AIMC Topic: Soccer

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Application of Machine Learning Methods to Investigate Joint Load in Agility on the Football Field: Creating the Model, Part I.

Sensors (Basel, Switzerland)
Laboratory studies have limitations in screening for anterior cruciate ligament (ACL) injury risk due to their lack of ecological validity. Machine learning (ML) methods coupled with wearable sensors are state-of-art approaches for joint load estimat...

Who are the best passing players in professional soccer? A machine learning approach for classifying passes with different levels of difficulty and discriminating the best passing players.

PloS one
The present study aimed to assess the use of technical-tactical variables and machine learning (ML) classifiers in the automatic classification of the passing difficulty (DP) level in soccer matches and to illustrate the use of the model with the bes...

Learning agile soccer skills for a bipedal robot with deep reinforcement learning.

Science robotics
We investigated whether deep reinforcement learning (deep RL) is able to synthesize sophisticated and safe movement skills for a low-cost, miniature humanoid robot that can be composed into complex behavioral strategies. We used deep RL to train a hu...

Association between match-related physical activity profiles and playing positions in different tasks: A data driven approach.

Journal of sports sciences
Assessing the intensity characteristics of specific soccer drills (matches, small-side game, and match-based exercises) could help practitioners to plan training sessions by providing the optimal stimulus for every player. In this paper, we propose a...

Predicting Soccer Players' Fitness Status Through a Machine-Learning Approach.

International journal of sports physiology and performance
PURPOSE: The study had 3 purposes: (1) to develop an index using machine-learning techniques to predict the fitness status of soccer players, (2) to explore the index's validity and its relationship with a submaximal run test (SMFT), and (3) to analy...

Relationship between external and internal load indicators and injury using machine learning in professional soccer: a systematic review and meta-analysis.

Research in sports medicine (Print)
This study verified the relationship between internal load (IL) and external load (EL) and their association on injury risk (IR) prediction considering machine learning (ML) approaches. Studies were included if: (1) participants were male professiona...

Prediction of defensive success in elite soccer using machine learning - Tactical analysis of defensive play using tracking data and explainable AI.

Science & medicine in football
The interest in sports performance analysis is rising and tracking data holds high potential for game analysis in team sports due to its accuracy and informative content. Together with machine learning approaches one can obtain deeper and more object...

Model of the Performance Based on Artificial Intelligence-Fuzzy Logic Description of Physical Activity.

Sensors (Basel, Switzerland)
The aim of the study was to build a fuzzy model of lower limb peak torque in an isokinetic mode. The study involved 93 male participants (28 male deaf soccer players, 19 hearing soccer players and 46 deaf untraining male). A fuzzy computational model...

xLength: Predicting Expected Ski Jump Length Shortly after Take-Off Using Deep Learning.

Sensors (Basel, Switzerland)
With tracking systems becoming more widespread in sports research and regular training and competitions, more data are available for sports analytics and performance prediction. We analyzed 2523 ski jumps from 205 athletes on five venues. For every j...

Deep Learning-Based Football Player Detection in Videos.

Computational intelligence and neuroscience
The main task of football video analysis is to detect and track players. In this work, we propose a deep convolutional neural network-based football video analysis algorithm. This algorithm aims to detect the football player in real time. First, five...