Minutes Played Should be Used for the Calculation of Session Rating of Perceived Exertion During Matches in NCAA Division I Women’s Soccer Original Research
Main Article Content
Keywords
Training Load, Collegiate, Periodization, Female, GPS
Abstract
Introduction: Monitoring Training Load in soccer is used to achieve the best individualized performance outcomes and to prevent injuries. However, there is no clear recommendation for which ‘match duration’ should be used in the calculation of match Session Rating of Perceived Exertion Training Load (sRPE-TL) in NCAA DI women’s soccer. Therefore, the purpose of this study was to establish a duration standard to be used in the calculation of sRPE-TL in collegiate NCAA DI women’s soccer matches. A secondary aim was to investigate whether multiple positions require the use of different durations for the calculation of sRPE-TL.
Methods: Seventeen athletes (means ± standard deviations: age 20 ± 1.1 yrs., height 170 ± 6.6 cm, weight 64.6 ± 7.0 kg) participated in this study. Repeated measures correlations were used to determine the relationship between the different sRPE-TL calculations and objective variables (e.g., GPS variables and HR-based variable). Data was analyzed using the rmcorr package in R Studio executing R. Alpha was set a-priori at p ≤ 0.05.
Results: The s-RPE-TL using the four ‘minutes played’ durations (‘minutes played only’, ‘warm-up added’, ‘halftime added’, and ‘warm-up and halftime added’) were strongly correlated with TLS (r = .773, .776, .789, .786), total distance (r = .825, .813, .811, .798), number of sprints (r = .716, .717, .712, .711), HSD (r = .608, .615, .609, .612), and mechanical load (r = .738, .738, .734, .732). When separated by positions, the correlations between sRPE-TL and objective data were similar across all four ‘minutes played’ durations.
Conclusions: Any of the ‘minutes played’ durations should be used to calculate match sRPE-TL values for the entire team. Multiple positions do not require the use of different durations for the calculation of sRPE-TL which facilitates sRPE-TL comparisons across positions.
References
2. Schwellnus M, Soligard T, Alonso JM, et al. How much is too much? (Part 2) International Olympic Committee consensus statement on load in sport and risk of illness. Br J Sports Med. 2016;50(17):1043-1052. doi:10.1136/bjsports-2016-096572
3. Soligard T, Schwellnus M, Alonso JM, et al. How much is too much? (Part 1) International Olympic Committee consensus statement on load in sport and risk of injury. Br J Sports Med. 2016;50(17):1030-1041. doi:10.1136/bjsports-2016-096581
4. Bengtsson H, Ekstrand J, Hägglund M. Muscle injury rates in professional football increase with fixture congestion: an 11-year follow-up of the UEFA Champions League injury study. Br J Sports Med. 2013;47(12):743-747.
5. Dellal A, Lago-Peñas C, Rey E, Chamari K, Orhant E. The effects of a congested fixture period on physical performance, technical activity and injury rate during matches in a professional soccer team. Br J Sports Med. 2015;49(6):390-394. doi:10.1136/bjsports-2012-091290
6. Ekstrand J, Hägglund M, Kristenson K, Magnusson H, Waldén M. Fewer ligament injuries but no preventive effect on muscle injuries and severe injuries: an 11-year follow-up of the UEFA Champions League injury study. Br J Sports Med. 2013;47(12):732-737.
7. Rollo I, Impellizzeri FM, Zago M, Iaia FM. Effects of 1 versus 2 games a week on physical and subjective scores of subelite soccer players. International Journal of Sports Physiology and Performance. 2014;9(3):425-431.
8. Brownstein CG, Dent JP, Parker P, et al. Etiology and recovery of neuromuscular fatigue following competitive soccer match-play. Frontiers in physiology. 2017;8:831.
9. Nédélec M, McCall A, Carling C, Legall F, Berthoin S, Dupont G. Recovery in Soccer: Part I – Post-Match Fatigue and Time Course of Recovery. Sports Medicine. 2012;42(12):997-1015. doi:10.2165/11635270-000000000-00000
10. McLaren SJ, Macpherson TW, Coutts AJ, Hurst C, Spears IR, Weston M. The relationships between internal and external measures of training load and intensity in team sports: a meta-analysis. Sports Medicine. 2018;48(3):641-658.
11. Bartlett JD, O’Connor F, Pitchford N, Torres-Ronda L, Robertson SJ. Relationships Between Internal and External Training Load in Team-Sport Athletes: Evidence for an Individualized Approach. International Journal of Sports Physiology and Performance. 2017;12(2):230-234. doi:10.1123/ijspp.2015-0791
12. Burgess DJ. The Research Doesn’t Always Apply: Practical Solutions to Evidence-Based Training-Load Monitoring in Elite Team Sports. International Journal of Sports Physiology and Performance. 2017;12(s2):S2-S2-141. doi:10.1123/ijspp.2016-0608
13. Castillo D, Weston M, McLaren SJ, Cámara J, Yanci J. Relationships Between Internal and External Match-Load Indicators in Soccer Match Officials. International Journal of Sports Physiology and Performance. 2017;12(7):922-927. doi:10.1123/ijspp.2016-0392
14. Scott T, Black CR, Quinn J, Coutts AJ. Validity and Reliability of the Session-RPE Method for Quantifying Training in Australian Football: A Comparison of the CR10 and CR100 Scales. The Journal of Strength & Conditioning Research. 2013;27(1):270-276. doi:10.1519/JSC.0b013e3182541d2e
15. Taylor KL, Weston M, Batterham AM. Evaluating Intervention Fidelity: An Example from a High-Intensity Interval Training Study. PLoS One. 2015;10(4). doi:10.1371/journal.pone.0125166
16. Alexiou H, Coutts AJ. A comparison of methods used for quantifying internal training load in women soccer players. International journal of sports physiology and performance. 2008;3(3):320-330.
