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Record W2900524811 · doi:10.3389/fphys.2018.01611

Combination of Agility and Plyometric Training Provides Similar Training Benefits as Combined Balance and Plyometric Training in Young Soccer Players

2018· article· en· W2900524811 on OpenAlexaff
Issam Makhlouf, Anis Chaouachi, Mehdi Chaouachi, Aymen Ben Othman, Urs Granacher, David G. Behm

Bibliographic record

VenueFrontiers in Physiology · 2018
Typearticle
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsMemorial University of Newfoundland
FundersUniversität PotsdamDeutsche Forschungsgemeinschaft
KeywordsPlyometricsPhysical therapyBalance (ability)Balance testBalance trainingSprintPhysical medicine and rehabilitationMulti-stage fitness testIsometric exerciseDynamic balanceStorkMedicinePhysical fitnessJumpEngineeringBiology

Abstract

fetched live from OpenAlex

Introduction: Studies that combined balance and resistance training induced larger performance improvements compared with single mode training. Agility exercises contain more dynamic and sport-specific movements compared with balance training. Thus, the purpose of this study was to contrast the effects of combined balance and plyometric training with combined agility and plyometric training and an active control on physical fitness in youth. Methods: Fifty-seven male soccer players aged (10-12 years) participated in an 8-week training program (2 x week). They were randomly assigned to a balance-plyometric (BPT: n=21), agility-plyometric (APT: n=20) or control group (n=16). Measures included proxies of muscle power (countermovement jump [CMJ], triple-hop-test [THT]), muscle strength (reactive strength index [RSI], maximum voluntary isometric contraction [MVIC] of handgrip, back extensors, knee extensors), agility (4x9-m shuttle run, Illinois agility test with and without the ball), balance (Standing Stork, Y-Balance), and speed (10-30 m sprints). Results: Significant time x group interactions were found for CMJ, hand grip MVIC force, ICODTwithout a ball, agility (4x9 m), standing stork balance, Y-balance, 10 and 30-m sprint. The APT pre- to post-test measures displayed large ES improvements for hand grip MVIC force, ICODT without a ball, agility test, CMJ, standing stork balance test, Y-balance test but only moderate ES improvements with the 10 and 30 m sprints. The BPT group showed small (30 m sprint), moderate (hand grip MVIC, ICODTwithout a ball) and large ES (agility [4x9m] test, CMJ, standing stork balance test, Y-balance) improvements respectively. Conclusion: In conclusion, whereas both groups provided significant improvements, the dynamic balance challenges associated with agility training provided greater ES benefits in 6 of 8 significant measures. It is recommended that youth incorporate balance exercises into their training and progress to agility with their strength and power training.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

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)0.0030.000

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 head0.027
GPT teacher head0.270
Teacher spread0.242 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
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

Citations141
Published2018
Admission routes1
Has abstractyes

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