musmem-mislabeled-divisions

Duplicate placements in bodybuilding contest data are detected by scanning files grouped by year, contest, and division. The script flags divisions where a placement appears more than once and the next sequential placement also exists, outputting structured results with athlete names and source files.

Mislabeled division detection processes male and female bodybuilding files separately across main and prelim datasets to avoid cross-gender comparisons. It groups records by year, contest, and division, then flags suspicious duplicate placements within those isolated file groupings.

The best way to scan contest results for data quality issues is using a script that categorizes flagged divisions into HIGH, MED, and LOW severity levels based on the number of suspicious placements. It excludes placements of 90 or higher and outputs a structured report.

Duplicate placements across divisions in bodybuilding contest data indicate potential mislabeling. The detection script flags instances where a placement appears more than once and the subsequent sequential placement also exists, excluding placement values of 90 or higher.

Limitations when scanning bodybuilding contest files for mislabeled divisions include the exclusion of placements valued at 90 or higher. The script requires distinct per-file groupings for male/female and prelim/main datasets to accurately flag suspicious duplicate placements without cross-gender comparisons.