AIMC Topic: Athletic Performance

Clear Filters Showing 21 to 30 of 97 articles

Explainable quality assessment of effective aligned skeletal representations for martial arts movements by multi-machine learning decisions.

Scientific reports
How to utilize modern technological means to provide both accurate scoring and objective feedback for martial arts movements has become an issue that needs to be addressed in the field of physical education. This study proposes an intelligent scoring...

Empowering the Sports Scientist with Artificial Intelligence in Training, Performance, and Health Management.

Sensors (Basel, Switzerland)
Artificial Intelligence (AI) is transforming the field of sports science by providing unprecedented insights and tools that enhance training, performance, and health management. This work examines how AI is advancing the role of sports scientists, pa...

Assessing the effectiveness of fuzzy logic-based models for predicting sports event outcomes: A CRITIC-VIKOR approach.

PloS one
Incorporating fuzzy logic-based models into sports prediction has generated significant interest due to the intricate nature of athletic events and the many factors influencing their outcomes. This study evaluates the effectiveness of fuzzy logic-bas...

Prediction of talent selection in elite male youth soccer across 7 seasons: A machine-learning approach.

Journal of sports sciences
This study aimed to investigate the relative importance of parameters from several domains associated to both selecting or de-selecting players with regards to the next age group within a professional German youth soccer academy across a 7-year perio...

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...

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...

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...

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...

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...

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...