Sports Performance Tests for Amputee Football Players: A Scoping Review

The usefulness of balance test in preseason evaluation of injuries in amputee football players: a pilot prospective observational study

Background

Low balance ability is generally associated with an increased risk of ligament injuries. It seems that assessing the level of stability in amputee football players can help evaluate the accompanying risk of sports injuries. Thus, the study aimed to examine the usefulness of the balance test in preseason evaluation by calculating between-group differences in stability parameters between injured and non-injured amputee players.

Methods

The study was designed as a pilot prospective observational study. Twenty-five elite amputee football players representing the Polish National Team and the highest division in Polish League completed one-leg preseason balance tests on the Biodex Balance System before the start of the football season. All players in this study were male, with an average age of 29 years (SD = 7.9), a stature of 174.2 cm (SD 5.2) and a body mass of 80.1 kg (SD = 13.1). Then, players were prospectively observed over one football season, and lower leg injury data were prospectively collected through the nine months. The between-group differences were tested using the non-parametric Mann-Whitney U test for players who sustained an injury (yes) and those who did not within the analysed season (no). Overall (OSI), medial-lateral (MLSI), and anterior-posterior stability index (APSI) were analysed as primary outcomes.

Results

The preseason values of the balance tests were not predictive (p > 0.05) regarding sustaining an injury during the season. No between-group differences were noted for any analysed outcomes (p values ranged from 0.093 to 0.453).

Conclusions

Although static balance tasks offer a chance to make a preliminary assessment of injury prediction in amputee footballers, in overall, the balance test results cannot be regarded as the sole predictive injury risk factor in amputee football.

Developing a Multicriteria Decision-Making Model Based on a Three-Layer Virtual Internet of Things Algorithm Model to Rank Players’ Value

This paper proposes a multicriteria decision-making model based on a three-layer virtual internet of things (IoT) algorithm to automatically track and evaluate professional football players’ performance over the Internet. The three layers were respectively related to (1) automated data reading, (2) the players’ comprehensive grey relational degree calculation, and (3) the players’ classification. The methodology was applied in the context of the COVID-19 pandemic to investigate the performance of the top 10 defenders (according to The Sun, an internationally renowned sports website) in the European leagues, participating in the knockout phase of the 2019–20 UEFA Champions League. The results indicate that Virgil van Dijk of Liverpool FC was the best defender, followed by Harry Maguire of Manchester United, and Sergio Ramos of Real Madrid in the second and third positions, respectively. However, this ranking contradicted that of The Sun’s, which ranked these defenders in the seventh, tenth, and eighth positions, respectively. These results can help club management, coaches, and teams negotiate price positioning and future contract renewals or player transfers.

Editorial: New Training Strategies and Evaluation Methods for Improving Health and Physical Performance

Physical activity is among the most effective methods for improving health, body composition, and physical function, and its practice is suitable for every population [...].