed within prolonged time there would be a decrement in match or days. In light of this issue, some attempts were performance from the first to the final set; and made to assess how players’ physiological and that the winning player would show less variation technical performance was influenced during a in performance than losing players. simulated tournament (Gescheit et al., 2015, 2016; Ojala and Häkkinen, 2013), which showed that Methods their technical, physical, physiological and Sample and variables perceptual status was compromised over Set-level statistics of 146 completed main consecutive days of the tournament due to heavy draw matches from 2016-2017 US Open (US) and speed strength loads, muscle damage, and Australian Open (AO) men’s singles were neuromuscular and perceptual fatigue. Moreover, included (in total 292 player observations). Whiteside and Reid (2016a) measured the Performance variables were collected from the physical responses of professional players during corresponding official website of each the first week of Australian Open, providing the tournament. Matches that had an early first-handed feedback of the external hitting and withdrawal of player were excluded, and as movement workloads within the most onerous men’s singles were played by the rule of “Best-of- Grand Slam tournament. Five”, all the matches concluding in three, four The former research inspected how and five sets were considered. In total, there were performance changed within different 543 individual sets collected. This investigation competitive tournaments and match locations, was approved by Institutional Research Ethics which could be regarded as a meso-level factor Committee of the Beijing Sport University and that influences players’ performance (De Bosscher conformed to the recommendations of the et al., 2006). Nonetheless, few studies have Declaration of Helsinki. analysed the variation in performance at a micro- Twenty-three match variables collected were level, which denotes for the set/game-based inter- grouped into the serve, return and efficiency & relationship between two competing players in physical performance related categories. Raw data terms of relative quality (Cui et al., 2018; Klaassen of some match variables were standardized into and Magnus, 2001), actual match strategy and their correspondent ratios to avoid bias arising tactics (O'Donoghue and Ingram, 2001) and from non-uniformity. The serve performance positioning dynamics during the point (Carvalho group included: ace%, serve winner%, double et al., 2013). Knowing this variation in fault%, 1st serve in%, 1st serve won%, 2nd serve performance would provide more evidence of won%, peak serve speed (km/h), 1st serve average how players could maintain constant performance speed (km/h) and second serve average speed or experience fluctuations in certain aspects (km/h); the return performance group was during the course of the match. Additionally, it comprised by: return winner%, return unforced also facilitates a deeper understanding about their error%, return 1st serve won%, return 2nd serve tactical behaviors as well as physiological and won%, break points per return game, break point mental state at an individual nano-level (Cowden, won% and break point saved%; while efficiency 2016; Gescheit et al., 2016). In turn, athletes who and physical group consisted of: winner of total are conscious of their performance variation could points won%, winner per unforced error ratio, Journal of Human Kinetics - volume 73/2020 http://www.johk.pl by Yixiong Cui et al. 155 dominance ratio, net points won%, net points won also performed via standardized (Cohen’s d) of total points won%, total distance covered in a mean differences with 90% confidence intervals set (m) and distance covered per point (m). (Hopkins et al., 2009). The difference within each The serve speed is measured by a radar pair of comparison was expressed as a factor of system that was tested to have acceptable the smallest worthwhile difference, based on a precision (average absolute measure difference: small standardized effect of Cohen’s d effect-size 0.8%) (ITF, 2005), while the distance related data principle (0.2 × between-sets SD). Thresholds for are provided by the Hawk-Eye system that is used effect size statistics were 0.2, trivial; 0.6, small; 1.2, to track player’s movement every 40 ms with a moderate; 2.0, large; and>2.0, very large. reported measurement mean error of 3.6 mm Uncertainty in the true differences of the (Mecheri et al., 2016). To test the inter-operator comparisons was assessed using non-clinical reliability of the collected data, two performance magnitude-based inferences. Magnitudes of clear analysts in tennis collected the data of two effects were described according to the following randomly-selected
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