Measuring Athlete Exposure and Body Contact Using Time-on-Task Technology in Ice Hockey
Bibliographic record
Abstract
It is common for athlete exposure (AE) and body contact (BC) to be incorrectly estimated in epidemiologic research due to the technical challenges associated with field-based research in ice hockey. Time-on-task technology has shown promise in accurately quantifying AE and BC using computer technology through direct measurement during real time games. The purpose of this prospective cohort study was to adopt time-on-task technology to monitor AE and BC in Atom hockey players who were permitted body checking versus those not allowed to body check. We evaluated 579 boys (age 9–10 year olds) from 42 representative Atom hockey teams over 107 games during the 2003–2004 regular season from five hockey associations using a time-on-task computing program running on a tablet computer. Body checking was allowed in four associations [Northern Ontario Hockey Association (NOHA), Minor Hockey Alliance of Ontario, Ontario Minor Hockey Association, Greater Toronto Hockey League], while one association was non-body checking (HNO). Body contact was 4.5 times greater in the body checking associations versus the non-body checking association per game. No significant difference in mean AE per game was found between body checking and non-body checking associations. However, greater AE was reported in NOHA games compared to the remaining four associations. Conversely, BC in the NOHA was significantly less compared to the remaining body checking associations, but not the HNO. Time-on-task technology was valuable in monitoring AE and BC, accounting for variability in individual players. Expected AE and BC was observed between checking and non-body checking associations. Unexpectedly larger AE in NOHA is attributed to smaller team roster size and longer duration games. Furthermore, decreased BC in NOHA players may be due to smaller roster size intrinsic factors contributing to the inverse relationship between AE and BC. Time-on-task technology is valuable in monitoring AE and BC in Atom ice hockey. This is a practical method of monitoring important aspects of the game.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".