The league had two methodologies: the original Google Sheet model (we’ll call it v1) and a new z-score model (v2). Both are computed from every season’s real data; you can toggle between them anywhere on the site.
The v2 z-score model in plain English
- Magnitude preservation. A z-score says how many standard deviations above or below the league mean a manager landed that season. +1σ on win % means exactly the same thing as +1σ on points, regardless of how spread out the league was.
- Comparability across metrics.Final standing, win %, share of points, and all-play win % have wildly different scales. Z-scoring puts them on the same axis so the weighted average is meaningful.
- Era-comparability. Yahoo era (2019–2022) had no weekly score data, so it uses 3 components renormalized to 1/3 each. The Sleeper era (2023+) adds the all-play component and uses 4 × 0.25. Both produce comparable career numbers because z-scoring strips out scale differences.
- Win % excludes the median game.2024 added the median bonus; counting it would silently inflate Sleeper-era win % relative to Yahoo. The v2 model uses head-to-head wins only, so the same season has the same meaning across eras.
- Display scale. The raw career number is roughly in [-1.0, +1.0]. We rescale to 1250 + 100·raw (Elo-anchored): 1250 ≈ a perfectly average career, +1σ ≈ 1350.
- Low-confidence flag.A manager with fewer than 3 seasons has a career mean that’s very sensitive to a single outlier season. We visually flag those rows so a 2-season manager isn’t mistaken for a steady performer.
The v1 spreadsheet model in plain English
The original model scores three things, then adds a loyalty/trophy bonus. It’s rank-based: within each category every manager is ordered against the whole field, and that rank — not the raw number — is converted to a 0–10 score, so each category is graded on a curve.
- Three weighted categories. Final standing is worth 60% (×0.6), share of points 30% (×0.3), and head-to-head win % just 10% (×0.1). The bias is deliberate — how you actually finished counts far more than a lucky or unlucky regular-season record.
- Value-table lookup.A manager’s rank in a category becomes a score of (N + 1 − rank) / N × 10 across the N-manager pool — 1st ≈ 10, last ≈ 0. The three category scores are blended by the weights above into a “weighted power” number out of 10.
- Legacy bonus. Added on top to reward longevity and hardware: +0.2 per season played, +0.2 per playoff appearance, and +0.6 per championship. This is why a long-tenured manager can edge out a flashier short-timer.
- Total score. Weighted power + legacy bonus — the single number behind the all-time v1 ranking.
v1 ↔ v2 side-by-side
Same managers, same seasons, two different formulas. Δ is how far a manager moves when you switch from v1 to v2 (positive = climbs in v2).
Worked example: Kevin Hulsebosch (v2 rank 1)
Each row is one season. The weighted column is that season’s contribution to the career mean. The σ columns are the per-component z-scores (higher = better).
| Year | Era | Final z | Win% z | Share z | All-play z | Weighted |
|---|
| 2019 | yahoo | 0.87 | 1.86 | 1.44 | — | 1.39 |
| 2020 | yahoo | -0.17 | 0.35 | 1.81 | — | 0.66 |
| 2021 | yahoo | 1.22 | 0.42 | 0.34 | — | 0.66 |
| 2022 | yahoo | -0.53 | -0.37 | -0.62 | — | -0.51 |
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The v1 formula reproduces the original spreadsheet within ±0.01. Both models are now recomputed from the live database every week, so the toggle stays apples-to-apples as new seasons land.
| 2024 | sleeper | 1.22 | 1.43 | 1.23 | 1.42 | 1.33 |
| 2025 | sleeper | 1.22 | 1.05 | 1.59 | 1.54 | 1.35 |
Hover any σ cell for the percentile-rank intuition.