Sterlin Thompson is a Colorado Rockies OF projected for 29 fantasy points on 8 R, 11 RBI, 0 SB by the managr projection engine. Monte-Carlo outcome odds put an elite season at 0% and a bust at 10%.
Projection snapshot: 2026-10-18. Rebuilt daily.
Sterlin Thompson's 2026 projection is built on 78 plate appearances in a limited role. Thompson bats left-handed.
Thompson's one season of regular playing time came in 2026 at age 25: 77 plate appearances, 26 total bases and 10 RBI. A single season is a thin base for a projection.
Thompson's projected range runs from a 27-point floor to a 194-point upside, around a 29-point median: a spread of 167 points, or 576% of the median.
By statistical profile, the closest comparisons to Thompson on the board are Hayden Senger, DaShawn Keirsey Jr. and Maverick Handley.
At 25, Thompson is in the age range where hitters 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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Walk-forward backtests, calibration quality, and benchmark comparisons. Run walk-forward first - most tools depend on its pair pool.
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Issues from the most recent data refresh, if any.
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