Preprint / Version 2

Bias in estimated short sprint profiles using timing gates due to the flying start

Simulation study and proposed solutions

##article.authors##

DOI:

https://doi.org/10.51224/SRXIV.179

Keywords:

sprinting, speed, modeling, bias

Abstract

Short sprints have been modeled using the mono-exponential equation that involves two parameters: (1) maximum sprinting speed (MSS) and (2) relative acceleration (TAU), most often performed using the timing gates. I have named this the No correction model. Unfortunately, due to the often utilized flying start, a bias is introduced when estimating parameters. In this paper, I have (1) proposed two additional models (Estimated TC and Estimated FD) that aim to correct this bias, and (2) provided a theoretical simulation study that provides model performances in estimating parameters. In conclusion, both Estimated TC and Estimated FD models provided more precise parameter estimates, but surprisingly, the No correction model provided better estimates of some parameter changes.

Metrics

Metrics Loading ...

References

Allaire J, Xie Y, McPherson J, Luraschi J, Ushey K, Atkins A, Wickham H, Cheng J, Chang W, Iannone R. 2022. Rmarkdown: Dynamic documents for r.

Altmann S, Hoffmann M, Kurz G, Neumann R, Woll A, Haertel S. 2015. Different Starting Distances Affect 5-m Sprint Times. Journal of Strength and Conditioning Research 29:2361–2366. DOI: 10.1519/JSC.0000000000000865.

Altmann S, Spielmann M, Engel FA, Neumann R, Ringhof S, Oriwol D, Haertel S. 2017. Validity of Single-Beam Timing Lights at Different Heights. Journal of Strength and Conditioning Research 31:1994–1999. DOI: 10.1519/JSC.0000000000001889.

Altmann S, Spielmann M, Engel FA, Ringhof S, Oriwol D, Härtel S, Neumann R. 2018. Accuracy of single beam timing lights for determining velocities in a flying 20-m sprint: Does timing light height matter? Journal of Human Sport and Exercise 13. DOI: 10.14198/jhse.2018.133.10.

Brown TD, Vescovi JD, Vanheest JL. 2004. Assessment of linear sprinting performance: A theoretical paradigm. Journal of Sports Science & Medicine 3:203–210.

Buchheit M, Samozino P, Glynn JA, Michael BS, Al Haddad H, Mendez-Villanueva A, Morin JB. 2014. Mechanical determinants of acceleration and maximal sprinting speed in highly trained young soccer players. Journal of Sports Sciences 32:1906–1913. DOI: 10.1080/02640414.2014.965191.

Clark KP, Rieger RH, Bruno RF, Stearne DJ. 2017. The NFL Combine 40-Yard Dash: How Important is Maximum Velocity? Journal of Strength and Conditioning Research:1. DOI: 10.1519/JSC.0000000000002081.

Edwards T, Piggott B, Banyard HG, Haff GG, Joyce C. 2020. Sprint acceleration characteristics across the Australian football participation pathway. Sports Biomechanics:1–13. DOI: 10.1080/14763141.2020.1790641.

Elzhov TV, Mullen KM, Spiess A-N, Bolker B. 2022. Minpack.lm: R interface to the levenberg-marquardt nonlinear least-squares algorithm found in MINPACK, plus support for bounds.

Furlan L, Sterr A. 2018. The Applicability of Standard Error of Measurement and Minimal Detectable Change to Motor Learning Research—A Behavioral Study. Frontiers in Human Neuroscience 12:95. DOI: 10.3389/fnhum.2018.00095.

Furusawa K, Hill AV, Parkinson JL. 1927. The dynamics of "sprint" running. Proceedings of the Royal Society of London. Series B, Containing Papers of a Biological Character 102:29–42. DOI: 10.1098/rspb.1927.0035.

Goerg GM. 2022. LambertW: Probabilistic models to analyze and gaussianize heavy-tailed, skewed data.

Haugen TA, Breitschädel F, Samozino P. 2020. Power-Force-Velocity Profiling of Sprinting Athletes: Methodological and Practical Considerations When Using Timing Gates. Journal of Strength and Conditioning Research 34:1769–1773. DOI: 10.1519/JSC.0000000000002890.

Haugen TA, Breitschädel F, Seiler S. 2019. Sprint mechanical variables in elite athletes: Are force-velocity profiles sport specific or individual? PLOS ONE 14:e0215551. DOI: 10.1371/journal.pone.0215551.

Haugen TA, Breitschädel F, Seiler S. 2020. Sprint mechanical properties in soccer players according to playing standard, position, age and sex. Journal of Sports Sciences 38:1070–1076. DOI: 10.1080/02640414.2020.1741955.

Haugen T, Buchheit M. 2016. Sprint Running Performance Monitoring: Methodological and Practical Considerations. Sports Medicine 46:641–656. DOI: 10.1007/s40279-015-0446-0.

Haugen TA, Tønnessen E, Seiler SK. 2012. The Difference Is in the Start: Impact of Timing and Start Procedure on Sprint Running Performance: Journal of Strength and Conditioning Research 26:473–479. DOI: 10.1519/JSC.0b013e318226030b.

