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The Relationship Between Tactical Positioning and the Race Outcome in 800-M Running at the 2016 Olympic Games and 2017 IAAF World Championship

Authors
  • González-Mohíno, Fernando1, 2
  • Cerro, Jesús Santos del3
  • Renfree, Andrew4
  • Yustres, Inmaculada1
  • González-Ravé, José Mª1
  • 1 University of Castilla-La Mancha, Sport Training Lab, Spain , (Spain)
  • 2 Facultad de Lenguas y Educación, Universidad Nebrija, Spain , (Spain)
  • 3 University of Castilla-La Mancha, Department of Statistics, Spain , (Spain)
  • 4 University of Worcester, Inst of Sport and Exercise Science, Henwick Grove, UK , (United Kingdom)
Type
Published Article
Journal
Journal of Human Kinetics
Publisher
Sciendo
Publication Date
Jan 31, 2020
Volume
71
Issue
1
Pages
299–305
Identifiers
DOI: 10.2478/hukin-2019-0090
Source
De Gruyter
Keywords
License
Green

Abstract

The purpose of this analysis was to quantify the probability of achieving a top-3 finishing position during 800-m races at a global championship, based on dispersion of the runners during the first and second laps and the difference in split times between laps. Overall race times, intermediate and finishing positions and 400 m split times were obtained for 43 races over 800 m (21 men’s and 22 women’s) comprising 334 individual performances, 128 of which resulted in higher positions (top-3) and 206 the remaining positions. Intermediate and final positions along with times, the dispersion of the runners during the intermediate and final splits (SS1 and SS2), as well as differences between the two split times (Dsplits) were calculated. A logistic regression model was created to determine the influence of these factors in achieving a top-3 position. The final position was most strongly associated with SS2, but also with SS1 and Dsplits. The Global Significance Test showed that the model was significant (p < 0.001) with a predictive ability of 91.08% and an area under the curve coefficient of 0.9598. The values of sensitivity and specificity were 96.8% and 82.5%, respectively. The model demonstrated that SS1, SS2 and Dplits explained the finishing position in the 800-m event in global championships.

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