Quantifying Change of Direction Movement Demands in Professional Tennis Matchplay: An Analysis From the Australian Open Grand Slam.

ABSTRACT: Giles, B, Peeling, P, and Reid, M. Quantifying change of direction movement demands in professional tennis matchplay: An analysis from the Australian Open Grand Slam. J Strength Cond Res 38(3): 517-525, 2024-Change of direction (COD) contributes significantly to the movement repertoire of professional tennis players, yet the time-motion and degree demands of these changes are poorly understood. This study examines the velocity, acceleration, and angular displacement profiles of COD movements in modern professional tennis. One hundred eighty-two singles matches of Hawk-Eye player tracking data collected from the Australian Open Grand Slam were used for analysis. A novel COD classification algorithm was used to identify >120,000 medium and high-intensity CODs for analysis. Descriptive characteristics of the COD performance were calculated using player coordinate and time variables. Sex comparisons were analyzed using 2 mixed-effects models assessed for differences via likelihood ratios. Players performed 1.6 CODs per point. Both sexes executed, on average, 1.3-1.4 shots and covered 4.8 m per COD, with men performing changes every 2.7 seconds and women every 3.1 seconds. Medium-intensity COD comprised 88-94% of all identified changes. Approximately 2 in 3 CODs involved a degree of change >105°, whereas cutting maneuvers (<45°) were most commonly high-intensity COD. This study is the first to quantify the COD characteristics of professional tennis matchplay. Both sexes performed the same average number of CODs per point, however, men executed high-intensity changes twice as frequently as women, at an average of 1 every 5 points. These novel findings will help to improve the specificity of training interventions in elite tennis conditioning.

Differentiating movement styles in professional tennis: A machine learning and hierarchical clustering approach.

PURPOSE: Recent explorations of tennis-specific movements have developed contemporary methods for identifying and classifying changes of direction (COD) during match-play. The aim of this research was to employ these new analysis techniques to objectively explore individual nuance and style factors in the execution of COD movements in professional tennis. METHODS: Player tracking data from 62 male and 77 female players at the Australian Open Grand Slam were analysed for COD movements using a model algorithm, with a sample of 150,000 direction changes identified. Hierarchical clustering methods were employed on the time-motion and degree characteristics of these direction changes to identify groups of different COD performers. RESULTS: Five unique clusters, labelled "Cutters", "Gear Changers", "Lateral Changers", "Balanced Changers" and "Passive Changers" were identified in accordance with their varying speed, acceleration, degree and directionality of change features. CONCLUSIONS: Player COD clustering challenge previously held assumptions regarding on-court movement style, highlighting the complexity and variation in the sport's locomotion demands. In practice, the speed, acceleration, directionality and degree of change characteristics of each COD style can facilitate athlete profiling and the specificity of training interventions.HighlightsWe used machine learning techniques and cluster analysis methodology to explore the time motion characteristics of direction change skill in professional tennis.We present five unique types of change of direction style in professional tennis players. These include "Cutters", "Gear Changers", "Lateral Changers", "Balanced Changers" & "Passive Changers". These style classifications were established in accordance with their varying speed, acceleration, degree and directionality of change features.We show that the application of machine learning techniques to player tracking data can facilitate a more intricate understanding the sport's physical demands, which can be used to inform training programme design.

Applying the brakes in tennis: How entry speed affects the movement and hitting kinematics of professional tennis players.

Purpose: Movement and stroke production are coupled when playing tennis but generally decoupled in training and research. This study explored the lower limb, trunk and racquet mechanics of tennis players performing running forehands at varying movement speeds. Methods: Eleven female and seven male professional tennis players hit forehand groundstrokes while travelling at different movement speeds (Low: 1.4-2.0 m s - 1 , Medium: 2.70-2.90 m s - 1 , High: 4.0-4.3 m s - 1 ). Kinematics were captured using a VICON camera system. Speed and sex effects were analysed using linear mixed-effects models. Results: Prior to impact, females increased drive leg loading kinematics, and reduced preparatory trunk rotation (-9°), while both sexes lengthened their final stride and backswing during high-speed trials. At impact, racquet-head speed was unchanged for male players but dropped 14% when females travelled at high entry speed (p < 0.001). Conclusions: Reduced trunk rotation and lower limb drive contributed to female players being unable to maintain racquet-head speed when moving at high speed. Conversely, male players generated similar racquet-head speed despite the different entry speeds necessitating lower limb joint adjustments. These findings highlight the different deceleration strategies employed by male and female tennis professionals and challenge the widely accepted training theory in tennis that emphasises hitting and moving actions being rehearsed separately.

A machine learning approach for automatic detection and classification of changes of direction from player tracking data in professional tennis.

The purpose of this study was to develop an automated method for identifying and classifying change of direction (COD) movements in professional tennis using tracking data. Three sport science and strength and conditioning experts coded match-play footage of nineteen professional tennis players (9 male and 10 female) from the Australian Open Grand Slam for COD of medium and high intensity. A total of 1,494 changes were identified and aligned with 2D player position sampled at 25 Hz based on camera tracking data. Several machine learning classifiers were trained and tested on a set of 1,128 time-motion features. A random forest algorithm was found to have the best out-of-sample performance, classifying medium and high intensity changes with an F1-score of 0.729. This research offers a novel and applicable way for utilising player tracking data and machine learning techniques to automatically identify and classify COD movements in professional tennis.

How do professional tennis players move? The perceptions of coaches and strength and conditioning experts.

The purpose of this study was to explore the processes associated with successful on-court movement in professional tennis. To date, research has only provided generalised insight into the physical demands of tennis movement and the requisite physical skills. Data were collected through semi-structured interviews with 15 international tennis and/or strength and conditioning coaches involved in the development of tennis-specific movement in professional men's and women's tennis. A descriptive, qualitative approach was adopted, with interviews transcribed verbatim and analysed using an inductive to deductive thematic analysis. The highlighted ideas and concepts enabled the dynamic construction of higher-order themes representative of "good" tennis movers, alongside the conceptual development of a common movement "goal" or "outcome". The established higher-order themes portrayed three "styles" of "good" movers in modern professional tennis: those who were "fast" around the court, those who "read the play" well, and those who were "efficient" in their movement. The established themes provide a framework for interpreting and categorising the movement of professional tennis players as well as its underpinning skill.

Mental toughness and behavioural perseverance: A conceptual replication and extension.

OBJECTIVES: The purpose of this study was to conduct a conceptual replication of the proposition that mental toughness is associated positively with behavioural perseverance. DESIGN: Repeated-measures design. METHODS: In total, 38 male Australian rules footballers took part in this study (age, 21±3 y; mass, 82.7±11.0kg; height, 1.84±.07m; football experience, 13±4 y). Participants self-reported mental toughness approximately one week prior to their first testing session where we assessed their aerobic capacity via the measurement of peak oxygen consumption (V˙O2peak). Approximately one week later, participants completed a 20m shuttle run test (MST). The final testing session took place approximately one week later, where participants completed a simulated team game circuit (STGC; 60min) to simulate game-relevant level of fatigue, which was followed immediately by a 20m MST. RESULTS: Mental toughness was a salient determinant of the variation in behavioural perseverance under typical circumstances, when prior knowledge from past research was incorporated directly into the estimation process. However, the positive association between mental toughness and behavioural perseverance did not generalise to a performance context in which participants were fatigued. CONCLUSIONS: The results of the current study suggest that mental toughness represents a salient psychological correlate of behavioural perseverance in a discrete physical task that taxes the aerobic energy system in some but not all situations. When fatigued, the effect of mental toughness is outweighed by greater underlying fitness.