AIMC Topic: Soccer

Clear Filters Showing 1 to 10 of 56 articles

Evaluation of various traditional machine learning techniques for predicting the acute effect of different hamstring muscle stretching methods among male soccer players.

Scientific reports
This study investigated the acute effects of static (SS), dynamic (DS), and ballistic (BS) hamstring stretching on performance in male soccer players and applied machine learning (ML) to predict protocol efficacy. A total of 249 players with and with...

Detection of violence in football sport based on deep learning and optimization algorithm.

Scientific reports
Among the various sports activities that are carried out all over the world, football is undoubtedly the most popular, most participated in and most watched activity and sport. The increasing spread of sports has caused it to break down geographical,...

Football sports automatic judgment model based on improved YOLOv7 and RNN.

PloS one
The extraction, classification, and judgment of sports video scenes can improve work efficiency and accuracy. To understand sports videos in dynamic scenes, this study applies deep learning technology, firstly introducing clustering algorithm and att...

Advanced feature engineering in Acute:Chronic Workload Ratio (ACWR) calculation for injury forecasting in elite soccer.

PloS one
Controlling training monotony and monitoring external workload using the Acute:Chronic Workload Ratio (ACWR) is a common practice among elite soccer teams to prevent non-contact injuries. However, recent research has questioned whether ACWR offers su...

Impact of Preseason Training Camps on Fitness, Fatigue, and Performance in Professional Football Players: Mildaltitude Camp Versus Sea-Level Camp.

International journal of sports physiology and performance
PURPOSE: Preseason in football is crucial for optimizing physical fitness, team cohesion, and tactical readiness. This study investigated the effects of 2 distinct preseason training environments-mild altitude with cooler conditions and sea level wit...

A method for feature division of Soccer Foul actions based on salience image semantics.

PloS one
The purpose of this study is to realize the automatic identification and classification of fouls in football matches and improve the overall identification accuracy. Therefore, a Deep Learning-Based Saliency Prediction Model (DLSPM) is proposed. DLSP...

Neuronal dynamics of slow and fast-motion motor imagery.

Neuroscience
Motor imagery (MI) is a cognitive process requiring mental simulation of physical actions, engaging neural networks that overlap with those activated during actual execution. This study investigated the neural correlates of slow and fast MI in ten he...

Comparative analysis of automated foul detection in football using deep learning architectures.

Scientific reports
Automated foul detection in football represents a challenging task due to the dynamic nature of the game, the variability in player movements, and the ambiguity in differentiating fouls from regular physical contact. This study presents a comprehensi...

Deep learning-based recognition model of football player's technical action behavior using PCA-LBP algorithm.

Scientific reports
Football is a sport that requires sportsmen to have both physical strength and physical features. It must consider the distinctions between individuals and then provide targeted training. Football players can perform better on the field with targeted...

Subjective recovery in professional soccer players: A machine learning and mediation approach.

Journal of sports sciences
Coaches often ask players to judge their recovery status (subjective recovery). We aimed to explore potential determinants of subjective recovery in 101 male professional soccer players of 4 Italian Serie C teams and to further investigate whether th...