8 hitters moved up the order, 8 moved down.
Batting order is playing time, and playing time is most of what a hitter is worth. The gap between batting first and batting eighth is roughly one plate appearance a game, about thirty a month, and no rankings page shows it, because a ranking assumes the role it was built with. These are the 16 regulars whose spot in the order has actually moved over the last week, out of 264 with enough starts to judge.
Hitting higher than they were. More plate appearances, more runs, and more chances with men on base.
| Player | Pos | Slot now | Slot before | Move | Starts (7d) | Our rank |
|---|---|---|---|---|---|---|
| Lawrence Butler | OF | 3.2 | 6.7 | up 3.4 | 4 | #411 |
| Steven Kwan | OF | 1.0 | 4.3 | up 3.3 | 4 | #204 |
| Jung Hoo Lee | OF | 2.6 | 5.8 | up 3.2 | 5 | #110 |
| Dylan Crews | OF | 2.0 | 4.8 | up 2.8 | 6 | #462 |
| Jo Adell | OF | 3.4 | 6.0 | up 2.6 | 5 | #237 |
| Francisco Alvarez | C | 5.0 | 7.5 | up 2.5 | 3 | #89 |
| Daniel Susac | C | 6.0 | 8.4 | up 2.4 | 4 | #356 |
| Jakob Marsee | OF | 5.2 | 7.6 | up 2.4 | 5 | #266 |
Dropped in the order. The at-bats go somewhere, and it is usually the first sign a role is being reconsidered.
| Player | Pos | Slot now | Slot before | Move | Starts (7d) | Our rank |
|---|---|---|---|---|---|---|
| Ernie Clement | 2B/SS/3B | 6.7 | 2.8 | down 3.9 | 6 | #108 |
| Brayan Rocchio | SS/2B | 7.2 | 3.4 | down 3.8 | 5 | #145 |
| Christian Yelich | DH | 4.4 | 1.4 | down 3.0 | 5 | #223 |
| Alex Call | OF | 7.0 | 4.0 | down 3.0 | 3 | #696 |
| Anthony Seigler | 2B/3B | 4.2 | 1.3 | down 3.0 | 4 | #629 |
| Cam Cauley | OF/2B | 8.7 | 5.8 | down 2.8 | 3 | #963 |
| Ozzie Albies | 2B | 5.4 | 2.6 | down 2.8 | 5 | #34 |
| Austin Martin | OF | 5.0 | 2.4 | down 2.6 | 5 | #388 |
Steven Kwan is batting first. Not "moved up," not "leading off some days": an average slot of 1.0 across his last four starts is the cleanest signal on this table, because it is the only one with nowhere left to go. A player cannot drift up from leadoff. He was at 4.3 before, which is the slot a manager uses when he is not sure whether the on-base skill or the lack of power is the defining trait. Somebody decided. That kind of move sticks because it is not a reaction to a hot week in the middle of the order, it is a structural choice about who sees the most plate appearances on the roster, and managers who make it tend to leave it alone for months.
Whether it changes what Kwan is worth is a separate question, and here I would be careful. He is ranked 204, and the gap between hitting fourth and hitting first over a full season is somewhere in the range of thirty extra plate appearances a month, which for a high-contact, low-power bat converts into runs and a few steals rather than anything that moves a roto standing sideways. The argument against me is a good one: runs are the category most hostage to lineup slot, and if you are punting power from your outfield anyway, a leadoff man who makes contact is exactly the profile that turns 204 into something closer to top-150 production. I would rather own him now than a week ago. I would not pay a top-150 price.
Francisco Alvarez is the one that meaningfully changes a valuation. He came into the week hitting eighth, essentially, at 7.5, and he is now at 5.0 across three starts. The forward rank is 89, which means the projection already had him as a top-ten catcher regardless of where he hit. The lineup slot was the drag on that number, not the bat. Three starts is a small sample and a manager can undo it with one cold series, so the falsifier is easy to state: if he is back at seventh or eighth inside two weeks, the move was matchup noise and the rank at 89 was already pricing the bat correctly. If he is still hitting fifth in two weeks, the counting stats catch up to the skill and 89 becomes conservative for a catcher.
The demotions are mostly the same story told badly. Ozzie Albies dropped from 2.6 to 5.4 and is still ranked 34, which tells you the engine is not treating five starts in the middle of the order as new information about the player. That is the right instinct. It is also the read a smart manager would push back on, because a switch-hitter who has been moved out of the two hole is usually being moved for a visible reason the data here does not show us. We do not know why. That admission matters more than a guess: nothing in this table separates a rest-and-reset shuffle from the beginning of a permanent slide.
Ernie Clement fell from 2.8 to 6.7 and Christian Yelich from 1.4 to 4.4, and neither drop is priced as fatal at 108 and 223. Yelich is the one I would act on. A DH who has lost the leadoff or two spot has no defensive value propping up his playing time, so if the slot does not come back within two weeks, the floor drops faster than the rank suggests. Sell him into name value now. If you are wrong, you gave up a mid-round outfielder's runs total, which is the cheapest possible way to be wrong here.
Slot is the average spot in the batting order across games actually started. Pinch-hit appearances are excluded, they have no meaningful place in the order and would move an average around at random.
The bar for appearing here is the tenth and ninetieth percentile of everyone with enough starts, recomputed each run. On this window the median change was exactly zero, which is why a player at the tail has genuinely been moved rather than having drifted a little.
Why a manager made a move is not in this data. An injury above them in the order, a platoon, a hot week, all produce the same row, and the cause is not guessed at here.
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.
-
-
-
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.
-
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.
-
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 |
|---|
Enter players for each side, one per line. Values use your scoring weights and injury-adjusted projections.
| Player | Pos | ProjPts | Status |
|---|
| Player | Pos | ProjPts | Status |
|---|
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.