Statistical Analysis for the First Bundesliga in the Current Soccer Season
Bibliographic record
Abstract
Statistical analysis for the 153 matches of First Bundesliga, i.e. the first national soccer league in Germany, in the first 17 “playing days” (August 10, 2013 to January 29, 2014) of the current soccer season was made. Various team parameters were compared between the winning and losing teams in the 118 non-drawing matches. The results support the conclusions of our earlier analysis (Yue, Broich, & Mester, 2014) that the quality of shots, represented by the goal efficiency, defined by the number of goals divided by the number of shots, is more important than the quantity of shots for winning a soccer game. This conclusion is also confirmed by the correlation analysis based on all the 153 matches: The correlation between the number of goals and the goal efficiency is found to be much stronger than the correlation between the number of goals and the number of shots. The team parameters of the second to the fourth importance are the number of shots, the number of passes and the number of ball contacts respectively. In contrast, the distance coverage is found to be statistically not important for winning a game.
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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 | 0.010 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".