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Record W2084726127 · doi:10.1139/apnm-2013-0199

Effects of high-intensity running training on soccer-specific fitness in professional male players

2014· article· en· W2084726127 on OpenAlexvenueno aff
Carl Wells, Andrew M. Edwards, M. Fysh, Barry Drust

Bibliographic record

VenueApplied Physiology Nutrition and Metabolism · 2014
Typearticle
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsnot available
Fundersnot available
KeywordsAnaerobic exerciseIntensity (physics)Physical therapyMedicineRunning economyAerobic exerciseTraining (meteorology)PsychologyAnimal scienceVO2 maxHeart rateInternal medicinePhysicsBiologyBlood pressure

Abstract

fetched live from OpenAlex

The purpose of this study was to investigate whether or not physiological and performance gains could be achieved with the addition of high-intensity running to an existing training programme in a group of well trained professional male soccer players. Sixteen professional male players (21.3 ± 2.1 years, stature 177.4 ± 4.2 cm, body mass 73.1 ± 8.1 kg) were randomised in training (TRA, n = 8) and control (CON, n = 8) groups. All players performed physiological assessments before and after a 6-week intervention. Outcome measures were: (i) V̇O2peak, (ii) V̇O2 kinetics during very heavy-intensity exercise, (iii) a maximal anaerobic running test, and (iv) Yo-Yo Intermittent Recovery Test level 2 (YIRT2). The only aerobic parameter to change after the intervention was the phase III time constant at exercise onset for CON, which lengthened (p = 0.012) to a value similar to that of the TRA group. However, TRA showed gains in anaerobic performance (p = 0.021), time to exhaustion (p = 0.019), and maximal running speed (p = 0.023). In the YIRT2, distance run increased for TRA over time (p = 0.015), and the TRA group were also capable of running further in the YIRT2 after the intervention compared with CON (p = 0.011). This study shows it is possible to improve the soccer-specific high-intensity running capacity of professional players when high-intensity intermittent training is added to the normal training load and that this effect is only detectable in anaerobic capabilities. The observed effects are meaningful to the training practices of elite athletes seeking a competitive edge in team sports when otherwise well matched.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.945
Threshold uncertainty score0.513

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.016
GPT teacher head0.251
Teacher spread0.235 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations32
Published2014
Admission routes1
Has abstractyes

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