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This study aimed to use a data-driven approach to identify individualized speed thresholds to characterize running demands and athlete workload during games and practices in skill and linemen football players. Data were recorded from wearable sensors over 28 sessions from 30 male Canadian varsity football athletes, resulting in a total of 287 performances analyzed, including 137 games and 150 practices, using a global positioning system. Speed zones were identified for each performance by fitting a 5-dimensional Gaussian mixture model (GMM) corresponding to 5 running intensity zones from minimal (zone 1) to maximal (zone 5). Skill players had significantly higher (p < 0.001) speed thresholds, percentage of time spent, and distance covered in maximal intensity zones compared to linemen. The distance covered in game settings was significantly higher (p < 0.001) compared to practices. This study highlighted the use of individualized speed thresholds to determine running intensity and athlete workloads for American and Canadian football athletes, as well as compare running performances between practice and game scenarios. This approach can be used to monitor physical workload in athletes with respect to their tactical positions during practices and games, and to ensure that athletes are adequately trained to meet in-game physical demands.

PurposeSubconcussive head impacts during contact sports are challenging to identify and their consequences remain elusive. Impaired autonomic nervous system responses involving altered cardiac dynamics have been reported following mild traumatic brain injury but remain underexplored in contact sports. This study monitored online effects of head impact exposure on athletes’ cardiovascular function during a Varsity Canadian football season.MethodsHeart rate recovery (HRR) segments (n=225) were extracted from 11 skill players (median [IQR] age: 23 [2] years; body mass index: 26 [1] kg/m²) equipped with two wearable sensors recording accelerations, heart rate, velocity, estimated metabolic energy expenditure, and fast head acceleration events (HAE). The heart signal derivative was used to detect HRR segments which were then matched with the number and intensity of HAE previously sustained during the game.ResultsFollowing a single HAE above 40 g, the median HRR (ΔHR/Δt=0.461 bpm/s, n=23 segments) decreased of 19% (p=0.005) compared to segments prior to the event (ΔHR/Δt=0.569 bpm/s, n=182 segments). This reduction was also observed with HAE as low as 20 g (0.474 bpm/s, n=42 segments; 30% reduction; p= 4.30e-08, figure 1). These were neither correlated with metabolic energy expenditure (R²=0.009, p=0.541) nor with peak running velocity reached before HAE (R²=4e-04, p=0.896).Abstract 83 Figure 1Heart rate recovery rates for segments binned by upper bounds for peak linear acceleration of 10 g (i.e., no head acceleration event – HAE –, leftmost), up to 20 g (second box), up to 30 g (third box), up to 40 g (fourth box) and 40 g and up (last box on the right). Significance test: Kruskal-Wallis rank sum test relative to the «no impacts» sample, thresholds: * = 0.05, ** = 0.01, *** = 0.001[Figure omitted. See PDF]ConclusionThis demonstrates a possible direct relationship between HAE starting at 20 g and disturbed cardiac response. Given the repetitive nature of subconcussive hits beyond this ≥ 20g threshold, there is an urgent need to investigate whether or how altered heart rate kinetics could influence severity of head injury in contact sports.