We graded 850 top-100 rankings from 2011 to 2019 against seven years of real fantasy production. The results changed how our Prospect Value board works.
Every winter the top-100 lists arrive, and every winter dynasty managers treat them as gospel. So we graded the gospel. We took every MLB Pipeline top-100 ranking from 2011 through 2019, 850 rankings covering 466 players, from Mike Trout to the deepest busts, and measured what actually happened over the next seven seasons: who reached the majors, who produced a usable fantasy season, who became a star, and who vanished.
The bars are set from real seasons, not vibes. A useful season is what a top-150 overall player scores in ESPN points (310). A star season is a top-50 year (405). A superstar season is a top-25 year (455). Here is what each slice of the list delivered:
Classes 2011 to 2019, outcomes through 2025. Peak = best single season in the seven-year window, 2020 prorated to a full schedule.
| Rank band | Reached MLB | Useful season | Star season | Superstar | Median peak |
|---|---|---|---|---|---|
| Ranks 1 to 10 | 100% | 68% | 46% | 33% | 385 |
| Ranks 11 to 25 | 98% | 49% | 29% | 18% | 303 |
| Ranks 26 to 50 | 96% | 44% | 17% | 11% | 278 |
| Ranks 51 to 75 | 96% | 34% | 12% | 6% | 226 |
| Ranks 76 to 100 | 92% | 26% | 11% | 4% | 156 |
The old worry, will he even make it, is basically dead for top-100 prospects: 92 to 100 percent of them reach the majors within seven years. The real spread is in mattering. A back-of-the-list prospect debuts almost as reliably as a top-10 one, but he delivers a usable fantasy season about a quarter of the time versus two-thirds for the elite tier. Stop asking if a prospect will arrive. Ask how often his slot of the list produces a season you would actually start.
Once you deduplicate players to their first appearance, first-time top-10 prospects produced a superstar season 48 percent of the time. But from rank 26 down to 100, star rates flatten into a band the data cannot statistically tell apart. A number 55 and a number 85 are, in outcome terms, the same lottery ticket. Treat the back half of any top-100 as one big tier and trade accordingly: the market pays a premium for number 40 over number 80 that history says is mostly noise.
There is no such thing as a pitching prospect, the saying goes. At the top of the list, it is simply wrong: top-10 pitchers produced a star season 48 percent of the time versus 44 percent for hitters, and back-of-list arms edged bats too. Pitcher risk is real, but it shows up as injury attrition along the way, not as a lower ceiling for the elite arms. Do not pass on a truly elite arm out of proverb.
Here is the finding that changed our model. Among top-25 hitters, the young ones dominate: bats ranked at age 20 or younger starred 50 percent of the time versus 24 percent for the older group. Among top-25 pitchers it inverts: teenage arms starred just 19 percent of the time while arms aged 22 to 23, the polished college types, hit 38 percent. Youth is a premium for bats and a caution flag for arms. As of this week, the Managr Prospect Value board applies its youth curve to hitters only; pitchers are scored age-neutral. Polished arms like Kade Anderson no longer get docked for being 21 instead of 18.
Prospects who climbed 15 or more spots between lists went on to star at double the rate of stable ones, and that edge survives controlling for rank. But fallers who stayed on the list performed just like stable prospects, because the fall itself already repriced them. Our board kept its bonus for risers and retired its penalty for fallers: a prospect who slid from 30 to 50 was being punished twice, once by the rank and once by us. Sliding catchers like Ethan Salas are the classic case the old penalty got wrong.
We also graded FanGraphs future value marks for the 2017 to 2020 classes. As a forecast the editorial rank beat the grade head to head in all four classes, but the FV ladder is still the cleanest mental model a dynasty manager can carry:
An FV 60 is roughly a one-in-four star. An FV 45 is one in twenty-five. Classes 2017 to 2020, seven-year windows.
| Scouting grade | Prospects | Useful season | Star season |
|---|---|---|---|
| FV 65 or higher | 22 | 68% | 36% |
| FV 60 | 60 | 42% | 23% |
| FV 55 | 123 | 33% | 15% |
| FV 50 | 319 | 25% | 10% |
| FV 45 | 600 | 12% | 4% |
| FV 40 | 1605 | 5% | 2% |
Today's board reflects all of this: Jesús Made holds the top spot on the strength of the signals that actually predict, elite rank, elite youth for a bat, and a climbing trajectory.
