Relating Individual And Training Load Factors To Adaptations Over The Collegiate Men’s Soccer Season

Soccer organizations have begun to integrate cutting edge technologies into athlete ]monitoring strategies in order to reduce injury risk and enhance performance. The Landing Error Scoring System (LESS) is a neuromuscular control assessment of 17 biomechanical risk factors which can be automatically evaluated using motion capture software. This investigation sought to determine if significant changes in LESS scores occur over a competitive Division-1 men’s college soccer season and whether these changes coincide with training status indicators. Although wearable technologies have become more prevalent in college men’s soccer, there is limited information regarding training load indicators and relationships with established measures of performance. Consequently, this investigation also aimed to determine which training load indicator was the best predictor of countermovement jump (CMJ) performance over the competitive men’s soccer season. Twenty-six healthy men’s soccer field position players (age: 20.3 ±1.4 years, height: 181.5 ± 6.4 cm) were assessed for changes in LESS and CMJ across the competitive season. Training load data were collected from GPS, accelerometer, and heart rate devices during the 6 days prior to each visit. Generalized linear mixed effects models were used to analyze longitudinal trends in both LESS and CMJ as well as identify significant predictors. LESS scores were significantly elevated at the end of preseason training and significantly related to resting heart rate and CMJ. Although significant relationships were found between a number of training load indicators, model fit indices determined distance covered above 6 m•s-1 to be the best predictor of CMJ. The elevation in LESS scores following preseason training combined with the identification of RHR and CMJ as significant predictors of LESS performance further support the link between overtraining and injury risk. CMJ performance is best predicted by maintenance of high intensity performance across the college soccer season.