The kinematic changes following a training intervention on pumping in slalom
DOI:
https://doi.org/10.51224/SRXIV.426Keywords:
Motor learning, Generalized Additive Model, Alpine skiing, Skiing technique, Pumping to increase velocityAbstract
Slalom racers rely on effective strategies to bring them down the course in the shortest amount of time possible. One proposed strategy that skiers can use to achieve this goal is to pump themselves to higher velocities by extending their center of mass closer to the turn's axis of rotation from a laterally tilted position during the turn. However, the effectiveness of this proposed strategy and its potential magnitude are much debated. In a previous study, we found that skilled skiers (n=66) greatly improved their race times after training to pump on flats in slalom. Here, we ran a follow-up study and explored the kinematic changes that may explain this improvement in a smaller sample (n=18) of this larger pool of skiers, where we recorded the positions of the skiers using a local positioning system in the upper section of the course. Using a Bayesian estimation approach, we found that the speed profile of the skiers changed greatly, with a change pattern consistent with what we would expect from pumping. We also found a general trend that the skiers had a longer path length at retention, though the change was less consistent from gate to gate. Pumping to increase speed on flats thus appears to be an important strategy for increasing speed on flats.
Metrics
References
Barr, D. J. (2021). Learning statistical models through simulation in R: An interactive text-
book. Version 1.0.0. In Learning statistical models through simulation in R: An interactive
textbook. Version 1.0.0. https://psyteachr.github.io/stat-models-v1.
Barr, D. J., Levy, R., Scheepers, C., & Tily, H. J. (2013). Random effects structure for con-
firmatory hypothesis testing: Keep it maximal. Journal of Memory and Language, 68(3),
–278. https://doi.org/10.1016/j.jml.2012.11.001
Bürkner, P.-C. (2017). Brms: An R Package for Bayesian Multilevel Models Using Stan. Journal
of Statistical Software, 80(1), 1–28. https://doi.org/10.18637/jss.v080.i01
Federolf, P. A. (2012). Quantifying instantaneous performance in alpine ski racing. Journal of
Sports Sciences, 30(10), 1063–1068. https://doi.org/10.1080/02640414.2012.690073
Gilat, A., & Subramaniam, B. (2013). Numerical methods for engineers and scientists. Wiley
& Sons Inc.
Gilgien, M., Spörri, J., Chardonnens, J., Kröll, J., & Müller, E. (2013). Determination of External
Forces in Alpine Skiing Using a Differential Global Navigation Satellite System. Sensors,
(8), 9821–9835. https://doi.org/10.3390/s130809821
Hébert-Losier, K., Supej, M., & Holmberg, H.-C. (2014). Biomechanical factors influencing the
performance of elite alpine ski racers. Sports Medicine, 44, 519–533. https://doi.org/10.
/s40279-013-0132-z
Howe, J. (2001). The new skiing mechanics. McIntire Publishing. https://books.google.no/
books?id=aUkAPgAACAAJ
Joubert, G. (1978). Le Ski: Un Art, Une Technique. Arthaud.
Joubert, G., & Vuarnet, J. (1967). How to Ski the New French Way. Dial Press.
Kay, M. (n.d.). Tidybayes: Tidy Data and Geoms for Bayesian Models. https://doi.org/10.
/zenodo.1308151
Krakauer, J. W., Hadjiosif, A. M., Xu, J., Wong, A. L., & Haith, A. M. (2019). Motor Learning.
Comprehensive Physiology, 9(2), 613–663. https://doi.org/10.1002/cphy.c170043
Kruschke, J. K., & Liddell, T. M. (2018). The bayesian new statistics: Hypothesis testing,
estimation, meta-analysis, and power analysis from a Bayesian perspective. Psychonomic
Bulletin & Review, 25(1), 178–206. https://doi.org/10.3758/s13423-016-1221-4
LeMaster, R. (1999). The skier’s edge. Human Kinetics.
LeMaster, R. (2010). Ultimate Skiing. Human Kinetics.
Lešnik, B., & Žvan, M. (2007). The best slalom competitors-kinematic analysis of tracks and
velocities. Kinesiology, 39(1.), 40–48.
Lind, D. A., & Sanders, S. P. (2004). The physics of skiing: Skiing at the triple point (2nd ed.).
Springer Science & Business Media.
Luginbühl, M., Gross, M., Lorenzetti, S., Graf, D., & Bünner, M. J. (2023). Identification of
optimal movement patterns for energy pumping. Sports, 11(2). https://doi.org/10.3390/
sports11020031
Magelssen, C., Gilgien, M., Tajet, S. L., Losnegard, T., Haugen, P., Reid, R., & Froemer, R.
(2024). Reinforcement learning enhances training and performance in skilled alpine skiers
compared to traditional coaching instruction. bioRxiv, 2024–2004.
