Predictive performance models in marathon based on half-marathon, age group and pacing behavior

Vista sencilla de ítem
dc.contributor.authorMuñoz Pérez, Iker
dc.contributor.authorCastañeda Babarro, Arkaitz
dc.contributor.authorSantisteban Leguina, Aitor
dc.contributor.authorVarela-Sanz, Adrián
dc.date.accessioned2024-11-12T13:42:46Z
dc.date.available2024-11-12T13:42:46Z
dc.date.issued2024-09
dc.date.updated2024-11-12T13:42:46Z
dc.description.abstractObjective: The main aim of this study was to develop an equation for predicting performance in 42.2 km (MRT) using pacing and packing behavior, age group and previous 21.1 km time as possible explanatory variables. Methods: 1571 men and 251 female runners who took part in the Valencia Marathon and Half-Marathon were selected to display the regression models. Stepwise regression analysis showed as explanatory variables for MRT: pacing behavior, age group, and time in 21.1 km. Results: The analysis showed four regression models to estimate accurately MRT based principally on athletes previous performance in half-marathon and pacing behavior for men (R2= 0.72–0.88; RMSE= 4:03–8:31 [min:s]). For women, it was suggested a multiple linear regression for estimating MRT (R2 0.95; RSE= 8:06 [min:s]) based on previous performance in half-marathon and pacing behavior. The subsequent concordance analysis showed no significant differences between four of the total regressions with real time in the marathon (p>0.05). Conclusion: The present results suggest that even and negative pacing behavior and a better time in 21.1 km, in the previous weeks of the marathon, might accurately predict the MRT. At the same time, nomadic packing behavior was the one that reported the best performance. On the other hand, although the age group variable might partially explain the final performance, it should be included with caution in the final model because of differences in sample distribution, causing an overestimation or underestimation of the final time.en
dc.identifier.citationMuñoz-Pérez, I., Castañeda-Babarro, A., Santisteban, A., & Varela-Sanz, A. (2024). Predictive performance models in marathon based on half-marathon, age group and pacing behavior. Sport Sciences for Health, 20(3), 797-810. https://doi.org/10.1007/S11332-023-01159-4
dc.identifier.doi10.1007/S11332-023-01159-4
dc.identifier.eissn1825-1234
dc.identifier.issn1824-7490
dc.identifier.urihttp://hdl.handle.net/20.500.14454/1784
dc.language.isoeng
dc.publisherSpringer-Verlag Italia s.r.l.
dc.rights© The Author(s) 2024
dc.subject.otherEndurance
dc.subject.otherModeling
dc.subject.otherPrediction
dc.subject.otherRunning
dc.subject.otherTesting
dc.titlePredictive performance models in marathon based on half-marathon, age group and pacing behavioren
dc.typejournal article
dcterms.accessRightsopen access
oaire.citation.endPage810
oaire.citation.issue3
oaire.citation.startPage797
oaire.citation.titleSport Sciences for Health
oaire.citation.volume20
oaire.licenseConditionhttps://creativecommons.org/licenses/by/4.0/
oaire.versionVoR
Archivos
Bloque original
Mostrando 1 - 1 de 1
Miniatura
Nombre:
muñoz_predictive_2024.pdf
Tamaño:
931.19 KB
Formato:
Adobe Portable Document Format
Descargar
Colecciones
Artículos