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The Influence of Sex, Age, and Race Experience on Pacing Profiles During the 90 Km Vasaloppet Ski Race

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The Influence of Sex, Age, and Race Experience on Pacing Profiles During the 90 Km Vasaloppet Ski Race Open Access Journal of Sports Medicine Dovepress open access to scientific and medical research Open Access Full Text Article ORIGINAL RESEARCH The influence of sex, age, and race experience on pacing profiles during the 90 km Vasaloppet ski race Magnus Carlsson1,2 Abstract: The purpose of this study was to investigate pacing-profile differences during the Hannes Assarsson1 90 km Vasaloppet ski race related to the categories of sex, age, and race experience. Skiing times Tomas Carlsson1,2 from eight sections (S1 to S8) were analyzed. For each of the three categories, 400 pairs of skiers were matched to have a finish time within 60 seconds, the same start group, and an assignment to 1School of Education, Health and Social Studies, Dalarna University, the same group for the other two categories. Paired-samples Student’s t-tests were used to investigate 2Dala Sports Academy, Falun, Sweden sectional pacing-profile differences between the subgroups. Results showed that males skied faster in S2 (P=0.0042), S3 (P=0.0049), S4 (P=0.010), and S1–S4 (P,0.001), whereas females skied faster in S6 (P,0.001), S7 (P,0.001), S8 (P=0.0088), and S5–S8 (P,0.001). For the age category, old subjects (40 to 59 years) skied faster than young subjects (19 to 39 years) in S3 (P=0.0029), For personal use only. and for the other sections, there were no differences. Experienced subjects ($4 Vasaloppet ski race completions) skied faster in S1 (P,0.001) and S1–S4 (P=0.0054); inexperienced skiers (,4 Vasaloppet ski race completions) had a shorter mean skiing time in S5–S8 (P=0.0063). In conclusion, females had a more even pacing profile than that of males with the same finish time, start group, age, and race experience. No clear age-related pacing-profile difference was identified for the matched subgroups. Moreover, experienced skiers skied faster in the first half whereas inexperienced skiers had higher skiing speeds during the second half of the race. Keywords: pacing strategy, cross-country skiing, endurance performance, sex difference. Introduction Recreational skiers have shown great interest in participating in long-distance (more than 50 km) cross-country ski races (eg, Vasaloppet, Marcialonga, and Birkebeiner- Open Access Journal of Sports Medicine downloaded from https://www.dovepress.com/ by 54.70.40.11 on 24-Dec-2018 rennet). For example, more than 15,000 skiers participate in the 90 km Vasaloppet ski race (VSR) each year (http://www.vasaloppet.se). There is limited research about what type of qualities are needed to optimize performance in long-distance cross- country skiing races. Endurance-related physiological variables, such as maximal oxygen uptake and the work intensity at the lactate threshold, have been shown to be indicators of competitive distance (5 to 50 km) performance in cross-country skiing1; thus, it is likely that these physiological qualities are important for the performance in long-distance races. Another determinant of competitive endurance performance Correspondence: Tomas Carlsson is how energetic resources are distributed to regulate power output.2 In cross-country School of Education, Health and skiing, this means that a skier must efficiently exert propelling forces appropriate to Social Studies, Dalarna University, Högskolegatan 2, 79188 Falun, Sweden the counteracting forces. This power-output regulation is related to the term pacing. Tel +46 23 778 402 Pacing has previously been defined as: “The goal directed distribution and manage- Fax +46 23 794 324 Email [email protected] ment of effort across the duration of an exercise bout.”3 Hence, pacing in sports can be submit your manuscript | www.dovepress.com Open Access Journal of Sports Medicine 2016:7 11–19 11 Dovepress © 2016 Carlsson et al. This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms. php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work http://dx.doi.org/10.2147/OAJSM.S101995 you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php). Powered by TCPDF (www.tcpdf.org) 1 / 1 Carlsson et al Dovepress regarded as a strategy to distribute the power output during influencing factor on athletes’ pacing is previous race experi- the exercise, which is influenced by both physiological and ence. A previous study showed that experienced marathon run- psychological factors.3 ners were able to keep their pace better than less experienced The influence of pacing in cross-country skiing has previ- marathon runners.19 It has been suggested that inexperienced ously been investigated based on skiing speed for a 1.4 km athletes tend to overestimate their