Estimating the Replicability of Sports and Exercise Science Research
- PMID: 40522610
- DOI: 10.1007/s40279-025-02201-w
Estimating the Replicability of Sports and Exercise Science Research
Abstract
Background: The replicability of sports and exercise research has not been assessed previously despite concerns about scientific practices within the field.
Aim: This study aims to provide an initial estimate of the replicability of applied sports and exercise science research published in quartile 1 journals (SCImago journal ranking for 2019 in the Sports Science subject category; www.scimagojr.com ) between 2016 and 2021.
Methods: A formalised selection protocol for this replication project was previously published. Voluntary collaborators were recruited, and studies were allocated in a stratified and randomised manner on the basis of equipment and expertise. Original authors were contacted to provide deidentified raw data, to review preregistrations and to provide methodological clarifications. A multiple inferential strategy was employed to analyse the replication data. The same analysis (i.e. F test or t test) was used to determine whether the replication effect size was statistically significant and in the same direction as the original effect size. Z-tests were used to determine whether the original and replication effect size estimates were compatible or significantly different in magnitude.
Results: In total, 25 replication studies were included for analysis. Of the 25, 10 replications used paired t tests, 1 used an independent t test and 14 used an analysis of variance (ANOVA) for the statistical analyses. In all, 7 (28%) studies demonstrated robust replicability, meeting all three validation criteria: achieving statistical significance (p < 0.05) in the same direction as the original study and showing compatible effect size magnitudes as per the Z test (p > 0.05).
Conclusion: There was a substantial decrease in the published effect size estimate magnitudes when replicated; therefore, sports and exercise science researchers should consider effect size uncertainty when conducting subsequent power analyses. Additionally, there were many barriers to conducting the replication studies, e.g., original author communication and poor data and reporting transparency.
© 2025. The Author(s).
Conflict of interest statement
Declarations. Ethics approval: Ethical approval was obtained at each local university, and all studies were conducted in accordance with the Declaration of Helsinki. Consent to participate: All participants provided consent to participate. Funding: Open Access funding provided by the IReL Consortium. This work was supported by the Irish Research Council’s Government of Ireland Postgraduate Scholarship Programme [GOIPG/2020/1155]. Conflict of interest: The authors report there are no competing interests to declare. Availability of data and material: Raw data, code and other supplementary materials are available at https://doi.org/10.17605/OSF.IO/SFBVA . Author contributions: Jennifer Murphy: conceptualisation (equal), data curation (lead), formal analysis (equal), funding acquisition (lead), investigation (lead), methodology (equal) and writing – original draft preparation (lead). Aaron R. Caldwell: conceptualisation (equal), methodology (equal), supervision, formal analysis (equal) and writing – review and editing (equal). Cristian Mesquida: conceptualisation (equal). Joe P. Warne: conceptualisation (equal), methodology (equal), supervision (lead) and writing – review and editing (equal). Aera J. M. Ladell, Alberto Encarnación-Martínez, Alexandre Tual, Andrew Denys, Bailey Cameron, Bas Van Hooren, Ben Parr, Bianca DeLucia, Billy R. J. Mason, Brad Clark, Brendan Egan, Calum Brown, Carl Ade, Chiarella Sforza, Christopher B. Taber, Christopher Kirk, Christopher McCrum, Cian O. Keeffe Tighe, Ciara Byrne, Claudia Brunetti, Cyril Forestier, Dan Martin, Danny Taylor, David Diggin, Dearbhla Gallagher, Deborah L. King, Elizabeth Rogers, Eric C. Bennett, Eric T. Lopatofsky, Gemma Dunn, Gérome C. Gauchar, Guillaume Mornieux, Ignacio Catalá-Vilaplana, Ines Caetan, Inmaculada Aparicio-Aparicio, Jack Barnes, Jake Blaisdell, James Steele, Jared R. Fletcher, Jasmin Hutchinson, Jason Au, Jason P. Oliemans, Javad Bakhshinejad, Joaquin Barrios, Jose Ignacio Priego Quesada, Joseph Rager, Julia B. Capon, Julie S. J. Walton, Kailey Stevens, Katie Heinrich, Kelly Wu, Kenneth Meijer, Laura Richards, Lauren Jutlah, Le Tong, Lee Bridgeman, Leo Banet, Leonard Mbiyu, Lucy Sefton, Margaret de Chanaleilles, Maria Charisi, Matthew Beerse, Matthew J. Major, Maya Caon, Mel Bargh, Michael Rowley, Miguel Vaca Moran, Nicholas Croker, Nicolas C. Hanen, Nicole Montague, Noel E. Brick, Oliver R. Runswick, Paul Willems, Pedro Pérez-Soriano, Rebecca Blake, Rebecca Jones, Rebecca Louise Quinn, Roberto Sanchis-Sanchis, Rodrigo Rabello, Roisin Bolger, Roy Shohat, Sadie Cotton, Samantha Chua, Samuel Norwood, Samuel Vimeau, Sandro Dias, Sissel Pedersen, Spencer S. Skaper, Taylor Coyle, Terun Desai, Thomas I. Gee, Tobias Edwards, Torsten Pohl, Vanessa Yingling, Vinicius Ribeiro, Youri Duchene, Zacharias Papadakis: data collection, drafting of preregistration, replication reports and review of final manuscript.
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