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Identifying patterns in squash contests using dynamical analysis and human perception.

2006· article· en· W2729338795 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Performance Analysis in Sport · 2006
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicSports Analytics and Performance
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsSquashContext (archaeology)DyadRelation (database)Phase (matter)MathematicsComputer scienceDynamical systems theoryPhase spacePhysicsPsychologyData miningSocial psychologyGeologyGeography

Abstract

fetched live from OpenAlex

This report examines the space-time patterns of squash players as they move around the squash court in the context of a dynamical system. The phase relations that describe the squash dyad (i.e., where one player is in relation to the other player) demonstrated a strong tendency towards an anti-phase (180°) relation, as expected. When the data from a number of squash rallies (N = 47) were combined a second stable phase relation of 135° emerged, thus indicating the existence of a previously undetected lead-lag phase relation within the squash dyad. The lead phase relation belonged to the server of the rally in each instance. Further inspections of individual squash rallies demonstrated other properties consistent with a dynamical system description, namely the existence of phase fluctuations (i.e., increased variability in the phase relations), phase transitions (i.e., a switch between stable phase relations), and phase slippages as a result of a missing, or extra, phase cycle for one of the two players. Together, these results indicate that the space-time interactions of squash players might usefully be described in the context of dynamical principles of self-organizing (complex) systems. These findings furthermore suggest that the dynamical properties of the squash dyad may contain important information for identifying the squash patterns that we think we see using visual inspection. To examine this supposition we used the point-light method to represent the movements of the two squash players within a rally as contrasted against a distracter set of varying complexities. Interestingly, humans retained the ability to identify the squash dyad beyond chance even when the distracter set contained squash-like properties. Whether a dynamical analysis of these data is likewise discriminatory in its ability to detect squash behaviours from squash-like behaviours remains to be determined in future research.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.138
Threshold uncertainty score0.676

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.023
GPT teacher head0.284
Teacher spread0.261 · 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