US-American professional IRONMAN® triathletes dominate participation but not performance in IRONMAN® races – an internet-based cross-sectional study using a machine learning approach (Preprint)
Bibliographic record
Abstract
BACKGROUND Since the first edition of IRONMAN® Hawaii in 1981, the number of races and finishers in the IRONMAN® format has increased considerably. Scientific literature has provided many insights into this specific sport discipline. However, we have no knowledge of where the fastest professional IRONMAN® triathletes originate and where the fastest IRONMAN® race courses take place. OBJECTIVE The aim of the present study was to investigate where in the world the fastest IRONMAN® race courses for professional IRONMAN® triathletes are. METHODS Data of all professional female and male IRONMAN® triathletes competing between 2002 and 2022 in all official IRONMAN® races were collected. A total of 6,954 finishers´ records (2,788 women and 4,166 men) from 68 different countries participating in 56 different event locations were considered. Data were analyzed using machine learning (ML) regression models. The models considered gender, country of origin, and event location as independent variables to predict the final race time. Five different algorithms (Random Forest Regressor, XG Boost Regressor, Ada Boost Regressor, Cat Boot Regressor, and Decision Tree Regressor) were examined. RESULTS The race site was the most important variable for the Random Forest Regressor model, while for the other four models, gender was the most important variable. A decision tree algorithm, trained with data from 2002 to 2022, showed that the fastest overall IRONMAN® race times of 08:38:48 h:min:s will be obtained in IRONMAN® Hawaii, IRONMAN® Florida, IRONMAN® Austria, IRONMAN® France, IRONMAN® Wisconsin, IRONMAN® Lanzarote or IRONMAN® Texas by male professional IRONMAN® triathletes originating from any other country than USA, Germany or Canada. Most of the professional IRONMAN® triathletes originated from the USA (1,786), followed by athletes from Germany (674) and Canada (427). Most athletes competed in IRONMAN® Hawaii (926), followed by IRONMAN® Florida (564) and IRONMAN® Austria (454). CONCLUSIONS The fastest IRONMAN® race courses for professional IRONMAN® triathletes are predominately located in the USA. Most of the professional IRONMAN® triathletes originated from the USA. The fastest IRONMAN® race times were achieved by male professional IRONMAN® triathletes originating from any other country than USA, Germany, or Canada. These insights are useful for athletes and coaches in planning their professional IRONMAN® career.
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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 | 0.002 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".