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HEART RATE RESPONSES PRIOR TO AND DURING A 15-KM SKATE SKI RACE: A PILOT STUDY

Abstract

E.C. Ranta, T. Vetrone, & D.P. Heil

Montana State University, Bozeman, MT

The unique population of Masters-level cross country ski racers has been largely overlooked in prior ski research. In order to accurately develop coaching techniques for Masters skiers, current training practices and race strategies must first be understood. Collecting heart rate (HR) response data, through the use of telemetry-based heart rate monitor (HRM) systems, is one method of characterizing these athletes. PURPOSE: This study tested the feasibility of utilizing HRMs as a means to collect HR data on multiple Masters-level cross country ski racers competing simultaneously. A secondary purpose was to explore correlations between warm-up (WU) and race HR responses. METHODS: Five men and two women volunteered to participate in the study. Two subjects were dropped from the results due to incomplete data collection and imprecise HRM recordings. The remaining four men (M±SD: 43±7 yrs; 71.8±5.3 kg; 179.1±2.5 cm; 8±4.3 yrs race experience) and one woman (38 yrs; 67.1 kg; 172.7 cm; 1 yr race experience) wore telemetry-based HRM systems (set at 5-sec sample intervals) during a 15-km skate ski race, in addition to the 45-min WU period immediately preceding the race. Subjects were instructed to warm-up and race as they would normally. Participants also filled out an online questionnaire for self-reporting of demographic, training, and racing history. HR data was downloaded to a computer and summarized for both the WU and race periods. Race HR was defined as two minutes past the initial onset of a steady-state HR through the last highest recorded HR value. Summary HR values were then combined with race performance times and compared using Pearson’s correlation at an alpha of 0.10. RESULTS: Average race and WU HR were 168±4 BPM and 124±16 BPM, respectively, while WU HR as a percentage of race HR was 74%±7%. Race time correlated significantly with WU time spent at or above average race HR (r =0 .971; P = 0.006), while average race HR correlated significantly with average WU HR (r = 0.948; P = 0.014) as well as WU time spent within the subject’s range of race HR (r =0 .930; P = 0.022). CONCLUSION: The use of telemetry-based HRM systems are a feasible option for characterizing the WU and race HR response patterns of Masters-level skiers despite the mass start format and extremely cold air temperatures (-22˚C). Additionally, WU HR patterns correlated well with self-selected race pacing strategies within this particular population. Although future studies would benefit from increasing subject recruitment and reducing HRM data collection errors, similar methodological strategies are practical for further examining the training and racing practices of Masters-level cross country skiers.

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