ArticleJournal of clinical medicine2022
Predictive Modeling of Injury Risk Based on Body Composition and Selected Physical Fitness Tests for Elite Football Players.
Article in Journal of clinical medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 20 citations in OpenAlex.
- Assessing the biomechanical characteristics of defensive movements in elite boxers of different competitive levels.BMC sports science, medicine & rehabilitation · 2026Article
- Preseason Body Composition Phenotypes and In-Season Injury Burden in Male Professional Basketball: A Retrospective Cohort Study.Sports (Basel, Switzerland) · 2026Article
- Development and validation of a machine learning model for non-contact injury prediction based on lower limb strength asymmetry in professional football.Scientific reports · 2026Article
- Short-term - change on physical capacities of football players within few days before ACL-injury: a retrospective case-control study.BMC sports science, medicine & rehabilitation · 2026Article
- Machine learning approaches to injury risk prediction in sport: a scoping review with evidence synthesis.British journal of sports medicine · 2025Article
- The Impact of Heat Exposure on the Health and Performance of Soccer Players: A Narrative Review and Bibliometric Analysis.Sports (Basel, Switzerland) · 2024Review
- Performance and healthcare analysis in elite sports teams using artificial intelligence: a scoping review.Frontiers in sports and active living · 2024Article
- The Effects of Pre-Season and Relationships with Physical, Physiological, Body Composition, and Load Markers: A Case Study Comparing Starters versus Non-Starters from an Elite Female Professional Soccer Team.Medicina (Kaunas, Lithuania) · 2023Article
- Advancements in Sports Medicine.Journal of clinical medicine · 2023Article
- Weekly External Load Performance Effects on Sports Injuries of Male Professional Football Players.International journal of environmental research and public health · 2023Article
- Sports Injuries of a Portuguese Professional Football Team during Three Consecutive Seasons.International journal of environmental research and public health · 2022Article
Corrections and comments
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Authors and funding
10 authors at 7 institutions in 4 countries.
Funding
Abstract
Injuries are one of the most significant issues for elite football players. Consequently, elite football clubs have been consistently interested in having practical, interpretable, and usable models as decision-making support for technical staff. This study aimed to analyze predictive modeling of injury risk based on body composition variables and selected physical fitness tests for elite football players through a sports season. The sample comprised 36 male elite football players who competed in the First Portuguese Soccer League in the 2020/2021 season. The models were calculated based on 22 independent variables that included players' information, body composition, physical fitness, and one dependent variable, the number of injuries per season. In the net elastic analysis, the variables that best predicted injury risk were sectorial positions (defensive and forward), body height, sit-and-reach performance, 1 min number of push-ups, handgrip strength, and 35 m linear speed. This study considered multiple-input single-output regression-type models. The analysis showed that the most accurate model presented in this work generates an error of RMSE = 0.591. Our approach opens a novel perspective for injury prevention and training monitorization. Nevertheless, more studies are needed to identify risk factors associated with injury prediction in elite soccer players, as this is a rising topic that requires several analyses performed in different contexts.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.