Jiménez-Reyes P, Samozino P, García-Ramos A, Cuadrado-Peñafiel V, Brughelli M, Morin J-B. 2018. Relationship between vertical and horizontal force-velocity-power profiles in various sports and levels of practice. PeerJ 6:e5937. DOI: 10.7717/peerj.5937.

Jovanović M. 2020. Bmbstats: Bootstrap Magnitude-based Statistics for Sports Scientists. Mladen Jovanović.

Jovanović M. 2022. Shorts: Short sprints.

Jovanović M, Vescovi JD. 2020. Shorts: An R Package for Modeling Short Sprints. Accepted to International Journal of Strength and Conditioning (IJSC).

Kruschke JK. 2015. Doing Bayesian data analysis: A tutorial with R, JAGS, and Stan. Boston: Academic Press.

Kruschke JK. 2018. Rejecting or Accepting Parameter Values in Bayesian Estimation. Advances in Methods and Practices in Psychological Science 1:270–280. DOI: 10.1177/2515245918771304.

Kruschke JK, Liddell TM. 2018a. Bayesian data analysis for newcomers. Psychonomic Bulletin & Review 25:155–177. DOI: 10.3758/s13423-017-1272-1.

Kruschke JK, Liddell TM. 2018b. The Bayesian New Statistics: Hypothesis testing, estimation, meta-analysis, and power analysis from a Bayesian perspective. Psychonomic Bulletin & Review 25:178–206. DOI: 10.3758/s13423-016-1221-4.

Makowski D, Ben-Shachar M, Lüdecke D. 2019. bayestestR: Describing Effects and their Uncertainty, Existence and Significance within the Bayesian Framework. Journal of Open Source Software 4:1541. DOI: 10.21105/joss.01541.

Mangine GT, Hoffman JR, Gonzalez AM, Wells AJ, Townsend JR, Jajtner AR, McCormack WP, Robinson EH, Fragala MS, Fukuda DH, Stout JR. 2014. Speed, Force, and Power Values Produced From Nonmotorized Treadmill Test Are Related to Sprinting Performance: Journal of Strength and Conditioning Research 28:1812–1819. DOI: 10.1519/JSC.0000000000000316.

Marcote-Pequeño R, García-Ramos A, Cuadrado-Peñafiel V, González-Hernández JM, Gómez MÁ, Jiménez-Reyes P. 2019. Association Between the Force and Performance Variables Obtained in Jumping and Sprinting in Elite Female Soccer Players. International Journal of Sports Physiology and Performance 14:209–215. DOI: 10.1123/ijspp.2018-0233.

Morin JB. 2017.A spreadsheet for Sprint acceleration Force-Velocity-Power profiling. Available at https://jbmorin.net/2017/12/13/a-spreadsheet-for-sprint-acceleration-force-velocity-power-profiling/ (accessed October 27, 2020).

Morin J-B, Samozino P. 2019. Spreadsheet for Sprint acceleration force-velocity-power profiling.

Morin J-B, Samozino P, Murata M, Cross MR, Nagahara R. 2019. A simple method for computing sprint acceleration kinetics from running velocity data: Replication study with improved design. Journal of Biomechanics 94:82–87. DOI: 10.1016/j.jbiomech.2019.07.020.

Motulsky H. 2018. Intuitive biostatistics: A nonmathematical guide to statistical thinking. New York: Oxford University Press.

R Core Team. 2022. R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing.

Samozino P, Rabita G, Dorel S, Slawinski J, Peyrot N, Saez de Villarreal E, Morin J-B. 2016. A simple method for measuring power, force, velocity properties, and mechanical effectiveness in sprint running: Simple method to compute sprint mechanics. Scandinavian Journal of Medicine & Science in Sports 26:648–658. DOI: 10.1111/sms.12490.

Stenroth L, Vartiainen P. 2020. Spreadsheet for sprint acceleration force-velocity-power profiling with optimization to correct start time. DOI: 10.13140/RG.2.2.12841.83045.

Stenroth L, Vartiainen P, Karjalainen PA. 2020. Force-velocity profiling in ice hockey skating: Reliability and validity of a simple, low-cost field method. Sports Biomechanics:1–16. DOI: 10.1080/14763141.2020.1770321.

Vescovi JD, Jovanović M. 2021. Sprint Mechanical Characteristics of Female Soccer Players: A Retrospective Pilot Study to Examine a Novel Approach for Correction of Timing Gate Starts. Frontiers in Sports and Active Living 3:629694. DOI: 10.3389/fspor.2021.629694.

Ward-Smith AJ. 2001. Energy conversion strategies during 100 m sprinting. Journal of Sports Sciences 19:701–710. DOI: 10.1080/02640410152475838.

Xie Y. 2022. Bookdown: Authoring books and technical documents with r markdown.

Xie Y, Allaire JJ, Grolemund G. 2018. R markdown: The definitive guide. Boca Raton, Florida: Chapman; Hall/CRC.

Xie Y, Dervieux C, Riederer E. 2020. R markdown cookbook. Boca Raton, Florida: Chapman; Hall/CRC.

Downloads

Posted

2022-07-18 — Updated on 2022-07-19

Versions