2 players changed hands in 7 days. 0 of them are ranked, here they are, by value.
Thirty clubs made 2 acquisitions by trade in the last 7 days. 0 of them are ranked on the managr board; the rest are not, which is itself the answer for most of them.
The list every site publishes is the transaction log. The list that decides your week is much shorter, so this is that one, the traded players who carry real projected value, ordered by it.
Proj pts is the engine's current full-season projection and Value is its replacement-adjusted fantasy value, the number the boards sort on. Both are read from the board as it stands today.
These are the projections as they currently stand, not a re-forecast of what the new park, lineup slot or bullpen role will do to them. A hitter moving into a better lineup and one moving out of one look identical in this table. Treat it as "here is who changed hands and how much fantasy value was involved", not as a verdict on the trade.
Traded but unranked (2): Christian Bethancourt, Logan Driscoll. Not being on the board is a projection in itself, the engine ranks roughly 1,300 players, so absence means it does not currently see startable value.
| Date | Player | To |
|---|---|---|
| 2026-08-20 | Logan Driscoll | Miami Marlins |
| 2026-08-19 | Christian Bethancourt | Pittsburgh Pirates |
Source: MLB Stats API transactions, joined to the managr board by player id. This piece is generated daily from those two feeds.
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.
Walk-forward over historical seasons. Reports RMSE, MAE, Spearman ρ, top-N hit rates.
Distribution, uncertainty, per-archetype performance, calibrated tiers, draft sim.
Load any rival projection or ADP source. Auto-detects player_name + rank / adp / projected.
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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| Player | Pos | ProjPts | Status |
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Every signal, formula, and data source the model uses for player evaluation - organized by product.
Configure your draft session. This stays on this device only.