Correlation Between Elite Women’s Wheelchair Basketball Skills Testing And Future Success In The Sport
Bibliographic record
Abstract
INTRODUCTION: Wheelchair basketball practices are built around developing technical and tactical skills required in game situations. To assess performance of these skills, testing protocols have been developed. This allows both player and coach to determine improvements. However, does achieving high scores on skills tests translate to success on the basketball court during competition. PURPOSE: The purpose of this analysis was to determine the relationship between skills test results and performance during competition as determined by the average efficiency scores. METHODS: In April, 2013, 25 female wheelchair basketball players were invited to compete for positions on the 2014 National Wheelchair Basketball Association (NWBA) Senior Women’s National Team. Skills tests were similar to those used at NWBA/PVA National Wheelchair Basketball Camps. Strength testing assessments were developed by a panel of NWBA Coaches with a history of National and International coaching experience. The results were then correlated with the box scores and player efficiency ratings obtained during the playoffs at the International Wheelchair Basketball Federation (IWBF) Women’s World Wheelchair Basketball Championship in Toronto, June, 2014. The USA Women’s team was divided into two groups by classification (players with functional classifications of 1.0, 1.5 and 2.0 represented Group 1 and players with functional classification of 2.5, 3.0, 3.5, 4.0 and 4.5 represented Group 2) for analysis. RESULTS: Player efficiency was differentially related to skills tests based on player classification. Among Group 1 players, higher player efficiency ratings during the World Championship games corresponded directly with better non-dominant passing (accuracy r = .95, p = .05; stationary distance r = 1.00, p < .001; moving distance r = 1.00, p < .001). In contrast, higher percentage of free throws was directly related to better player efficiency for the players in Group 2 (r = 1.00, p < .001). CONCLUSIONS: Findings may represent differential skill sets needed by lower and higher class players. Passing, in particular non-dominant passing skills, may give players with a lower classifications an advantage on the court; whereas, accuracy of free throws (and more opportunity) may be a skill that sets players with higher classification apart.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".