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Record W4295928012 · doi:10.7190/shu-thesis-00463

An investigation into football-specific dynamic balance measures

2021· dissertation· en· W4295928012 on OpenAlex
Leona Claire Brayne

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueSheffield Hallam University · 2021
Typedissertation
Languageen
FieldMedicine
TopicSports injuries and prevention
Canadian institutionsnot available
FundersBabol University of Medical SciencesMcGill University
KeywordsDynamic balanceBalance (ability)FootballComputer sciencePhysical medicine and rehabilitationEngineeringMedicinePolitical science

Abstract

fetched live from OpenAlex

Dynamic balance is a key component required to be successful in many sports yet the importance of dynamic balance in elite level sports has not been identified. The aim of this programme of doctoral study was to determine whether sport specific measures of dynamic balance could differentiate for skill level in footballers. Initially a literature review was performed to identify any gaps in the literature and to inform the research. A scoping review was then performed to provide an in-depth investigation into the understanding of the term dynamic balance and associated terms. More encompassing definitions of dynamic balance, postural control and postural stability were developed as well as a taxonomy to classify movements and existing balance tests. Following this, an investigation into important movements in football was conducted and those movements identified as important were classified using the taxonomy and aligned with existing dynamic balance tests to provide specificity. Finally, sport-specific measures of dynamic balance, along with a common balance measure used in football, were investigated to identify whether they had the ability to differentiate for skill level in footballers. Definitions of dynamic balance and related terms demonstrated disparity, overlap and they fail to cover the full range of dynamic balance situations. There are numerous dynamic balance tests available, they lack specificity, and test selection is difficult due to the complex and multi-factorial nature of balance. The taxonomy provided an approach for differentiating dynamic balance components, comprehensive profile of existing dynamic balance tests and a tool to identify strengths and limitations of existing tests and identify sport specific tests. Important movements in football were identified as shielding the ball, a shoulder barge whilst running, jostling to win the ball and shielding the ball whilst jostling, accelerating and braking, and a single leg kick or standing volley. Investigations identified that no existing dynamic balance tests aligned with the important movements in football. The external forces test shows promise at being a measure that can differentiate for skill level in football. Time to stabilisation was lowest for elite players (1.33 s) followed by recreational players (1.91). A large effect size was observed between elite and recreational players (g = -1.3) and recreational and non-football players (g = 0.82). There was a small effect size between elite and non-football players (g = -0.43). The mSEBT, kicking task and deceleration task were not considered a good measure of performance nor are they able to differentiate for skill level in football. This programme of research identifies that previous research has not identified the components of balance that should be tested for in football, and previous research has not made use of sport specific tests to assess dynamic balance in football. It is recommended that future research in this field refers to the newly proposed definitions. Additionally, further work should investigate other outcome measures of dynamic balance and whether they provide a better indication of dynamic postural control strategies. Finally, future directions could focus on whether participant variability exists at different skill levels.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.607
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.009
GPT teacher head0.253
Teacher spread0.244 · 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