Ball Tracking Data Research Articles

Investigating Acceleration and Deceleration Patterns in Elite Youth Football: The Interplay of Ball Possession and Tactical Behavior

The main objective of this study was (1) to analyze the patterns of acceleration (Ac) and deceleration (Dec) during football matches in elite youth football, both within and between different segments of the match; and (2) to investigate the impact of ball possession and various playing positions on these acceleration and deceleration patterns. To provide a broader explanatory context, the influence of tactical space management was assessed in terms of depth and width. A descriptive comparative design was used, and data were collected during two friendly matches. Player and ball tracking data were collected using a local positioning system. In the attack phase, differences were obtained in the average Ac (first half: 0.42 ± 0.06 m·s−2, second half: 0.38 ± 0.07 m·s−2; p = 0.021, d = 0.50) and average Dec (first half: −0.44 ± 0.09 m·s−2, second half: −0.36 ± 0.08 m·s−2; p = 0.001, d = 0.84). Wingers in the attack phase obtained higher values in maximum Ac (1.65 ± 0.65 m·s−2; p = 0.007, η2 = 0.03), and in the total number of both Ac (68.7 ± 45.22; p = 0.001, η2 = 0.10) and Dec (70.6 ± 45.70; p = 0.001, η2 = 0.10). In the defense phase, full-backs obtained higher values in average Ac (0.53 ± 0.17 m·s−2; p = 0.001, η2 = 0.07) and average Dec (−0.49 ± 0.18 m·s−2; p = 0.001, η2 = 0.05) and wingers in the total number of Ac (43.9 ± 27.30; p = 0.001, η2 = 0.11) and Dec (43.8 ± 28.60; p = 0.001, η2 = 0.10). In young football players, Ac and Dec do not follow a decreasing end throughout the match, and their behavior is uneven depending on ball possession and the position assigned to the player, with the highest demands on Ac/Dec in winger and full-back positions.

A review and reassessment of the aerodynamics of cricket ball swing

This paper reviews 70 years of cricket ball swing literature and reassesses the results in light of new measurements. A comparison of ball tracking data with published experimental results shows that current understanding does not explain the behaviour observed in professional cricket matches. Descriptions of cricket ball boundary layer aerodynamics are updated with new results which show that the seam acts more like a series of vortex generators than a trip and that there is a laminar separation bubble on the seam side of the ball. Previous results for reverse swing are consolidated and compared with new data, showing that different magnitudes of swing occur depending on the condition of both sides of the ball. Variation in pressure and temperature should be included when the Reynolds number, a non-dimensional ball speed, is calculated, while humidity can be neglected. Studies on the effect of wind speed and direction are summarised and results considering the effect of free-stream turbulence are compared with new measurements. Throughout the paper, recommendations for future work are suggested. These include quantitative study of the effect of surface defects and roughness, an assessment of whether atmospheric turbulence can affect swing and investigation into the effect of backspin on swing.

Analysing Hawk-Eye ball-tracking data to explore successful serving and returning strategies at Wimbledon

ABSTRACT Investigations of elite tennis match-play have highlighted the importance of serving and returning strategies. This study establishes the most common and effective strategies used by male and female players at Wimbledon, and identifies associated winner-loser differences. Hawk-Eye ball-tracking data from 302 men’s and 139 women’s singles matches contested between 2016 and 2018 were analysed using confidence intervals, Chi-square and Chi-square partitions. For both sexes, first serves to lateral areas (Zones A and D) of the service boxes were more common and more successful than first serves to central areas (Zones B and C). Second serves to lateral areas also tended to be more successful than those to central areas, but players typically prioritised safety, often executing second serves to Zone C (central, but towards the backhand of right-handed opponents). Men and women hit more serve-returns to central areas than lateral areas of the court, despite serve-returns to lateral areas being more successful. Furthermore, winning male players were more accurate than losing male players, executing a comparatively higher percentage of serves and returns to lateral areas; winning female players demonstrated this on first serves only. These findings can be used to improve the specificity and representativeness of players’ grass court training.

Capture, analyse, visualise: An exemplar of performance analysis in practice in field hockey.

The goal of performance analysis is to capture the multitude of factors that affect sports strategy, and present them in an informative, interpretable, and accessible format. The aim of this study was to outline a performance analysis process in field hockey that captures, analyses and visualises strategy in layers of detail culminating in the creation of an RStudio Shiny application. Computerised notational analysis systems were developed to capture in-game events and ball tracking data of 74 matches from the Women’s Pro League 2019. Game styles were developed using k-means cluster analysis to reduce detailed in-game events into practical profiles to identify the attack types, game actions and tempo of a team’s strategy. Ball movement profiles were developed to identify the predictability (entropy) and direction (progression rates) of ball movements, and consequent distribution of possession in different attacking zones. The Shiny application, an interactive web-platform, links the information from simple game profiles with detailed game variables to understand each teams’ holistic game plan, how they are different, and how to exploit these differences. The process outlined can be applied to any team invasion sport to understand, develop and communicate successful strategies under different match situations.

