Quantitative analysis of the dominant external factors influencing elite speed Skaters' performance using BP neural network

IntroductionSpeed skating, being a popular winter sport, imposes significant demands on elite skaters, necessitating their effective assessment and adaptation to diverse environmental factors to achieve optimal race performance.ObjectiveThe aim of this study was to conduct a thorough analysis of the...

Full description

Bibliographic Details
Main Authors: Zhenlong Yang, Peng Ke, Yiming Zhang, Feng Du, Ping Hong
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-02-01
Series:Frontiers in Sports and Active Living
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fspor.2024.1227785/full
_version_ 1797319421172121600
author Zhenlong Yang
Peng Ke
Yiming Zhang
Feng Du
Ping Hong
author_facet Zhenlong Yang
Peng Ke
Yiming Zhang
Feng Du
Ping Hong
author_sort Zhenlong Yang
collection DOAJ
description IntroductionSpeed skating, being a popular winter sport, imposes significant demands on elite skaters, necessitating their effective assessment and adaptation to diverse environmental factors to achieve optimal race performance.ObjectiveThe aim of this study was to conduct a thorough analysis of the predominant external factors influencing the performance of elite speed skaters.MethodsA total of 403 races, encompassing various race distances and spanning from the 2013 to the 2022 seasons, were examined for eight high-caliber speed skaters from the Chinese national team. We developed a comprehensive analytical framework utilizing an advanced back-propagation (BP) neural neural network model to assess three key factors on race performance: ice rink altitude, ice surface temperature, and race frequency.ResultsOur research indicated that the performance of all skaters improves with higher rink altitudes, particularly in races of 1,000 m and beyond. The ice surface temperature can either enhance or impaire performance and varies in its influences based on skaters' technical characteristics, which had a perceptible or even important influence on races of 1,500 m and beyond, and a negligible influence in the 500 m and 1,000 m races. An increase in race frequency generally contributed to better performance. The influence was relatively minor in the 500 m race, important in the 3,000 m race, and varied among individuals in the 1,000 m and 1,500 m races.ConclusionThe study results offer crucial guidelines for speed skaters and coaches, aiding in the optimization of their training and competition strategies, ultimately leading to improved competitive performance levels.
first_indexed 2024-03-08T04:05:41Z
format Article
id doaj.art-7766479ed01e4119a65a2cf23ee0b59c
institution Directory Open Access Journal
issn 2624-9367
language English
last_indexed 2024-03-08T04:05:41Z
publishDate 2024-02-01
publisher Frontiers Media S.A.
record_format Article
series Frontiers in Sports and Active Living
spelling doaj.art-7766479ed01e4119a65a2cf23ee0b59c2024-02-09T05:04:42ZengFrontiers Media S.A.Frontiers in Sports and Active Living2624-93672024-02-01610.3389/fspor.2024.12277851227785Quantitative analysis of the dominant external factors influencing elite speed Skaters' performance using BP neural networkZhenlong Yang0Peng Ke1Yiming Zhang2Feng Du3Ping Hong4School of Transportation Science and Engineering, Beihang University, Beijing, ChinaSchool of Transportation Science and Engineering, Beihang University, Beijing, ChinaSchool of Transportation Science and Engineering, Beihang University, Beijing, ChinaSchool of Transportation Science and Engineering, Beihang University, Beijing, ChinaSchool of Competitive Sports, Beijing Sports University, Beijing, ChinaIntroductionSpeed skating, being a popular winter sport, imposes significant demands on elite skaters, necessitating their effective assessment and adaptation to diverse environmental factors to achieve optimal race performance.ObjectiveThe aim of this study was to conduct a thorough analysis of the predominant external factors influencing the performance of elite speed skaters.MethodsA total of 403 races, encompassing various race distances and spanning from the 2013 to the 2022 seasons, were examined for eight high-caliber speed skaters from the Chinese national team. We developed a comprehensive analytical framework utilizing an advanced back-propagation (BP) neural neural network model to assess three key factors on race performance: ice rink altitude, ice surface temperature, and race frequency.ResultsOur research indicated that the performance of all skaters improves with higher rink altitudes, particularly in races of 1,000 m and beyond. The ice surface temperature can either enhance or impaire performance and varies in its influences based on skaters' technical characteristics, which had a perceptible or even important influence on races of 1,500 m and beyond, and a negligible influence in the 500 m and 1,000 m races. An increase in race frequency generally contributed to better performance. The influence was relatively minor in the 500 m race, important in the 3,000 m race, and varied among individuals in the 1,000 m and 1,500 m races.ConclusionThe study results offer crucial guidelines for speed skaters and coaches, aiding in the optimization of their training and competition strategies, ultimately leading to improved competitive performance levels.https://www.frontiersin.org/articles/10.3389/fspor.2024.1227785/fullspeed skatingBP neural networkice rink altitudeice temperaturerace frequency
spellingShingle Zhenlong Yang
Peng Ke
Yiming Zhang
Feng Du
Ping Hong
Quantitative analysis of the dominant external factors influencing elite speed Skaters' performance using BP neural network
Frontiers in Sports and Active Living
speed skating
BP neural network
ice rink altitude
ice temperature
race frequency
title Quantitative analysis of the dominant external factors influencing elite speed Skaters' performance using BP neural network
title_full Quantitative analysis of the dominant external factors influencing elite speed Skaters' performance using BP neural network
title_fullStr Quantitative analysis of the dominant external factors influencing elite speed Skaters' performance using BP neural network
title_full_unstemmed Quantitative analysis of the dominant external factors influencing elite speed Skaters' performance using BP neural network
title_short Quantitative analysis of the dominant external factors influencing elite speed Skaters' performance using BP neural network
title_sort quantitative analysis of the dominant external factors influencing elite speed skaters performance using bp neural network
topic speed skating
BP neural network
ice rink altitude
ice temperature
race frequency
url https://www.frontiersin.org/articles/10.3389/fspor.2024.1227785/full
work_keys_str_mv AT zhenlongyang quantitativeanalysisofthedominantexternalfactorsinfluencingelitespeedskatersperformanceusingbpneuralnetwork
AT pengke quantitativeanalysisofthedominantexternalfactorsinfluencingelitespeedskatersperformanceusingbpneuralnetwork
AT yimingzhang quantitativeanalysisofthedominantexternalfactorsinfluencingelitespeedskatersperformanceusingbpneuralnetwork
AT fengdu quantitativeanalysisofthedominantexternalfactorsinfluencingelitespeedskatersperformanceusingbpneuralnetwork
AT pinghong quantitativeanalysisofthedominantexternalfactorsinfluencingelitespeedskatersperformanceusingbpneuralnetwork