A Systematic Review of the Effects of Strength and Power Training on Performance in Cross-Country Skiers
Bibliographic record
Abstract
To identify and evaluate current scientific literature concerning the effect of strength, power and speed training on relevant physiological and biomechanical characteristics and performance of competitive cross-country skiers (XCS), the databases Scopus and PubMed were searched systematically for original articles in peer-reviewed journals. Of the 599 studies retrieved, 12 met the inclusion criteria (i.e., assessment of outcome measures with relevance for XCS performance; involvement of traditional resistance training; application of external resistance to the body; intervention longer than 4 weeks; randomized controlled trial). The methodological rigor of each study was assessed using the PEDro scale, which were mostly poor-to-fair, with good methodological quality in only two articles. All of the strength/power/speed interventions improved 1RM (0.8-6.8 ES), but findings with respect to jump performance, ability to generate force rapidly and body composition were mixed. Interventions demonstrated moderate-to-high ES on XCS specific performance compared with control (mean ES = 0.56), but the pattern observed was not consistent. None of the interventions changed anaerobic capacity, while in most studies VO2max was either unchanged or increased. Work economy or efficiency was enhanced by most of the interventions. In conclusion, present research indicates that strength training improves general strength, with moderate effects on XCS performance, and inconclusive effects on work economy and VO2max/VO2peak. Strength training with high loads, explosive strength training, or sprint interval training seem to be promising tools for modern XCS training. Future investigations should include long-term (e.g., >6 months) strength training to allow sufficient time for increased strength and speed to influence actual XCS performance. Moreover, they should include both sexes, as well as upper- and lower-body muscles (trained separately and together) and employ free weights and core training. Methodological differences and limitations highlighted here may explain discrepancies in findings and should be taken into consideration in future research in this area.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".