Enhancing strategic defensive positioning and performance in the outfield.

Over the past 20 years, professional and collegiate baseball has undergone a transformation, with statistics and analytics increasingly factoring into most of the decisions being made on the field. One particular example of the increased role of analytics is in the positioning of outfielders, who are tasked with tracking down balls hit to the outfield to record outs and minimize potential offensive damage. This paper explores the potential of location analytics to enhance the strategic positioning of players, enabling improved response and performance. We implement a location optimization model to analyze collegiate ball-tracking data, seeking outfielder locations that simultaneously minimize the average distance to a batted ball and maximize the weighted importance of batted ball coverage within a response standard. Trade-off outfielder configurations are compared to observed fielder positioning, finding that location models and spatial optimization can lead to performance improvements ranging from 1 to 3%, offering a significant strategic advantage over the course of a season.

A Cluster Analysis Approach to Profile Men and Women’s Volley Positions in Professional Tennis Matches (Doubles)

(1) Background: Tennis ball tracking technology allows the aquirement of novel and reliable data about several performance indicators, such as volley positions. This information is key to understand match dynamics in doubles tennis and to better help preparing players for the demands they will face in match play. As such, the purpose of this study was to describe and compare the different types of volley positions in men’s and women’s doubles professional tennis. (2) Methods: Ball tracking data were collected for 46 women (Billie Jean King Cup) and 96 men’s doubles matches (Davis Cup). The variables used were the distance to the net, the distance to the centre of the court and the height of the impact. A K-Means cluster analysis was used to identify in each subsample different profiles of volley locations. (3) Results: The inferential analysis revealed differences in men’s (distance to the net η2 = 0.72, distance to the centre of the court η2 = 0.77 and impact height η2 = 0.63) and women’s subsamples (distance to the net η2 = 0.48, distance to the centre of the court η2 = 0.52 and impact height η2 = 0.51). (4) Conclusions: The results allowed the suggestion of a higher variability in men’s matches, as there were seven different clusters identified, and only four in women’s.

Use of Machine Learning to Automate the Identification of Basketball Strategies Using Whole Team Player Tracking Data

The use of machine learning to identify and classify offensive and defensive strategies in team sports through spatio-temporal tracking data has received significant interest recently in the literature and the global sport industry. This paper focuses on data-driven defensive strategy learning in basketball. Most research to date on basketball strategy learning has focused on offensive effectiveness and is based on the interaction between the on-ball player and principle on-ball defender, thereby ignoring the contribution of the remaining players. Furthermore, most sports analytical systems that provide play-by-play data is heavily biased towards offensive metrics such as passes, dribbles, and shots. The aim of the current study was to use machine learning to classify the different defensive strategies basketball players adopt when deviating from their initial defensive action. An analytical model was developed to recognise the one-on-one (matched) relationships of the players, which is utilised to automatically identify any change of defensive strategy. A classification model is developed based on a player and ball tracking dataset from National Basketball Association (NBA) game play to classify the adopted defensive strategy against pick-and-roll play. The methodology described is the first to analyse the defensive strategy of all in-game players (both on-ball players and off-ball players). The cross-validation results indicate that the proposed technique for automatic defensive strategy identification can achieve up to 69% accuracy of classification. Machine learning techniques, such as the one adopted here, have the potential to enable a deeper understanding of player decision making and defensive game strategies in basketball and other sports, by leveraging the player and ball tracking data.

Validation of ball spin estimates in tennis from multi-camera tracking data

ABSTRACTThe purpose of this study was to examine the accuracy of methods to estimate ball spin rate and spin axis direction using multi-camera tracking technology. The method implemented by Hawk-Eye and a theoretical ball trajectory model were assessed for their accuracy against high speed-vision. A theoretical ball trajectory model was found to estimate ball spin rate and the spin axis direction more accurately than the method used by Hawk-Eye. The superior performance of the ball trajectory model was indicated by a lower mean bias and standard deviation (2.92 ± 222.76) than Hawk-Eye (−100.01 ± 542.44), as well as narrower limits of agreement and a 327.63 RPM lower RMSE. Spin rates less than 4500 RPM were estimated with the highest accuracy, but neither method was able to consistently and accurately estimate spin rates >4500 RPM. The application of a trajectory model to multi-camera ball tracking data provides a practical and non-invasive method to accurately estimate the spin imparted when hitting, allowing for large-scale collection of spin rates during matches.

