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Cormier P, Meylan C, Agar-Newman D, Geneau D, Epp-Stobbe A, Lenetsky S, 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 2024; 38:405-418. [PMID: 38088913 DOI: 10.1519/jsc.0000000000004689] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
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.
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Affiliation(s)
- Patrick Cormier
- Canadian Sport Institute Pacific, Victoria, British Columbia, Canada
- School of Exercise Science, Physical and Health Education, University of Victoria, Victoria, British Columbia, Canada
- Health and Athletic Performance Department, Canada Soccer, Ottawa, Ontario, Canada
| | - César Meylan
- Canadian Sport Institute Pacific, Victoria, British Columbia, Canada
- School of Kinesiology, University of British Columbia, Vancouver, British Columbia, Canada
- Toronto Football Club, Health and Performance Department, Toronto, Ontario, Canada; and
| | - Dana Agar-Newman
- Canadian Sport Institute Pacific, Victoria, British Columbia, Canada
- School of Exercise Science, Physical and Health Education, University of Victoria, Victoria, British Columbia, Canada
| | - Daniel Geneau
- Canadian Sport Institute Pacific, Victoria, British Columbia, Canada
- School of Exercise Science, Physical and Health Education, University of Victoria, Victoria, British Columbia, Canada
| | - Amarah Epp-Stobbe
- Canadian Sport Institute Pacific, Victoria, British Columbia, Canada
- School of Exercise Science, Physical and Health Education, University of Victoria, Victoria, British Columbia, Canada
| | - Seth Lenetsky
- Canadian Sport Institute Pacific, Victoria, British Columbia, Canada
- Toronto Football Club, Health and Performance Department, Toronto, Ontario, Canada; and
| | - Marc Klimstra
- Canadian Sport Institute Pacific, Victoria, British Columbia, Canada
- School of Exercise Science, Physical and Health Education, University of Victoria, Victoria, British Columbia, Canada
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Miguens N, Brocherie F, Moulié L, Milhet P, Bon M, Lassus P, Toussaint JF, Sedeaud A. Individual In-Situ GPS-Derived Acceleration-Speed Profiling: Toward Automatization and Refinement in Male Professional Rugby Union Players. SPORTS MEDICINE - OPEN 2024; 10:6. [PMID: 38206549 PMCID: PMC10784250 DOI: 10.1186/s40798-023-00672-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Accepted: 12/21/2023] [Indexed: 01/12/2024]
Abstract
BACKGROUND Recently a proof-of-concept was proposed to derive the soccer players' individual in-situ acceleration-speed (AS) profile from global positioning system (GPS) data collected over several sessions and games. The present study aimed to propose an automatized method of individual GPS-derived in-situ AS profiling in a professional rugby union setting. METHOD AS profiles of forty-nine male professional rugby union players representing 61.5 million positions, from which acceleration was derived from speed during 51 training sessions and 11 official games, were analyzed. A density-based clustering algorithm was applied to identify outlier points. Multiple AS linear relationships were modeled for each player and session, generating numerous theoretical maximal acceleration (A0), theoretical maximal running speed (S0) and AS slope (ASslope, i.e., overall orientation of the AS profile). Each average provides information on the most relevant value while the standard deviation denotes the method accuracy. In order to assess the reliability of the AS profile within the data collection period, data were compared over two 2-week phases by the inter-class correlation coefficient. A0 and S0 between positions and type of sessions (trainings and games) were compared using ANOVA and post hoc tests when the significant threshold had been reached. RESULTS All AS individual profiles show linear trends with high coefficient of determination (r2 > 0.81). Good reliability (Inter-class Correlation Coefficient ranging from 0.92 to 0.72) was observed between AS profiles, when determined 2 weeks apart for each player. AS profiles depend on players' positions, types of training and games. Training and games data highlight that highest A0 are obtained during games, while greatest S0 are attained during speed sessions. CONCLUSIONS This study provides individual in-situ GPS-derived AS profiles with automatization capability. The method calculates an error of measurement for A0 and S0, of paramount importance in order to improve their daily use. The AS profile differences between training, games and playing positions open several perspectives for performance testing, training monitoring, injury prevention and return-to-sport sequences in professional rugby union, with possible transferability to other sprint-based sports. KEY POINTS AS profiles computed from rugby union GPS data provide positional benchmarks during training and competition. This study provides automatic detection of atypical data and the computation of error measurement of theoretical maximal acceleration and speed components. This refinement constitutes a step forward for a daily use of ecological data by considering data collection and method reliabilities. This easy-to-implement approach may facilitate its use to the performance management process (talent identification, training monitoring and individualization, return-to-sport).