individual capability, which sprint4 and 5.6–50 km distance5–9 performances; together, contributes to a more pronounced positive pacing profile; this these studies indicate that cross-country skiers tend to adopt requires a downregulation of power output as a consequence a positive pacing profile (ie, race speed gradually decreasing of a premature sensation of fatigue.3 Hence, previous race throughout the race). This pacing strategy has been ques- experience appears to be an important factor for adopting an tioned by a numerical simulation of sprint skiing that claims accurate pacing strategy for the specific exercise task. that an even pacing profile, characterized by minor variations The purpose of the current study was to investigate in skiing speed, is optimal for performance.10 However, there pacing-profile differences during the 90 km VSR related to is presently no detailed information available about how a the categories of sex, age, and race experience. We hypoth- skier should regulate his/her power output to optimize per- esized that there was a larger proportion of females, old, and formance in long-distance races. experience skiers who skied slower in the sections during first An athlete’s pacing profile in a self-paced competition is half and faster in the sections during the second half in the influenced by a predetermined pacing strategy and an altera- 90 km VSR compared to males, young, and inexperienced tion in homeostatic status during the race; hence, the power skiers, respectively. output is regulated by the brain, at various subconscious to conscious levels, according to the afferent feedback from Methods numerous physiological systems to reduce the risk of criti- Study design cal homeostatic disturbances.11 It has been suggested that To investigate pacing-profile differences for the categories athletes, during the event, continuously compare their rate of For personal use only. of sex, age, and race experience for a long-distance cross- perceived exertion with the expected rate of perceived exer- country skiing race, skiing times from the 90 km VSR were tion, and if these diverge, the athletes increase or decrease analyzed. To minimize the effect of weather and waxing on the pace.12 Different pacing profiles have been proposed to performance, results from the VSR year 2012 (http://results. optimize performance depending on the exercise duration; vasaloppet.se) were chosen because of the stable track and for marathon running with an approximate duration of 2.5 weather conditions throughout the race. For each category, hours, a more even pacing profile has been associated with the subjects were matched based on finish time, start group, better performance.13–15 Information about the optimal pac- and the other two categories. The Institutional Review Board ing profile for performances that last more than 5 hours is granted approval for this study, and the requirement for limited; however, it has been suggested that an even pacing written informed consent was waived because all data were profile was preferable for a 100 km ultramarathon running publicly available. performance where the mean race time was ∼8 hours.16 Open Access Journal of Sports Medicine downloaded from https://www.dovepress.com/ by 54.70.40.11 on 24-Dec-2018 A recent investigation regarding the pacing profiles of Race characteristics marathoners demonstrated that both males and females tried The 90 km VSR is a mass-start competition and the skiers to maintain an even pacing profile; however, independent of are, based on their results from cross-country skiing races the performance level, all groups displayed a positive pacing approved by Vasaloppet organization, assigned to eleven profile (ie, the race speed gradually decreased throughout the different start groups (start groups 0 to 10). The race is per- race).17 However, it appears that females are more likely than formed using the classical technique. The weather conditions males to adopt a more even pacing profile during marathon throughout the race were stable with an air temperature below running.18,19 It has been proposed that these sex differences zero (–9°C at the start, –1°C at midday, and –3°C during the originate from both physiological and psychological differ- afternoon). The 90 km course had 1,380 m of total climbing, ences between males and females.19 an altitude difference of 360 m, and a maximum continuous Differences in pacing profiles have also been shown for climbing section of 180 m. In addition to the finish time, split athletes with different ages, where older marathon runners times were recorded at seven official intermediate-time sta- were shown to have a more even pacing profile compared tions, and the course was divided into eight sections (S1 to S8) to that of their younger counterparts.18 Another proposed (Figure 1).
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