The week's top producers from July 27 to August 2, 2026, led by Ceddanne Rafaela.
The seven days from July 27 to August 2, 2026, sorted by fantasy points actually banked. Points, not rates: a hitter with seven plate appearances and a .571 average had seven chances to do something, and a leaderboard that puts him first is measuring luck rather than production.
| Batter | Team | Pts | PA | HR | R | RBI | SB | AVG | OPS | Our rank |
|---|---|---|---|---|---|---|---|---|---|---|
| Ceddanne Rafaela | BOS | 41 | 31 | 5 | 7 | 11 | 2 | .419 | 1.387 | #69 |
| Alex Bregman | CHC | 32 | 31 | 1 | 8 | 3 | 0 | .429 | 1.234 | #84 |
| Francisco Lindor | NYM | 32 | 30 | 3 | 4 | 8 | 0 | .346 | 1.241 | #80 |
| Yordan Alvarez | HOU | 32 | 30 | 1 | 5 | 7 | 0 | .455 | 1.373 | #2 |
| Kevin McGonigle | DET | 32 | 34 | 2 | 9 | 6 | 0 | .385 | 1.086 | #28 |
| Spencer Torkelson | DET | 30 | 29 | 1 | 7 | 8 | 0 | .423 | 0.991 | #334 |
| Nico Hoerner | CHC | 29 | 27 | 2 | 4 | 7 | 3 | .423 | 1.098 | #52 |
| Shohei Ohtani | LAD | 28 | 23 | 2 | 4 | 6 | 0 | .500 | 1.609 | #1 |
| Eduardo Valencia | DET | 28 | 19 | 2 | 6 | 8 | 0 | .474 | 1.421 | unranked |
| Gleyber Torres | DET | 27 | 28 | 2 | 6 | 9 | 0 | .261 | 1.002 | #74 |
| Pitcher | Team | Pts | IP | K | W | SV | ERA | WHIP | Our rank |
|---|---|---|---|---|---|---|---|---|---|
| Gavin Williams | CLE | 49 | 12.2 | 22 | 1 | 0 | 1.42 | 0.47 | #27 |
| Sandy Alcantara | MIA | 42 | 13.0 | 10 | 2 | 0 | 0.00 | 0.85 | #127 |
| Walbert Urena | LAA | 38 | 12.0 | 12 | 1 | 0 | 0.75 | 0.83 | #597 |
| Pete Fairbanks | MIA | 35 | 4.0 | 5 | 0 | 4 | 0.00 | 0.50 | #348 |
| Gerrit Cole | NYY | 35 | 11.2 | 12 | 2 | 0 | 0.77 | 1.11 | #122 |
| Aroldis Chapman | BOS | 34 | 4.0 | 8 | 1 | 3 | 0.00 | 0.75 | #97 |
| Chase Burns | CIN | 33 | 11.0 | 13 | 1 | 0 | 1.64 | 1.00 | #21 |
| David Peterson | CHC | 33 | 12.0 | 11 | 1 | 0 | 2.25 | 0.83 | #431 |
| Martin Perez | ATL | 30 | 12.0 | 10 | 1 | 0 | 2.25 | 1.00 | #255 |
| Colin Rea | CHC | 29 | 12.0 | 9 | 1 | 0 | 2.25 | 0.83 | #286 |
6 of the 20 players above sit below roster-relevant value on our board despite the week they just had. That is the useful column in these tables. A big week from a top-30 player is confirmation; a big week from someone the engine still will not rank is a sample, and the difference decides whether you are looking at a pickup or at noise.
Five home runs in 31 plate appearances is the loudest line on the board, and Ceddanne Rafaela's forward rank of 69 is the engine's way of saying it liked him before the week and likes him about the same now. That is the useful signal. A 0.419 average across 31 trips will not survive contact with June, but the two steals sitting under the five homers are the part that carries: Rafaela's fantasy value has always been the combination, not the power spike. Nobody is trading him to you cheaply now. If you own him, the correct move is nothing at all, and if you are shopping, wait for the average to normalize and the price to follow it down.
The week I would actually chase is Gavin Williams. Forty-nine points on 12.2 innings with 22 strikeouts is the rare big week where the components are the whole story rather than the luck, and a forward rank of 27 confirms the engine wasn't reacting to the box score. Twenty-two punchouts in two starts is a rate no defense and no sequencing luck produces for you. Chase Burns sits one spot ahead of him at 21 on 13 strikeouts in 11 innings, which tells you these two are already priced as front-end arms rather than as hot streaks. Hold both. The cost of selling Williams on a 1.42 ERA is that you sell the strikeout rate along with it.
Now the sells, and they are not close. Spencer Torkelson put up 30 points on eight RBI and a 0.423 average, and the engine ranks him 334th going forward. One home run in 29 plate appearances is the tell: this was an RBI week produced by the Detroit lineup turning over in front of him, not by Torkelson doing anything new. Gleyber Torres drove in nine with a 0.261 average in the same lineup, which is the same story from a different seat. Torkelson at 334 is a bench bat in most formats and a waiver-wire piece in shallow ones. The strongest case against selling is that first-base scarcity is real and eight RBI in a week is eight RBI regardless of how they arrived. Fine. But you are buying the lineup, not the hitter, and the lineup can change on a lineup card.
Walbert Urena is the starkest gap on the page and the clearest ignore. Twelve innings, twelve strikeouts, a 0.75 ERA, and a forward rank of 597. Almost nothing produces a number that far down except a projection built on a thin track record and a strikeout rate that does not support the run prevention: twelve in twelve innings is ordinary, and ordinary strikeout stuff running a sub-one ERA is the definition of a week that regresses. David Peterson at 431 and Colin Rea at 286 are the same shape, both of them 12 innings with fewer than a strikeout an inning. If you have a free roster spot in a deep league, streaming Urena against a soft opponent is defensible. Rostering him as a held asset is not.
Here is the test I would set. Urena's next two starts settle it: if he is still striking out roughly one per inning and the ERA climbs toward four, the engine was right and you drop him without a second thought. If he pushes past ten strikeouts per nine, the 597 was built on missing information and the market will be slower to notice than you are. For Torkelson, watch where he hits. Cleanup with runners in front of him keeps the RBI flowing; a drop to sixth or seventh kills the only thing holding his week up.
Points are the window total from our own scoring, over the exact dates named above. Sorting on points rather than on rate stats means playing time counts for something, which is how fantasy actually works, a player who sat four of seven days did not help you, whatever he hit when he played.
Our rank is the engine's view looking forward, not a grade on the week. The two disagreeing is the interesting case, not an error: the week is what happened, and the rank is what we expect next.
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.