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Affiliation(s)
- Nathan Miguens
- IRMES - URP 7329, Institut de Recherche Médicale Et d'Epidémiologie du Sport, Université de Paris Cité, 11 Avenue du Tremblay, 75012, Paris, France
- Institut National du Sport, de l'Expertise Et de La Performance (INSEP), Paris, France
| | - Franck Brocherie
- Laboratory Sport, Expertise and Performance (EA 7370), French Institute of Sport, Paris, France
| | - Loïc Moulié
- Stade Montois Rugby Pro, 270 Avenue du Stade, 40 000, Mont De Marsan, France
| | - Patrick Milhet
- Stade Montois Rugby Pro, 270 Avenue du Stade, 40 000, Mont De Marsan, France
| | - Mathieu Bon
- Stade Montois Rugby Pro, 270 Avenue du Stade, 40 000, Mont De Marsan, France
| | - Pierre Lassus
- Stade Montois Rugby Pro, 270 Avenue du Stade, 40 000, Mont De Marsan, France
| | - Jean-François Toussaint
- IRMES - URP 7329, Institut de Recherche Médicale Et d'Epidémiologie du Sport, Université de Paris Cité, 11 Avenue du Tremblay, 75012, Paris, France
- Institut National du Sport, de l'Expertise Et de La Performance (INSEP), Paris, France
- Centre d'Investigation en Médecine du Sport, Assistance Publique - Hôpitaux de Paris, Hôtel-Dieu, Paris, France
| | - Adrien Sedeaud
- IRMES - URP 7329, Institut de Recherche Médicale Et d'Epidémiologie du Sport, Université de Paris Cité, 11 Avenue du Tremblay, 75012, Paris, France.
- Institut National du Sport, de l'Expertise Et de La Performance (INSEP), Paris, France.
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Cormier P, Tsai MC, Meylan C, Soares VHT, Clarke DC, Klimstra M. Minimal Number of Events Required for Acceleration-Speed Profiling in Elite Women's Soccer. Int J Sports Physiol Perform 2023; 18:1457-1460. [PMID: 37741637 DOI: 10.1123/ijspp.2023-0223] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Revised: 08/18/2023] [Accepted: 08/21/2023] [Indexed: 09/25/2023]
Abstract
PURPOSE To determine the minimum number of events (training or matches) for producing valid acceleration-speed (AS) profiles from global navigation satellite system (GNSS) data. METHODS Nine elite female soccer players participated in a 4-week training camp consisting of 19 events. AS profile metrics calculated from different combinations of athlete events were compared to force-velocity (FV) profile metrics from 2 × 40-m stand-alone sprint effort trials, using the same GNSS 10-Hz technology. Force-velocity profiles were calculated, from which AS profiles were obtained. AS profiles from training and matches were generated by plotting acceleration and speed points and performing a regression through the maximal points to obtain the AS metrics (theoretical maximal speed, x-intercept [in meters per second], theoretical maximal acceleration, y-intercept [in meters per second squared], and the slope per second). A linear mixed model was performed with the AS metrics as the outcome variables, the number of events as a fixed effect, and the participant identifier as a mixed effect. Dunnett post hoc multiple comparisons were used to compare the means of each number of event grouping (1-19 events) to those estimated from the dedicated sprint test. RESULTS Theoretical maximal speed and theoretical maximal acceleration means were no longer significantly different from the isolated sprint reference with 9 to 19 (small to trivial differences = -0.31 to -0.04 m·s-1, P = .12-.99) and 6 to 19 (small differences = -0.4 to -0.28 m·s-2, P = .06-.79) events, and the slopes were no longer different with 1 to 19 events (trivial differences = 0.06-0.03 s-1, P = .35-.99). CONCLUSIONS AS profiles can be estimated from a minimum of 9 days of tracking data. Future research should investigate methodology resulting in AS profiles estimated from fewer events.