バスケットボールにおける選手・ボール位置情報の 3 次元可視化ツール

バスケットボールにおける選手・ボール位置情報の 3 次元可視化ツール

Characterisation of ball degradation events in professional tennis

Tennis balls are acknowledged to degrade with use and are replaced at regular intervals during professional matches to maintain consistency and uniformity in performance, such that the game is not adversely affected. Balls are subject to the international tennis federation’s (ITF) ball approval process, which includes a degradation test to ensure a minimum standard of performance. The aim of this investigation was to establish if the ITF degradation test can assess ball longevity and rate of degradation and determine if there is a need for a new degradation test that is more representative of in-play conditions. Ball tracking data from four different professional events, spanning the three major court surfaces, including both men’s and women’s matches were analysed. The frequency of first serves, second serves, racket impacts and surface impacts were assessed and the corresponding distribution of ball speed and (for surface impacts) impact angle was determined. Comparison of ball impact frequency and conditions between in-play data and the ITF degradation test indicated the development of a new test, more representative of in-play data, would be advantageous in determining ball longevity and rate of degradation with use. Assessment of data from different surfaces highlighted that grass court subjected the ball to fewer racket and surface impacts than hard court or clay. In turn, this appears to influence the distribution of ball speed on impact with the surface or racket, suggesting a surface-specific degradation test may be beneficial. As a result of these findings a new test protocol has been proposed, utilising the in-play data, to define the frequency of impacts and impact conditions to equate to nine games of professional tennis across the different surfaces.

Discovering Team Structures in Soccer from Spatiotemporal Data

In team sports like soccer, utilizing tracking data for analysis is challenging due to the dynamic and multi-agent nature of the data. The biggest issue surrounds the changing of positions or “roles” between players on a frame-to-frame basis, which causes misalignment of the data and makes it difficult to perform team analysis. In this paper, we present an unsupervised method to learn a formation template which allows us to “align” the tracking data at the frame level. Not only does this approach give important contextual information to facilitate large-scale analysis (e.g., we know when a player is in the left-wing position compared to left-back), it also yields the team structure or “formation” which serves as a strong descriptor for identifying a team’s style. The utility of the approach is demonstrated on a full season of player and ball tracking data from a professional soccer league consisting of over 21.5 million frames of player tracking data.

Matchplay characteristics of Grand Slam tennis: implications for training and conditioning

ABSTRACTThe purpose of this study was to probe the sex-based differences in the stroke and movement dynamics of Grand Slam hard-court tennis. Player and ball tracking data were collated for 102 male and 95 female players during the 2012–2014 Australian Open tournaments. Serve, serve return, groundstroke and movement data were compared between sexes. Serve statistics were the subject of the largest differences, with males achieving significantly faster speeds, aces and unreturned serves while also winning a greater percentage of service points. When returning serve, women contacted the ball closer to the net, lower to the ground and achieved flatter ball trajectories than males. Groundstroke frequencies were similar between sexes, although males hit with greater speed, flatter trajectories and impacted more shots inside the baseline. Distance covered per set or during points won or lost was not sex dependent, yet men exhibited faster average movement speeds. These findings highlight the need for sex-specific training and practice designs that cater to the different stroke dynamics, particularly in relation to the first serve and serve-return, as well as movement speeds.

The Automatic Checkout Method of Balloon-Tracking Data at Unequal Intervals of Time

By tracking a beacon ball with theodolite and radar synchronously to inspect the accuracy of ra-dar data is one of the common calibrating methods without calibration towers at sea. Relied on some com-plications, the theodolite which acts as the standard in the precision test can not following the track of a d-ynamic target continuously for a long time. So the present processing methods based on isochronal interv-als can just make use of less continuous data. Upon that a new dynamic adaptive checkout method is introduced. It solves the problem of outliers-eliminating automatically among a great deal of data at unequal in-terval time by three culling steps. The results indicate that this method can eliminate outliers in beacon ball tracking data and make batch processing base on uncontinuous data implemented effectively. Not only the data quantity has been increased, but also the data process efficiency has been improved.

The Automatic Checkout Method of Balloon-Tracking Data at Unequal Intervals of Time

By tracking a beacon ball with theodolite and radar synchronously to inspect the accuracy of ra-dar data is one of the common calibrating methods without calibration towers at sea. Relied on some com-plications, the theodolite which acts as the standard in the precision test can not following the track of a d-ynamic target continuously for a long time. So the present processing methods based on isochronal interv-als can just make use of less continuous data. Upon that a new dynamic adaptive checkout method is introduced. It solves the problem of outliers-eliminating automatically among a great deal of data at unequal in-terval time by three culling steps. The results indicate that this method can eliminate outliers in beacon ball tracking data and make batch processing base on uncontinuous data implemented effectively. Not only the data quantity has been increased, but also the data process efficiency has been improved.