Deviation from goal pace, body temperature and body mass loss predictors of road race performance

UNCG Author/Contributor (non-UNCG co-authors, if there are any, appear on document)
William M. Adams, Assistant Professor (Creator)
The University of North Carolina at Greensboro (UNCG )
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Abstract: Objectives: The purpose of this study was to examine the relationship between pacing, gastrointestinal temperature (TGI), and percent body mass loss (%BML) on relative race performance during a warm weather 11.3 km road race. Design: Observational study of a sample of active runners competing in the 2014 Falmouth Road Race. Methods: Participants ingested a TGI pill and donned a GPS enabled watch with heart rate monitoring capabilities prior to the start of the race. Percent off predicted pace (%OFF) was calculated for seven segments of the race. Separate linear regression analyses were used to assess the relationship between pace, TGI, and %BML on relative race performance. One-way ANOVA was used to analyse post race TGI (=40 °C vs <40 °C) on pace and %OFF. Results: Larger %BML was associated with faster finish times (R2 = 0.19, p = 0.018), faster average pace (R2 = 0.29, p = 0.012), and a greater %OFF (R2 = 0.15, p = 0.033). %OFF during the first mile (1.61 km) significantly predicted overall finish time (R2 = 0.64, p < 0.001) while %OFF during the second mile (3.22 km) (R2 change = 0.18, p < 0.001) further added to the model (R2 = 0.82, p < 0.001). Body temperature (pre race TGI and post race TGI) was not predictive of overall finish time (p > 0.05). There was a trend in a slower pace (p = 0.055) and greater %OFF (p = 0.056) in runners finishing the race with a TGI > 40 °C. Conclusions: Overall, finish time was influenced by greater variations in pace during the first two miles of the race. In addition, runners who minimized fluid losses and had lower TGI were associated with meeting self-predicted goals.

Additional Information

Journal of Science and Medicine in Sport. 2017;20(3):302-306
Language: English
Date: 2017
Hypohydration, Dehydration, Gastrointenstinal temperature, Predicted running performance

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