Space–time coordination dynamics in basketball: Part 2. The interaction between the two teams
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.
Bibliographic record
Abstract
In this article, we examine the space-time coordination dynamics of two basketball teams during competition. We identified six game sequences at random, from which the movement data of each player were obtained for analysis of team behaviours in both the longitudinal (basket-to-basket) and lateral (side-to-side) directions. The central position of a team was measured using its spatial (geometric) centre and dispersion using a stretch index, obtained from the mean distance of team members from the spatial centre. Relative-phase analysis of the spatial centres demonstrated in-phase stabilities in both the longitudinal and lateral directions, with more stability in the longitudinal than lateral direction. As anticipated, this finding is consistent with the results of an analysis of individual playing dyads (see companion article, this issue), as well as the more general principle of complex systems conforming to similar descriptions at different levels of analysis. Phase relations for the stretch index demonstrated in-phase attraction in the longitudinal direction and no attraction to any values in the lateral direction. Finally, the difference between the two stretch indexes at any instant showed phase transitions between two stable patterns when the difference was represented in binary form. This result is attributed to the reciprocity between teams in their amounts of expansion and contraction when possession of the ball is won and lost.
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 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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it