The success of critical velocity protocol on predicting 10000 meters running performance
Background and Study Aim. The study aims to evaluate which of the critical velocity (CV) estimates of the three widely used models and the best-fit model successfully predict the running performance of 10000 meters. Materials and Methods. The group of participants in this study consisted of 11 Bri...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IP Iermakov S.S.
2023-08-01
|
| Series: | Physical Education of Students |
| Subjects: | |
| Online Access: | https://sportedu.org.ua/index.php/PES/article/view/1844 |
| _version_ | 1797733147907981312 |
|---|---|
| author | Barış Çabuk Onur Demirarar Merve Cin Refik Çabuk Bahtiyar Özçaldıran |
| author_facet | Barış Çabuk Onur Demirarar Merve Cin Refik Çabuk Bahtiyar Özçaldıran |
| author_sort | Barış Çabuk |
| collection | DOAJ |
| description | Background and Study Aim. The study aims to evaluate which of the critical velocity (CV) estimates of the three widely used models and the best-fit model successfully predict the running performance of 10000 meters.
Materials and Methods. The group of participants in this study consisted of 11 British endurance athletes. The CV estimations were obtained from the models with the athletes' running velocity and exhaustion times of 1500, 3000, and 5000 meters (m). The information was taken from a website where the results of the British athletes are recorded. In terms of selecting endurance athletes, the data of the athletes who ran 1500 m, 3000 m, 5000 m, and 10000 m in the same two years were included in this study. By fitting the data into mathematical models, the CV estimates of the three mathematical models and the individual best-fit model were compared with the 10000 m running velocity. The CV estimates were obtained by fitting the relevant data on the running velocity, exhaustion time, and running distance of the three running distances of athletes to each of the three mathematical models.
Results. 10000 m running velocity and times of the athletes corresponded to 19.65 ± 1.26 km-1 and 30.4 ± 1.94 minutes, respectively. The CV values obtained from the three mathematical models and 10000 m running velocity were similar (p > 0.05). Although the lowest total standard error levels were obtained with the best individual fit method, the 10000 m running velocity was overestimated (p < 0.05).
Conclusions. Three mathematical models predicted 10000 meters of race velocity when an exhaustion interval between 2-15 minutes was used. Even though the mathematically most valid CV value was obtained with the best individual fit method, it overestimated the 10000 m running velocity. When comparing the values of CV and the velocity of running 10,000 meters, our study suggests using the linear 1/velocity model. This is because the linear 1/velocity model has the smallest effect size, and there is no statistically significant difference in the total standard error level between the linear 1/velocity model and the best-fit model. |
| first_indexed | 2024-03-12T12:24:00Z |
| format | Article |
| id | doaj.art-ab0b6ce03e0f41df92ae9e53731e61e4 |
| institution | Directory Open Access Journal |
| issn | 2308-7250 |
| language | English |
| last_indexed | 2024-03-12T12:24:00Z |
| publishDate | 2023-08-01 |
| publisher | IP Iermakov S.S. |
| record_format | Article |
| series | Physical Education of Students |
| spelling | doaj.art-ab0b6ce03e0f41df92ae9e53731e61e42023-08-30T05:37:59ZengIP Iermakov S.S.Physical Education of Students2308-72502023-08-0127416216810.15561/20755279.2023.04032146The success of critical velocity protocol on predicting 10000 meters running performanceBarış Çabuk0https://orcid.org/0000-0002-2745-2424Onur Demirarar1https://orcid.org/0000-0002-2421-0067Merve Cin2https://orcid.org/0000-0001-9408-7853Refik Çabuk3https://orcid.org/0000-0002-3682-3135Bahtiyar Özçaldıran4https://orcid.org/0000-0002-9724-6730Ege UniversityGendarmerie and Coast Guard AcademyGendarmerie and Coast Guard AcademyBayburt UniversityEge UniversityBackground and Study Aim. The study aims to evaluate which of the critical velocity (CV) estimates of the three widely used models and the best-fit model successfully predict the running performance of 10000 meters. Materials and Methods. The group of participants in this study consisted of 11 British endurance athletes. The CV estimations were obtained from the models with the athletes' running velocity and exhaustion times of 1500, 3000, and 5000 meters (m). The information was taken from a website where the results of the British athletes are recorded. In terms of selecting endurance athletes, the data of the athletes who ran 1500 m, 3000 m, 5000 m, and 10000 m in the same two years were included in this study. By fitting the data into mathematical models, the CV estimates of the three mathematical models and the individual best-fit model were compared with the 10000 m running velocity. The CV estimates were obtained by fitting the relevant data on the running velocity, exhaustion time, and running distance of the three running distances of athletes to each of the three mathematical models. Results. 10000 m running velocity and times of the athletes corresponded to 19.65 ± 1.26 km-1 and 30.4 ± 1.94 minutes, respectively. The CV values obtained from the three mathematical models and 10000 m running velocity were similar (p > 0.05). Although the lowest total standard error levels were obtained with the best individual fit method, the 10000 m running velocity was overestimated (p < 0.05). Conclusions. Three mathematical models predicted 10000 meters of race velocity when an exhaustion interval between 2-15 minutes was used. Even though the mathematically most valid CV value was obtained with the best individual fit method, it overestimated the 10000 m running velocity. When comparing the values of CV and the velocity of running 10,000 meters, our study suggests using the linear 1/velocity model. This is because the linear 1/velocity model has the smallest effect size, and there is no statistically significant difference in the total standard error level between the linear 1/velocity model and the best-fit model.https://sportedu.org.ua/index.php/PES/article/view/1844aerobic capacitycritical velocityelite athletestrack and field |
| spellingShingle | Barış Çabuk Onur Demirarar Merve Cin Refik Çabuk Bahtiyar Özçaldıran The success of critical velocity protocol on predicting 10000 meters running performance Physical Education of Students aerobic capacity critical velocity elite athletes track and field |
| title | The success of critical velocity protocol on predicting 10000 meters running performance |
| title_full | The success of critical velocity protocol on predicting 10000 meters running performance |
| title_fullStr | The success of critical velocity protocol on predicting 10000 meters running performance |
| title_full_unstemmed | The success of critical velocity protocol on predicting 10000 meters running performance |
| title_short | The success of critical velocity protocol on predicting 10000 meters running performance |
| title_sort | success of critical velocity protocol on predicting 10000 meters running performance |
| topic | aerobic capacity critical velocity elite athletes track and field |
| url | https://sportedu.org.ua/index.php/PES/article/view/1844 |
| work_keys_str_mv | AT barıscabuk thesuccessofcriticalvelocityprotocolonpredicting10000metersrunningperformance AT onurdemirarar thesuccessofcriticalvelocityprotocolonpredicting10000metersrunningperformance AT mervecin thesuccessofcriticalvelocityprotocolonpredicting10000metersrunningperformance AT refikcabuk thesuccessofcriticalvelocityprotocolonpredicting10000metersrunningperformance AT bahtiyarozcaldıran thesuccessofcriticalvelocityprotocolonpredicting10000metersrunningperformance AT barıscabuk successofcriticalvelocityprotocolonpredicting10000metersrunningperformance AT onurdemirarar successofcriticalvelocityprotocolonpredicting10000metersrunningperformance AT mervecin successofcriticalvelocityprotocolonpredicting10000metersrunningperformance AT refikcabuk successofcriticalvelocityprotocolonpredicting10000metersrunningperformance AT bahtiyarozcaldıran successofcriticalvelocityprotocolonpredicting10000metersrunningperformance |