Sean Reynolds is a RP projected for 0 fantasy points on 0 IP, 0 K, 3.9 ERA, 1.354 WHIP by the managr projection engine. Monte-Carlo outcome odds put an elite season at 0% and a bust at 18%.
Projection snapshot: 2026-10-18. Rebuilt daily.
Reynolds's one season with meaningful innings came in 2025 at age 27: 27 innings with 25 strikeouts. A single season is a thin base for a projection.
Tracking data from 2025: Reynolds struck out 21.4% of batters and walked 14.5%, a strikeout-minus-walk rate of 6.9 points, and hitters missed on 22.7% of their swings. Contact against Reynolds averaged 90.3 mph off the bat, with an 11.1% barrel rate.
Reynolds's projected range runs from an 86-point floor to a 148-point upside, around a 92-point median: a spread of 62 points, or 67% of the median.
By statistical profile, the closest comparisons to Reynolds on the board are Brandon Waddell, Caleb Boushley and Bailey Horn.
At 28, Reynolds is in the age range where pitchers typically hold their skills.
This report is generated from the managr engine's 2026-10-18 snapshot and rebuilt daily.
Curated picks where the model has the highest decision conviction. Updated every render.
Run rankings to populate Market Edge.
Run rankings first.
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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.
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The most important governance tools. Output renders in Validation.
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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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Findings article + all-time top-100 performer leaderboard from every World Baseball Classic (2006-2026).
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