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A GNSS-based method to define athlete manoeuvrability in field-based team sports.

ABSTRACT: This study presented a method of quantifying the manoeuvrability of two field-based team sport athletes and investigated its relationship with running velocity during competition. Across a season, 10 Hz Global navigation satellite system (GNSS) devices were worn during matches by 62 athletes (Australian Football League [AFL]; n = 36, 17 matches, National Rugby League [NRL]; n = 26, 21 matches). To quantify manoeuvrability, tortuosity was calculated from the X and Y coordinates from match GNSS files (converted from latitude and longitude). Tortuosity was calculated as 100 x natural logarithm of the chord distance (distance travelled between X and Y coordinates), divided by the straight-line distance. The maximal tortuosity was then quantified for each 0.5 m∙s-1 speed increment, ranging from 0 to the highest value for each game file. A quadratic model was fitted for each match file, controlling for the curvilinear relationship between tortuosity and velocity. A comparison of the quadratic coefficients between sports, and within sport between positions was investigated using linear mixed models. Resulting standard deviations (SDs) and mean differences were then assessed to establish standardized effect sizes (ES) and 90% confidence intervals (CI). A curvilinear relationship exists between maximal tortuosity and running speed, reflecting that as speed increases, athletes' ability to deviate from a linear path is compromised (i.e., run in a more linear path). Compared to AFL, NRL had a greater negative quadratic coefficient (a) (ES = 0.70; 0.47 to 0.93) for the 5 second analysis, meaning that as speed increased, NRL athletes' manoeuvrability reduced at a faster rate than when compared to AFL. There were no positional differences within each sport. GNSS derived information can be used to provide a measure of manoeuvrability tortuosity during NRL and AFL matches. The curvilinear relationship between tortuosity and speed demonstrated that as speed increased, manoeuvrability was compromised.

SUBMITTER: Duthie GM

PROVIDER: S-EPMC8604331 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundCoach-athlete relationship (CAR), thriving and athlete engagement are important psychological variables that affect sports performance. On the basis of self-determination theory, this study constructs a mediation model to examine the influence of CAR on athlete engagement and the mediating effect of thriving between them.MethodsThis cross-sectional study involves a questionnaire survey with 287 Chinese active athletes (M = 19.63, SD = 2.53) aged 14-26 years (64.5% male, 35.5% female) from eight sports. CAR, thriving and athlete engagement were assessed using the CAR Questionnaire, the Thriving Scale, and the Athlete Engagement Questionnaire, respectively.ResultsCAR and its dimensions can significantly and positively predict athlete engagement, complementarity, commitment, and closeness, accounting for 35.1%, 34.6%, and 30.4% of the cumulative variance in dominance analysis, respectively. The direct and indirect paths show that CAR affects athlete engagement through the mediating effect of thriving. The mediating effect model has a good fit and indirect effects account for 56.9% of the total effects.ConclusionThe effect of CAR on athlete engagement reflects a practical application of interpersonal dynamics in competitive sports to a certain extent. The following suggestions can be used to improve athlete engagement. First, setting common goals, emphasizing mutual cooperation, and building trust and support, promote coaches and athletes to have a higher sense of commitment and complementarity to each other, thereby helping improve athlete engagement. Second, meeting the vitality and progress needs of athletes effectively mobilizes CAR resources to promote athlete engagement, which can be manipulated by cultivating closeness, commitment, and complementarity. Third, to ensure the athletes' sports state and mental health, the sports team should focus on the cultivation of athletes' capacities to thrive and internally form a dynamic and positive sports atmosphere in their team. In the future, we can track and compare the influence of the improvement of CAR on thriving and athlete engagement can be tracked and compared from the dual perspectives of coaches and athletes.

Project description:The aim of this study was to define a method for evaluating a player's decisions during a game based on the success probability of his actions and for analyzing the player strategy inferred from game actions. There were developed formal definitions of i) the stochastic process of player decisions in game situations and ii) the inference process of player strategy based on his game decisions. The method was applied to the context of soccer goalkeepers. A model of goalkeeper positioning, with geometric parameters and solutions to optimize his position based on the ball position and trajectory, was developed. The model was tested with a sample of 65 professional goalkeepers (28.8 ± 4.1 years old) playing for their national teams in 2010 and 2014 World Cups. The goalkeeper's decisions were compared to decisions from a large dataset of other goalkeepers, defining the probability of success in each game circumstance. There were assessed i) performance in a defined set of classes of game plays; ii) entropy of goalkeepers' decisions; and iii) the effect of goalkeepers' positioning updates on the outcome (save or goal). Goalkeepers' decisions were similar to the ones with the lowest probability of goal on the dataset. Goalkeepers' entropy varied between 24% and 71% of the maximum possible entropy. Positioning dynamics in the instants that preceded the shot indicated that, in goals and saves, goalkeepers optimized their position before the shot in 21.87% and 83.33% of the situations, respectively. These results validate a method to discriminate successful performance. In conclusion, this method enables a more precise assessment of a player's decision-making ability by consulting a representative dataset of equivalent actions to define the probability of his success. Therefore, it supports the evaluation of the player's decision separately from his technical skill execution, which overcomes the scientific challenge of discriminating the evaluation of a player's decision performance from the action result.

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A GNSS-based method to define athlete manoeuvrability in field-based team sports.

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