CHC vs PIT prediction for May 26, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects PIT 3.7 - CHC 4.5. CHC is favored with a 56.2% win probability. The run line is -1.5 and the total is 8.5. Model projects 8.2 total runs.
PIT
3.7
Projected Score
VS
O/U 8.5
CHC
4.5
Projected Score
Win Probability
PITCHC
-1.5
Run Line (PIT)
8.5
Total Line
10,000
Simulations
Calibrated accuracy at this confidence: 53.9% (2,300 games)
Projected Runs Range 10th – 90th percentile
CHC
346
PIT
246
Projected
PIT 3.7 — CHC 4.5
Actual
PIT 12 — CHC 1
Starting Pitcher Matchup
Jordan Wicks L
CHC
FF40%94 mph10% whiff
CH24%83 mph48% whiff
SL13%87 mph29% whiff
Braxton Ashcraft R
PIT
FF32%97 mph14% whiff
CU26%85 mph38% whiff
SL22%92 mph35% whiff
Weather Impact
PNC Park
82°F6 mph wind
HR: 1.012 Total: 1.004
thin air, 6mph in
Bullpen Comparison
CHC
3.81ERA
5.08FIP
8.23K/9
4.11BB/9
1.32WHIP
PIT
4.18ERA
4.16FIP
9.24K/9
4.37BB/9
1.37WHIP
Betting Edges
RUN_LINE AWAY +1.5
-28.7% EV
-192
RUN_LINE HOME -1.5
-23.7% EV
+160
F5_ML HOME
-20.1% EV
-147
ML HOME
-19.5% EV
-133
ML AWAY
+15.6% EV
+114
F5_ML AWAY
+14.3% EV
+118
First 5 Innings & NRFI
CHC F5
2.1 runs
45.0% win
PIT F5
1.8 runs
36.0% win
F5 Total
3.9
NRFI
63.7%
YRFI
36.3%
Avg 1st Inn Runs
0.70
HR Spotlight
Avg HRs
2.0
Over 0.5 HR
86%
Over 1.5 HR
58%
No HR
14%
Michael Busch CHC21.2%
ISO: 0.194 | Barrel: 8.2% | vs Braxton Ashcraft | Park: 0.95x Platoon: 1.12x
Brandon Lowe PIT19.9%
ISO: 0.173 | Barrel: 16.4% | vs Jordan Wicks | Park: 0.95x
Oneil Cruz PIT14.6%
ISO: 0.223 | Barrel: 11.4% | vs Jordan Wicks | Park: 0.95x
Pitcher Strikeout Projections
Jordan Wicks
0.0 K projected
CHC | K/9: 0.0
Braxton Ashcraft
0.0 K projected
PIT | K/9: 0.0
Injury Report
CHC8 injured
Edward Cabrera SP15-DAY-IL
Matt Shaw RF10-DAY-IL
Hunter Harvey RP60-DAY-IL
Matthew Boyd SP15-DAY-IL
Brandon Birdsell RPDAY-TO-DAY
Jeff Brigham RPDAY-TO-DAY
+2 more
PIT8 injured
Ryan O'Hearn RF10-DAY-IL
Jared Jones SP60-DAY-IL
Chris Devenski RP15-DAY-IL
Joey Bart C10-DAY-IL
Anthony Solometo SPDAY-TO-DAY
Oddanier Mosqueda RPDAY-TO-DAY
+2 more
AI Intelligence Analysis
STRONG BET +1RED ZONE43.9% WR (n=169)
Market has massively overestimated PIT home value: -133 ML prices PIT at 57.1% (46.7% CHC away), yet model projects 56.2% CHC away win prob. The edge: 15.6% (+9.3 to model). Braxton Ashcraft (PIT, 3.12 ERA, B grade stuff) is legitimately better than Jordan Wicks (CHC, debut/TBD), BUT the market is heavily overweighting the home-field advantage. Ashcraft's 3.12 ERA and B-grade command (0.62 stuff grade) is good, but Wicks is an unknown commodity (young LHP). Model sees through the home bias and identifies value in CHC as away underdog. Weather supports this: 81.7F warm but 5.7 mph wind blowing IN (into field, not out) reduces home run potential. Park factor 1.0 (neutral). However, zone data shows away ML is RED (43.9% WR historically), which conflicts with the model's 15.6% edge call. This is a COMMON case where high edge correlates with model overconfidence. Moderate bet with unit_modifier 1.0 (not 1.5) to respect zone warning.
Key Factors
- Ashcraft (PIT): 3.12 ERA, 8.0 K-rate, B stuff grade (0.539) — legitimate starter quality
- Wicks (CHC): Unknown debut SP, no ERA data; model has limited information
- Market pricing: -133 PIT = 57.1% implied vs model 56.2% — 0.9% gap but 15.6% edge claim suggests model overconfident
- Wind: 5.7 mph blowing IN (negative -5.7) reduces HR potential; neutral effect on sides
- Temperature 81.7F: Warm, slight boost to base hits but not determinative
Risk Factors
- High edge (15.6%) = red flag per calibration (zone 43.9% WR). Model likely overconfident.
- Wicks is TBD; if he pitches well, edge materializes. If rough outing, CHC value evaporates.
- Away ML historically weak (RED zone 43.9% WR)
PITCHER MISMATCHHIGH EDGE WARNINGRED ZONE AWAY MLWEATHER INYOUNG SP RISK
Edge Analysis
Moneyline
CHC 56.2%
-23.7 pts
Run Line
-1.5
-23.7 pts
Total
8.5
+0.9 pts
How this prediction was generated: This page shows output from the Olympus Bets MLB Baseball Monte Carlo engine. Each game is simulated 10,000 times using real-time team data, injury reports, and current odds. Probabilities are calibrated using Bayesian methods and sized via the Kelly Criterion. Full methodology →