Nic Enright is a RP projected for 0 fantasy points on 0 IP, 0 K, 3.9 ERA, 1.409 WHIP by the managr projection engine. Monte-Carlo outcome odds put an elite season at 0% and a bust at 13%.
Projection snapshot: 2026-10-18. Rebuilt daily.
Enright's one season with meaningful innings came in 2025 at age 28: 31 innings with 30 strikeouts. A single season is a thin base for a projection.
Tracking data from 2025: Enright struck out 23.6% of batters and walked 9.4%, a strikeout-minus-walk rate of 14.2 points, and hitters missed on 26.4% of their swings. Contact against Enright averaged 87.8 mph off the bat, with a 6.0% barrel rate.
Enright's projected range runs from an 85-point floor to a 135-point upside, around a 92-point median: a spread of 50 points, or 54% of the median.
By statistical profile, the closest comparisons to Enright on the board are Nick Hernandez, Logan VanWey and Grant Holman.
At 29, Enright 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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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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