Magelssen, C., Haugen, P., Reid, R., & Gilgien, M. (2022). Is there a contextual interference
effect for sub-elite alpine ski racers learning complex skills? Frontiers in Bioengineering
and Biotechnology, 10. https://doi.org/10.3389/fbioe.2022.966041
McElreath, R. (2018). Statistical rethinking: A Bayesian course with examples in R and Stan.
Chapman; Hall/CRC.
McKinney, W. (2011). Pandas: A foundational Python library for data analysis and statistics.
Python for High Performance and Scientific Computing, 14(9), 1–9.
Mote, C. D., & Louie, J. K. (1983). Accelerations induced by body motions during snow skiing.
Journal of Sound and Vibration, 88(1), 107–115. https://doi.org/10.1016/0022-460X(83)
-X
Müller, E. (1994). Analysis of the biomechanical characteristics of different swinging techniques
in alpine skiing. Journal of Sports Sciences, 12(3), 261–278.
Pedersen, E. J., Miller, D. L., Simpson, G. L., & Ross, N. (2019). Hierarchical generalized
additive models in ecology: An introduction with mgcv. PeerJ, 7, e6876.
R Core Team. (2022). R: A Language and Environment for Statistical Computing. R Foundation
for Statistical Computing. https://www.R-project.org/
Reid, R. C. (2010). A kinematic and kinetic study of alpine skiing technique in slalom [{PhD}
{Thesis}]. Norwegian School of Sport Sciences.
Reid, R. C., Gilgien, M., Moger, T., Tjørhom, H., Haugen, P., Kipp, R., & Smith, G. (2009). Turn
characteristics and energy dissipation in slalom. na.
Spörri, J., Kröll, J., Schwameder, H., & Müller, E. (2012). Turn characteristics of a top world
class athlete in giant slalom: A case study assessing current performance prediction concepts.
International Journal of Sports Science & Coaching, 7(4), 647–659.
Spörri, J., Kröll, J., Schwameder, H., & Müller, E. (2018). The role of path length- and speedrelated
factors for the enhancement of section performance in alpine giant slalom. European
Journal of Sport Science, 18(7), 911–919. https://doi.org/10.1080/17461391.2018.
Spörri, J., Kröll, J., Schwameder, H., Schiefermüller, C., & Müller, E. (2012). Course setting and
selected biomechanical variables related to injury risk in alpine ski racing: An explorative
case study. British Journal of Sports Medicine, 46(15), 1072. https://doi.org/10.1136/
bjsports-2012-091425
Supej, M. (2008). Differential specific mechanical energy as a quality parameter in racing
alpine skiing. Journal of Applied Biomechanics, 24(2), 121–129. https://doi.org/10.1123/
jab.24.2.121
Supej, M., & Cernigoj, M. (2006). Relations between Different Technical and Tactical Approaches
and Overall Time at Men’s World Cup Giant Slalom Races. Kinesiologia Slovenica,
, 63–69.
Supej, M., Hébert-Losier, K., & Holmberg, H.-C. (2015). Impact of the steepness of the slope
on the biomechanics of world cup slalom skiers. International Journal of Sports Physiology
and Performance, 10(3), 361–368. https://doi.org/10.1123/ijspp.2014-0200
Supej, M., & Holmberg, H.-C. (2010). How gate setup and turn radii influence energy dissipation
in slalom ski racing. Journal of Applied Biomechanics, 26(4), 454–464. https:
//doi.org/10.1123/jab.26.4.454
Supej, M., & Holmberg, H.-C. (2011). A new time measurement method using a high-end
global navigation satellite system to analyze alpine skiing. Research Quarterly for Exercise
and Sport, 82(3), 400–411. https://doi.org/10.1080/02701367.2011.10599772
Supej, M., Kipp, R., & Holmberg, H.-C. (2011). Mechanical parameters as predictors of performance
in alpine World Cup slalom racing. Scandinavian Journal of Medicine & Science in
Sports, 21(6), e72–e81. https://doi.org/10.1111/j.1600-0838.2010.01159.x
Supej, M., Kugovnik, O., Nemec, B., & Šmitek, J., 1916-. (2001). Doba smučanja s sledenjem
telesa - Tekmovalna slalomska tehnika z vidika biomehanike = [Slalom racing technique
from the viewpoint of biomechanics]. Šport.
Virtanen, P., Gommers, R., Oliphant, T. E., Haberland, M., Reddy, T., Cournapeau, D., Burovski,
E., Peterson, P., Weckesser, W., & Bright, J. (2020). SciPy 1.0: Fundamental algorithms for
scientific computing in Python. Nature Methods, 17(3), 261–272.
Wood, S. N. (2017). Generalized additive models: An introduction with R. chapman; hall/CRC.
Downloads
Posted
Categories
License
Copyright (c) 2024 Christian Magelssen, Robert Reid, Live Steinnes Luteberget, Matthias Gilgien, Petter Andre Husevåg Jølstad, Per Haugen (Author)
This work is licensed under a Creative Commons Attribution 4.0 International License.