Top-100 prospects almost all debut; the question is whether they matter. The list is sharp through rank 25 and mostly one big tier after that. Elite pitching prospects hit like elite hitting prospects. Youth predicts stardom for bats and works against teenage arms, so our Prospect Value board now ages hitters and pitchers differently, and it no longer double-punishes fallers. The full method, the calibration tables and the study you can rerun yourself all live on the Methodology page.
Curated picks where the model has the highest decision conviction. Updated every render.
Run rankings to populate Market Edge.
Run rankings first.
Mark a player as drafted to get a recommendation.
Studies and awards - the research-side surfaces of the managr platform.
Live snapshot of the projection system.
Backtest, parsimony, ablation, and benchmark - one synthesized report. Output renders in Validation.
Final Value = Raw Projection × MasterConfidence × TeamContext. Each layer answers one question - no overlap.
Recency weighting: prior seasons contribute by recency (more recent = more weight) and sample size (more PA = more weight).
Shrinkage: observed rates regress toward position-specific population means by an amount inversely proportional to sample size. Catches small-sample outliers.
Quality-of-contact adjustments: xwOBA, barrel rate, and bat-tracking metrics replace luck-driven outcome stats with skill-driven ones.
PT modeling: projected PA is anchored to workload tier (full-time, regular, platoon, backup catcher) using historical role distributions.
Monte Carlo: N simulated seasons per player using projected mean + uncertainty, producing P10 / P50 / P90 distribution and bust%.
Confidence layers: four orthogonal multipliers: Roster (depth chart), Role (PT certainty), Sample (career PA), Market (consensus alignment). The Audit tab shows all four for every player.
VAR: Value Above Replacement at the player's primary position. Replacement levels are floored per position so SS scarcity doesn't artificially inflate stable middle infielders.
Tune component weights against historical seasons. Stored in session.
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Walk-forward backtests, calibration quality, and benchmark comparisons. Run walk-forward first - most tools depend on its pair pool.
Projects every historical batter-season from prior data only. Reports RMSE, MAE, Spearman ρ, hit rates. Populates the pair pool other validators use.
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Distribution, uncertainty, per-archetype performance, calibrated tiers, draft sim.
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Where the model finds value the market is missing.
Curated picks from current rankings.
Where the model has measurable advantage.
The safety layer. Realism, false-confidence, forensics - what to remove.
The most important governance tools. Output renders in Validation.
Per-era ablation, error clusters, bias, correlations, removals. Each tells you what to remove. Run walk-forward first.
The smallest model that retains predictive power. Every feature beats the burden of proof.
Live pipeline status and data freshness.
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Last known status of each underlying data source.
Source status will appear once data has been refreshed.
Issues from the most recent data refresh, if any.
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MVP, Cy Young, Rookie of the Year - historical winners with their stats, plus model-predicted current-season winners.
Predictions from the current 2026 projection model. Top candidates per award based on projected fantasy points + advanced-stat underlying. League assignment from current team.
Coaching rosters for every MLB team plus a multi-year Fantasy Points Above Average ranking of every MLB coach.
Findings article + all-time top-100 performer leaderboard from every World Baseball Classic (2006-2026).
A growing collection of fantasy baseball studies. Each card opens a detail page with the methodology, the data sources, and (where the data exists today) live computed findings.
Active player injuries, refreshed from upstream sources.
| Player | Team | Pos | Status | Explanation | Replacement |
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Enter players for each side, one per line. Values use your scoring weights and injury-adjusted projections.
| Player | Pos | ProjPts | Status |
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Every signal, formula, and data source the model uses for player evaluation - organized by product.
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