Optimal [Formula: see text] ratio for predicting 15 km performance among elite male cross-country skiers

Pacing and predictors of performance during cross-country skiing races: A systematic review

BACKGROUND

Cross-country skiing (XCS) racing, a popular international winter sport, is complex and challenging from physical, technical, and tactical perspectives. Despite the vast amount of research focusing on this sport, no review has yet addressed the pacing strategies of elite XCS racers or the factors that influence their performance. The aim was to review the scientific literature in an attempt to determine the effects of pacing strategy on the performance of elite XCS racers.

METHODS

Four electronic databases were searched using relevant subject headings and keywords. Only original research articles published in peer-reviewed journals and the English language and addressing performance, biomechanics, physiology, and anthropometry of XCS racers were reviewed.

RESULTS

All 27 included articles applied correlative designs to study the effectiveness of different pacing strategies. None of the articles involved the use of an experimental design. Furthermore, potential changes in external conditions (e.g., weather, ski properties) were not taken into consideration. A comparable number of studies focused on the skating or classical technique. In most cases, positive pacing was observed, with certain indications that higher-level athletes and those with more endurance and strength utilized a more even pacing strategy. The ability to achieve and maintain a long cycle length on all types of terrain was an important determinant of performance in all of the included studies, which was not the case for cycle rate. In general, uphill performance was closely related to overall race performance, with uphill performance being most closely correlated to the success of female skiers and performance on flat terrain being more important for male skiers. Moreover, pacing was coupled to the selection and distribution of technique during a race, with faster skiers employing more double poling and kick double poling, less diagonal stride, and more V2 (double dance) than V1 (single dance) skating across a race.

CONCLUSION

We propose that skiers at all levels can improve their performance with more specific training in techniques (i.e., maintaining long cycles without compromising cycle rate and selecting appropriate techniques) in combination with training for endurance and more strength. Furthermore, we would advise less experienced skiers and/or those with lower levels of performance to apply a more even pacing strategy rather than a positive one (i.e., starting the race too fast).

Aerobic power and lean mass are indicators of competitive sprint performance among elite female cross-country skiers

The purpose of this study was to establish the optimal allometric models to predict International Ski Federation’s ski-ranking points for sprint competitions (FISsprint) among elite female cross-country skiers based on maximal oxygen uptake ( V˙O2max) and lean mass (LM). Ten elite female cross-country skiers (age: 24.5±2.8 years [mean ± SD]) completed a treadmill roller-skiing test to determine V˙O2max (ie, aerobic power) using the diagonal stride technique, whereas LM (ie, a surrogate indicator of anaerobic capacity) was determined by dual-emission X-ray anthropometry. The subjects’ FISsprint were used as competitive performance measures. Power function modeling was used to predict the skiers’ FISsprint based on V˙O2max, LM, and body mass. The subjects’ test and performance data were as follows: V˙O2max, 4.0±0.3 L min⁻¹; LM, 48.9±4.4 kg; body mass, 64.0±5.2 kg; and FISsprint, 116.4±59.6 points. The following power function models were established for the prediction of FISsprint: 3.91×105⋅V˙O2max−6.00 and 6.95 × 10¹⁰ · LM^−5.25; these models explained 66% (P=0.0043) and 52% (P=0.019), respectively, of the variance in the FISsprint. Body mass failed to contribute to both models; hence, the models are based on V˙O2max and LM expressed absolutely. The results demonstrate that the physiological variables that reflect aerobic power and anaerobic capacity are important indicators of competitive sprint performance among elite female skiers. To accurately indicate performance capability among elite female skiers, the presented power function models should be used. Skiers whose V˙O2max differs by 1% will differ in their FISsprint by 5.8%, whereas the corresponding 1% difference in LM is related to an FISsprint difference of 5.1%, where both differences are in favor of the skier with higher V˙O2max or LM. It is recommended that coaches use the absolute expression of these variables to monitor skiers’ performance-related training adaptations linked to changes in aerobic power and anaerobic capacity.

The influence of sex, age, and race experience on pacing profiles during the 90 km Vasaloppet ski race

The purpose of this study was to investigate pacing-profile differences during the 90 km Vasaloppet ski race related to the categories of sex, age, and race experience. Skiing times 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 the same group for the other two categories. Paired-samples Student’s t-tests were used to investigate 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), 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.