Evidence map›Paper›PMID 40605172›Full record

ArticleMedicine and science in sports and exercise2025

Simulations Reveal How Touchdown Kinematic Variables Affect Top Sprinting Speed: Implications for Coaching.

Nicos Haralabidis, Ashton J Eaton, Scott L Delp, Jennifer L Hicks

Abstract read
In one paragraph

Article in Medicine and science in sports and exercise, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Nicos HaralabidisDepartment of Bioengineering, Stanford University, Stanford, CA.
Ashton J EatonNike, Inc., Nike Explore Team, Beaverton, OR.
Scott L Delp
Jennifer L HicksDepartment of Bioengineering, Stanford University, Stanford, CA.

Funding

TR&D Project 3: OpenSim for PredictionP41EB027060 · NIBIB · STANFORD UNIVERSITY · PI SCOTT L DELP · 2020 to 2026
$9.7M
NIBIB NIH HHS P41 EB027060
6 · The paper itself

Abstract

introductionSprint performance is a priority for coaches and athletes. Several kinematic variables, including horizontal touchdown distance (HTD) and inter-knee touchdown distance (IKTD), are targeted by coaches to increase top sprinting speed. However, the results of past research are conflicting, potentially due to the use of experimental inter-athlete study designs where it is not possible to establish cause-effect relationships.

methodsIn this study, we used a predictive simulation approach to assess cause-effect relationships between HTD and IKTD and sprinting speed. We scaled a three-dimensional musculoskeletal model to match the anthropometry of an international caliber male sprinter and generated predictive simulations of a single symmetric step of top-speed sprinting using a direct collocation optimal control framework. We first used our simulation framework to establish the model's top speed with minimal constraints on touchdown kinematics (the optimal simulation). Then, in additional simulations, we enforced specific HTD or IKTD values (±2, 4, and 6 cm compared with optimal).

resultsThe model achieved a top speed of 11.85 m·s -1 in the optimal simulation. Shortening HTD by 6 cm reduced speed by 7.3%, whereas lengthening HTD by 6 cm had a smaller impact on speed, with a 1.6% reduction. Speed in the simulation was insensitive to the IKTD changes we tested.

conclusionsThe results of our simulations indicate that there is an optimal HTD to maximize sprinting speed, providing support for coaches and athletes to adjust this technique variable. Conversely, our results do not provide evidence to support utilizing IKTD as a key technique variable for speed enhancement. We share the simulation framework so researchers can explore the effects of additional modifications on sprinting performance ( https://github.com/nicos1993/Pred_Sim_Sprinting ).

Indexed as

Athletic PerformanceMentoringRunningBiomechanical PhenomenaComputer SimulationHumansKneeMaleModels, BiologicalCOACHINGELITEOPTIMAL CONTROLOPTIMIZATIONTECHNIQUE

Identifiers

PMID40605172
PMCPMC12893165

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LicenceCC BY-NC-ND
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.