Experience of using of sport social network open data for Moscow marathon 2017 results analysis
https://doi.org/10.17238/ISSN2223-2524.2019.1.80
Abstract
Objective: to explore the possibilities of sport social network open data in analysis of Moscow Marathon 2017 (MM2017) results. Materials and methods: open data, downloaded from sport gadgets to Strava.com social network by 1165 of 7972 MM2017 participants were retrieved (information about sex, age, race time, average heart rate (HR) and cadence at the race, and training intensity). Results: the age of participants was 34 (30-39) years, 13% of women, women were significantly younger than men. The median of the race time was 4:31:56 for women, 4:03:11 for men, p = 0.0001; the average cadence was 174 and 169 respectively, p = 0.0001; average HR was 163 and 162 respectively, p = 0.07. There was no correlation between age and race time, at least for runners under 60 years. The total distance, the number and duration of trainings in 2017 and 2016, personal bests at distances 5-42.2 km did not differ significantly in men and women, but were higher in participants with over-median race time and over-median age. Average HR and average cadence of participants with under-median race time was significantly higher than in those with over-median race time (163 and 161 bpm, p = 0.002; 174 and 166 per minute, p = 0.0001 respectively). The average HR was expectedly higher in younger participants (164 and 160 bpm, p <0.0001). The average cadence in runners divided by the median of age was not significantly different. Analysis of average time in pulse zones showed that participants with better race time were able to maintain higher HR for longer time, what can be considered to more intense training. Conclusions: the open data of Strava.com users can enrich mass running analytics, limited before by age, sex and the race time of participants. The availability of information about the average HR, cadence at the race and training intensity can improve the research possibilities in sports medicine. This data can be useful instrument of coaching.
About the Authors
А. V. Melekhov
Pirogov Russian National Research Medical University
Russian Federation
Russian Federation
Aleksandr V. Melekhov, MD, D.Sc. (Medicine), Associate Professor of the Hospital Therapy Department №2
Moscow
M. A. Melekhova
School №1514
Russian Federation
Russian Federation
Marya A. Melekhova, Senior
Moscow
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Review
For citations:
Melekhov А.V., Melekhova M.A. Experience of using of sport social network open data for Moscow marathon 2017 results analysis. Sports medicine: research and practice. 2019;9(1):80-88. (In Russ.) https://doi.org/10.17238/ISSN2223-2524.2019.1.80
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