A Systematic Review and Meta-Analysis of Wearable Satellite System Technology for Linear Sprint Profiling: Technological Innovations and Practical Applications

ABSTRACT

Cormier, P, Meylan, C, Agar-Newman, D, Geneau, D, Epp-Stobbe, A, Lenetsky, S, and Klimstra, M. A systematic review and meta-analysis of wearable satellite system technology for linear sprint profiling: technological innovations and practical applications. J Strength Cond Res 38(2): 405-418, 2024-An emerging and promising practice is the use of global navigation satellite system (GNSS) technology to profile team-sports athletes in training and competition. Therefore, the purpose of this narrative systematic review with meta-analysis was to evaluate the literature regarding satellite system sensor usage for sprint modeling and to consolidate the findings to evaluate its validity and reliability. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, an electronic search of the databases, PubMed and SPORTDiscus (EBSCO), was conducted. Concurrent validity and reliability studies were considered, and 16 studies were retained for the review from the initial 1,485 studies identified. The effects on outcomes were expressed as standardized mean differences (SMDs, Cohen's d ) for each outcome (i.e., maximal sprint speed [MSS], the acceleration constant [τ], maximal theoretical velocity [ V0 ], relative force [ F0 ], and relative power [P max ]). Effect magnitudes represented the SMD between GNSS-derived and criterion-derived (i.e., radar and laser) and resulted in the following estimates: small for MSS ( d = 0.22, 95% CI 0.01 to 0.42), τ ( d = -0.18, 95% CI -0.60 to 0.23), V0 ( d = 0.14, 95% CI -0.08 to 0.36), relative F0 ( d = 0.15, 95% CI -0.25 to 0.55), and relative P max ( d = 0.21, 95% CI -0.16 to 0.58). No publication bias was identified in meta-analyzed studies and moderator analysis revealed that several factors (sampling rate and sensor manufacturer) influenced the results. Heterogeneity between studies was considered moderate to high. This highlighted the differences between studies in sensor technology differences (i.e., sampling rate, sensor fusion, and satellite network acquisition), processing techniques, criterion technology used, sprint protocols, outcome reporting, and athlete characteristics. These findings may be useful in guiding improvements in sprint modeling using GNSS technology and enable more direct comparisons in future research. Implementation of all-out linear sprint efforts with GNSS technology can be integrated into sport-specific sessions for sprint modeling when robust and consistent data processing protocols are performed, which has important implications for fatigue monitoring, program design, systematic testing, and rehabilitation in individual and team sports.

The Influence of Physical Contact on Athlete Load in International Female Rugby Sevens

ABSTRACT

Epp-Stobbe, A, Tsai, M-C, Morris, C, and Klimstra, M. The influence of physical contact on athlete load in international female rugby sevens. J Strength Cond Res 37(2): 383-387, 2023-Although self-reported rate of perceived exertion (RPE) is a simple and popular metric for monitoring player loads, this holistic measure may not adequately represent the distinct contributing factors to athlete loading in team sports, such as contact load. The purpose of this investigation is to determine the relationship between the number of contacts experienced and playing time on RPE in elite women's rugby sevens athletes during competition. Additionally, we examine the contribution of the number of contacts and playing time to RPE. The data collected included RPE, playing time, and number of contacts from 1 team participating in 74 international women's sevens matches. The relationship was modeled using multiple linear regression. Results, including the coefficients for the number of contacts and playing time, were significant (p < 0.001), and R2adjusted was 0.3063. Because contacts are accounted for within the measure of RPE in the proposed model, this further supports the value of RPE as a global measure of athlete experience. However, this study has found a different relationship between RPE and playing time dependent on the number of contacts, such that the influence of playing time on RPE decreases as the number of contacts increase. Ultimately, this may mean that the weighting of individual salient factors affecting player loads, such as the number of contacts or playing time, depend on the levels of all known and potentially unknown factors experienced and may limit the use of RPE when contextualizing player load across athletes. Taken together, the findings suggest that the number of contacts, playing time, and RPE should be considered when monitoring athlete loads while further substantiating the need for more, and higher resolution, measures to better quantify competition loads in contact team sports.

Concurrent Validity and Reliability of Different Technologies for Sprint-Derived Horizontal Force-Velocity-Power Profiling

ABSTRACT

Cormier, P, Tsai, M-C, Meylan, C, Agar-Newman, D, Epp-Stobbe, A, Kalthoff, Z, and Klimstra, M. Concurrent validity and reliability of different technologies for sprint-derived horizontal force-velocity-power profiling. J Strength Cond Res XX(X): 000-000, 2022-This study evaluated the validity and reliability of common systems to assess sprint-derived horizontal force-velocity-power (FVPH) profile metrics. Two double constellation athlete monitoring systems (STATSports Apex, Catapult Vector S7) and one timing gate system were compared with a radar gun for the computation of FVPH metrics. Intersystem validity was assessed using intraclass correlation coefficients (ICC), Pearson's correlation coefficients (R2), and Bland-Altman plots with absolute and percent agreement. Intrasystem reliability was assessed with agreement bias and ICC. STATSports demonstrated moderate agreement for F0, Pmax, τ, and Drf (8.62, 6.46, -9.81, and 9.96%, respectively) and good agreement for V0 and MSS (-2.18 and -1.62%). Catapult displayed good agreement across all metrics (F0, V0, Pmax, MSS, τ, and Drf: -0.96, -0.89, -1.85, -0.84, 0.38, and -0.27%, respectively). Timing gates demonstrated good agreement with V0 and MSS (-2.62 and -1.71%) and poor agreement with F0, Pmax, τ, and Drf (19.17, 16.64, -20.49, and 20.18%, respectively). Intrasystem reliability demonstrated good agreement (<2% bias) with very large to near-perfect ICC (0.84-0.99) for Catapult and STATSports systems. Overall, GPS/GNSS 10 Hz technology is reliable across devices and can provide moderate-to-good accuracy of FVPH metrics in single maximal effort sprints. However, Catapult provided better agreement for more FVPH metrics than STATSports, which may be related to differences in proprietary algorithms. Also, modeling timing gate data using current FVPH profiling techniques results in poor bias that requires greater investigation. GPS/GNSS data can be used for FVPH profiling, which could inform performance and rehabilitation processes.