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Affiliation(s)
- Patrick Cormier
- Canadian Sport Institute Pacific, Victoria, BC, Canada
- School of Exercise Science, Physical and Health Education, University of Victoria, Victoria, BC, Canada
- Health and Athletic Performance Department, Canada Soccer, Ottawa, ON, Canada
| | | | - Cesar Meylan
- Canadian Sport Institute Pacific, Victoria, BC, Canada
- Health and Athletic Performance Department, Canada Soccer, Ottawa, ON, Canada
- School of Kinesiology, University of British Columbia, Vancouver, BC, Canada
| | - Victor H T Soares
- Laboratory of Alternative Energy Conversion, Simon Fraser University, Surrey, BC, Canada
| | - David C Clarke
- Canadian Sport Institute Pacific, Victoria, BC, Canada
- Department of Biomedical Physiology and Kinesiology, Simon Fraser University, Burnaby, BC, Canada
- SFU Sports Analytics Group, Simon Fraser University, Burnaby, BC, Canada
| | - Marc Klimstra
- Canadian Sport Institute Pacific, Victoria, BC, Canada
- School of Exercise Science, Physical and Health Education, University of Victoria, Victoria, BC, Canada
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Vantieghem-Nicolas L, Morin JB, Cotte T, Sangnier S, Rossi J. Concurrent Validity and Reliability of the Sprint Force-Velocity Profile Assessed with K-AI Wearable Tech. SENSORS (BASEL, SWITZERLAND) 2023; 23:8189. [PMID: 37837018 PMCID: PMC10575115 DOI: 10.3390/s23198189] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 09/10/2023] [Accepted: 09/26/2023] [Indexed: 10/15/2023]
Abstract
Establishing a sprint acceleration force-velocity profile is a way to assess an athlete's sprint-specific strength and speed production capacities. It can be determined in field condition using GNSS-based (global navigation satellite system) devices. The aims of this study were to (1) assess the inter-unit and the inter-trial reliability of the force-velocity profile variables obtained with K-AI Wearable Tech devices (50 Hz), (2) assess the concurrent validity of the input variables (maximal sprint speed and acceleration time constant), and (3) assess the validity of the output variables (maximal force output, running velocity and power). Twelve subjects, including one girl, performed forty-one 30 m sprints in total, during which the running speed was measured using two GPS (global positioning system) devices placed on the upper back and a radar (Stalker® Pro II Sports Radar Gun). Concurrent validity, inter-device and inter-trial reliability analyses were carried out for the input and output variables. Very strong to poor correlation (0.99 to 0.38) was observed for the different variables between the GPS and radar devices, with typical errors ranging from small to large (all < 7.6%). Inter-unit reliability was excellent to moderate depending on the variable (ICC values between 0.65 and 0.99). Finally, for the inter-trial reliability, the coefficients of variation were low to very low (all < 5.6%) for the radar and the GPS. The K-AI Wearable Tech used in this study is a concurrently valid and reliable alternative to radar for assessing a sprint acceleration force-velocity profile.
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Affiliation(s)
- Laurine Vantieghem-Nicolas
- Université Jean Monnet Saint-Etienne, Lyon 1, Université Savoie Mont-Blanc, Laboratoire Interuniversitaire de Biologie de la Motricité, F-42023 Saint-Etienne, France; (L.V.-N.); (S.S.); (J.R.)
| | - Jean-Benoit Morin
- Université Jean Monnet Saint-Etienne, Lyon 1, Université Savoie Mont-Blanc, Laboratoire Interuniversitaire de Biologie de la Motricité, F-42023 Saint-Etienne, France; (L.V.-N.); (S.S.); (J.R.)
| | - Thierry Cotte
- ASSE, Cellule d’aide à la Performance, F-42000 Saint-Etienne, France
| | - Sébastien Sangnier
- Université Jean Monnet Saint-Etienne, Lyon 1, Université Savoie Mont-Blanc, Laboratoire Interuniversitaire de Biologie de la Motricité, F-42023 Saint-Etienne, France; (L.V.-N.); (S.S.); (J.R.)
| | - Jeremy Rossi
- Université Jean Monnet Saint-Etienne, Lyon 1, Université Savoie Mont-Blanc, Laboratoire Interuniversitaire de Biologie de la Motricité, F-42023 Saint-Etienne, France; (L.V.-N.); (S.S.); (J.R.)
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