Trent Harris is a San Francisco Giants RP projected for 70 fantasy points on 25.4 IP, 29 K, 2.5 ERA, 1.182 WHIP, 2 SV by the managr projection engine. Monte-Carlo outcome odds put an elite season at 0% and a bust at 14%.
Projection snapshot: 2026-10-18. Rebuilt daily.
Trent Harris's 2026 projection is built on 25 innings out of the bullpen.
Harris's one season with meaningful innings came in 2026 at age 27: 23 innings with 27 strikeouts. A single season is a thin base for a projection.
Harris's projected range runs from a 66-point floor to a 108-point upside, around a 70-point median: a spread of 42 points, or 60% of the median.
By statistical profile, the closest comparisons to Harris on the board are Nate Lavender, Jayden Murray and Franco Aleman.
At 27, Harris 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.
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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%.
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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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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.
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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.
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