Aldo Di Martino, Silvana Mirella Aliberti, Daria Nurzynska, Raffaele Canonico, Gennaro De Luca, Angelo Gioffredi, Clotilde Castaldo, Franca Di Meglio
Post-match thermal asymmetries are highly prevalent in elite youth soccer and appear to reflect dynamic, load-dependent recovery responses rather than stable thermal phenotypes. Longitudinal thermographic monitoring may help characterise individual recovery patterns when interpreted alongside other monitoring tools.
BACKGROUND: Evidence regarding the longitudinal use of infrared thermography in elite under-18 soccer players remains limited. Most previous studies have relied on cross-sectional designs or short observation periods.
METHODS: This prospective longitudinal observational study monitored 18 elite under-18 male outfield soccer players across 16 official matches (96 valid assessments). Thermographic evaluations were performed 48 h post-match under standardized conditions across six bilateral lower-limb regions. A thermal asymmetry was defined as relevant if ΔTsk ≥ 0.5 °C. Linear mixed-effects models, paired t-tests and chi-square tests were used for statistical analysis.
RESULTS: Relevant asymmetries were detected in 79.2% of assessments (mean maximum ΔTsk 0.77 ± 0.43 °C). Posterior Thigh BF (40.6%) and Posterior Thigh ST (35.4%) showed the highest prevalence (χ2 = 16.31, p = 0.006). Significant side-to-side differences were found for Anterior Thigh (p = 0.004), Adductor (p = 0.039) and Posterior Thigh BF (p = 0.032). The intraclass correlation coefficient for Thermal Asymmetry Burden was very low (ICC = 0.024). Fifteen athletes (83.3%) showed recurrent asymmetry and 13 (72.2%) showed a recurrent same-region pattern. Match-to-match variation in TAB was significant (Kruskal-Wallis p = 0.025; ANOVA p = 0.011). No time-loss muscle injuries occurred.
CONCLUSIONS: Post-match thermal asymmetries are highly prevalent in elite youth soccer and appear to reflect dynamic, load-dependent recovery responses rather than stable thermal phenotypes. Longitudinal thermographic monitoring may help characterise individual recovery patterns when interpreted alongside other monitoring tools.