Disney Night & theme-night boosts
Finals +0.73 vs own season mean; Disney +0.12; Latin Night -0.42; premieres -1.02.
Ballroom Data · Artometrics-style report · Nov 3, 2026 (America/Los_Angeles)
Headline
Relative to each couple’s own season average, Finals boost scores by +0.73, Halloween by +0.38, and Disney by a modest +0.12. Latin Night actually sits -0.42 below couples’ season means, and premieres drag -1.02.
Theme table (min n=30)
| Theme | Mean | Boost vs season | n |
|---|---|---|---|
| Finals | 9.423 | 0.728 | 458 |
| Halloween | 8.601 | 0.377 | 78 |
| Most Memorable Year | 8.136 | 0.180 | 131 |
| Movie Night | 7.849 | 0.132 | 64 |
| Disney | 7.999 | 0.116 | 160 |
| Latin Night | 7.353 | -0.419 | 105 |
| Premiere / first dances | 6.346 | -1.020 | 338 |
Methods & caveats
Boost = dance judge_mean − that celebrity’s season-wide mean. Theme labels grouped from week_theme text (Disney/Halloween/Latin/Movie/Most Memorable/Finals/Semifinals/Premiere). Semifinals omitted from boost leaders when n filters apply as shown.
Coverage: seasons 1–35; 3,602 performances; 11,027 individual judge marks in the cleaned Ballroom Data SQLite build (Nov 3, 2026, America/Los_Angeles).
Known gaps: Season 31 Mirrorball winner is not tagged as Winners in the performance table (Charli D’Amelio / Mark Ballas is missing from our winners extract). Seasons 33–35 largely lack Kaggle ages/hometowns. Season 35 celebrity names in the wiki scrape are often first-name-only or garbled. Dance-style strings still include some unclean variants. We never impute missing values.
Sources: howisonlab/dwts_dataset (GitHub); Kaggle brupley/dancing-with-the-stars-dataset (CC BY-SA 4.0); Wikipedia DWTS season pages for seasons 32–35 (CC BY-SA 4.0). Scores are per-judge means on a 0–10 scale so 3-judge and 4-judge weeks are comparable. Marathons/relays/megamixes are excluded from style averages unless noted.
Disclaimer: Unofficial fan analysis. Not affiliated with BBC Worldwide, Disney, or ABC.
Downloads
Quarto source, rendered report, chart exports (PNG/SVG), and the analysis CSV.