17. Foster C, Hector L, Welsh R, Schrager M, Green M, Snyder A. Effects of specific versus cross-training on running performance. Europ J Appl Physiol. 1995;70(4):367-372. doi:10.1007/BF00865035
18. Borresen J, Lambert MI. Quantifying Training Load: A Comparison of Subjective and Objective Methods. International Journal of Sports Physiology and Performance. 2008;3(1):16-30. doi:10.1123/ijspp.3.1.16
19. Barrett S, McLaren S, Spears I, Ward P, Weston M. The influence of playing position and contextual factors on soccer players’ match differential ratings of perceived exertion: a preliminary investigation. Sports. 2018;6(1):13.
20. Foster C, Florhaug J, Franklin J, et al. A new approach to monitoring exercise training. The Journal of Strength & Conditioning Research. 2001;15(1):109-115.
21. Pustina AA, Sato K, Liu C, et al. Establishing a duration standard for the calculation of session rating of perceived exertion in NCAA division I men’s soccer. Journal of Trainology. 2017;6(1):26-30.
22. Scott B, Lockie RG, Knight TJ, Clark AC, de Jonge XAJ. A comparison of methods to quantify the in-season training load of professional soccer players. International journal of sports physiology and performance. 2013;8(2):195-202.
23. McFadden BA, Walker AJ, Bozzini BN, Sanders DJ, Arent SM. Comparison of internal and external training loads in male and female collegiate soccer players during practices vs. games. The Journal of Strength & Conditioning Research. 2020;34(4):969-974.
24. Gregson W, Drust B, Atkinson G, Salvo VD. Match-to-match variability of high-speed activities in premier league soccer. International journal of sports medicine. 2010;31(04):237-242.
25. Bloomfield J, Polman R, O’Donoghue P. Physical demands of different positions in FA Premier League soccer. Journal of sports science & medicine. 2007;6(1):63.
26. Di Salvo V, Baron R, Tschan H, Calderon Montero F, Bachl N, Pigozzi F. Performance Characteristics According to Playing Position in Elite Soccer. Int J Sports Med. 2007;28(3):222-227. doi:10.1055/s-2006-924294
27. Peltonen J, Tuulari E. Polar Team Pro - Portable player tracking system to Increase team performance and prevent injuries. Polar R&D, Research and Technology. Published online October 2018.
28. Huggins RA, Giersch GEW, Belval LN, et al. The Validity and Reliability of Global Positioning System Units for Measuring Distance and Velocity During Linear and Team Sport Simulated Movements. The Journal of Strength & Conditioning Research. 2020;34(11):3070-3077. doi:10.1519/JSC.0000000000003787
29. Gilgen-Ammann R, Schweizer T, Wyss T. RR interval signal quality of a heart rate monitor and an ECG Holter at rest and during exercise. Eur J Appl Physiol. 2019;119(7):1525-1532. doi:10.1007/s00421-019-04142-5
30. Goodie JL, Larkin KT, Schauss S. Validation of the Polar Heart Rate Monitor for Assessing Heart Rate During Physical and Mental Stress. Journal of Psychophysiology. 2000;14(3):159-164. doi:10.1027//0269-8803.14.3.159
31. Weippert M, Kumar M, Kreuzfeld S, Arndt D, Rieger A, Stoll R. Comparison of three mobile devices for measuring R–R intervals and heart rate variability: Polar S810i, Suunto t6 and an ambulatory ECG system. Eur J Appl Physiol. 2010;109(4):779-786. doi:10.1007/s00421-010-1415-9
32. Banister EW. Modeling Elite Athletic Performance. (Green H, McDougal J, Wegner H, eds.). Human Kinectics; 1991.
33. Bland JM, Altman DG. Statistics notes: Calculating correlation coefficients with repeated observations: Part 1--correlation within subjects. BMJ. 1995;310(6977):446-446. doi:10.1136/bmj.310.6977.446
34. Bakdash JZ, Marusich LR. Repeated Measures Correlation. Front Psychol. 2017;8:456. doi:10.3389/fpsyg.2017.00456
35. Ishida A, Travis SK, Draper G, White JB, Stone MH. Player Position Affects Relationship Between Internal and External Training Loads During Division I Collegiate Female Soccer Season. Journal of Strength and Conditioning Research. 2022;36(2):513-517.
36. Barros RML, Misuta MS, Menezes RP, et al. Analysis of the Distances Covered by First Division Brazilian Soccer Players Obtained with an Automatic Tracking Method. J Sports Sci Med. 2007;6(2):233-242.
37. Bradley PS, Carling C, Archer D, et al. The effect of playing formation on high-intensity running and technical profiles in English FA Premier League soccer matches. Journal of Sports Sciences. 2011;29(8):821-830. doi:10.1080/02640414.2011.561868