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Athletic Performance

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A detailed analysis of game statistics of professional tennis players: An inferential and machine learning approach.

PloS one
Tennis, a widely enjoyed sport, motivates athletes and coaches to optimize training for competitive success. This retrospective predictive study examines anthropometric features and statistics of 1990 tennis players in the 2022 season, using 20,040 d...

Neural network and layer-wise relevance propagation reveal how ice hockey protective equipment restricts players' motion.

PloS one
Understanding the athlete's movements and the restrictions incurred by protective equipment is crucial for improving the equipment and subsequently, the athlete's performance. The task of equipment improvement is especially challenging in sports incl...

Using machine learning to determine the nationalities of the fastest 100-mile ultra-marathoners and identify top racing events.

PloS one
The present study intended to determine the nationality of the fastest 100-mile ultra-marathoners and the country/events where the fastest 100-mile races are held. A machine learning model based on the XG Boost algorithm was built to predict the runn...

Integration of machine learning XGBoost and SHAP models for NBA game outcome prediction and quantitative analysis methodology.

PloS one
This study investigated the application of artificial intelligence in real-time prediction of professional basketball games, identifying the variations within performance indicators that are critical in determining the outcomes of the games. Utilizin...

Predicting Basketball Shot Outcome From Visuomotor Control Data Using Explainable Machine Learning.

Journal of sport & exercise psychology
Quiet eye (QE), the visual fixation on a target before initiation of a critical action, is associated with improved performance. While QE is trainable, it is unclear whether QE can directly predict performance, which has implications for training int...

Performance of artificial neural network compared to multi-linear regression in prediction of countermovement jump height.

Journal of bodywork and movement therapies
Previous research has used primarily linear regression models to predict jump height and establish contributors of performance. The purpose of this study was to compare the performance of artificial neural network (ANN) and multi-linear regression (M...

IMU Airtime Detection in Snowboard Halfpipe: U-Net Deep Learning Approach Outperforms Traditional Threshold Algorithms.

Sensors (Basel, Switzerland)
Airtime is crucial for high-rotation tricks in snowboard halfpipe performance, significantly impacting trick difficulty, the primary judging criterion. This study aims to enhance the detection of take-off and landing events using inertial measurement...

The factors affecting aerobics athletes' performance using artificial intelligence neural networks with sports nutrition assistance.

Scientific reports
This work aims to comprehensively explore the influencing factors of aerobics athletes' performance by integrating sports nutrition assistance and artificial intelligence neural networks. First, a personalized assessment and analysis of athletes' nut...

Early specialization in formative basketball: A machine learning analysis of shooting patterns in U14 and professional players.

Journal of sports sciences
Growing evidence supports that early sport specialization in children and adolescents may compromise long-term athlete development and high-performance acquisition. This study aimed to determine the presence of specialised shooting roles in formative...