Does Placement of Timing Sensors and Sprinting Model Alter Force–Velocity Metrics? A GNSS Simulation Study

Horizontal force–velocity profiling (FV) has become a prominent approach to evaluate sprinting performance and force/power characteristics in athletes. As optical timing gates (TGs) are the most prevalent and accessible athlete sprint testing measurement devices, initial FV applications involved measuring sprint performance using TGs placed at the 0.75, 10, 15, 20, 30, and 40 m marks during all-out sprint testing sessions. However, there was uncertainty as to the standardization in the number, placement, and total distance of TG measurements to determine FV outputs. While original investigations have attempted to determine optimal TG measurement configurations, they have not been compared to continuous velocity measurements, nor have they been subject to a statistical optimization approach. Therefore, the objective of this study is to use simulated TG locations, derived from continuous GNSS velocity measurements, to identify the shortest distance with the minimum number of optimal timing-gate locations to obtain accurate estimates of FV metrics. A total of 49 elite women’s rugby sevens athletes performed 40 m sprint tests between 2015 and 2020. Data were collected using GNSS units (STATSports, Ireland), with athlete split times extracted every 2.5 m interval for the first 10 m, and every 5 m for the remainder of the sprint to simulate timing gates. FV metrics and times generated for all the combinations were compared to the standard model and GNSS models, respectively, using a one-way repeated measures analysis of variance (ANOVA) model. The shortest distance with an average percentage difference 0.27% (RMSE 1.43) for the standard model and 0.43% (RMSE 0.08) for the GNSS models were [0.75, 10-15-25] and [0.75, 5-10-30] combinations, respectively, across all FV measures. For individual FV metrics, different combinations can provide better estimations, indicating that certain regions of the sprint are required for the determination of specific metrics. Within this cohort, the best TG combinations for linear sprint testing are 10 to 15 m shorter than the current suggested combination, using three fewer gates. Further, alternative combinations may offer greater accuracy for specific FV metrics. This work provides an approach for the determination of the most accurate TG locations for teams with constraints on time, money, and equipment.