STL vs CHC prediction for July 5, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects CHC 4.4 - STL 3.3. CHC is favored with a 63.7% win probability. The run line is -1.5 and the total is 8.0. Model projects 7.7 total runs.
CHC
4.4
Projected Score
VS
O/U 8.0
STL
3.3
Projected Score
Win Probability
CHCSTL
-1.5
Run Line (CHC)
8.0
Total Line
10,000
Simulations
Calibrated accuracy at this confidence: 64.3% (2,777 games)
Projected Runs Range 10th – 90th percentile
STL
135
CHC
246
Projected
CHC 4.4 — STL 3.3
Actual
CHC 6 — STL 4
Starting Pitcher Matchup
Matthew Liberatore L
STL
FF32%94 mph12% whiff
SL22%86 mph34% whiff
CU17%80 mph32% whiff
Javier Assad R
CHC
SI40%93 mph7% whiff
FF18%93 mph13% whiff
FC15%88 mph14% whiff
Weather Impact
Wrigley Field
71°F11 mph wind
HR: 1.041 Total: 1.021
thin air
Bullpen Comparison
STL
4.30ERA
4.29FIP
8.27K/9
4.08BB/9
1.36WHIP
CHC
4.04ERA
5.13FIP
8.17K/9
4.04BB/9
1.34WHIP
Betting Edges
RUN_LINE AWAY +1.5
-46.2% EV
-172
TOTAL OVER 8.0
-23.3% EV
-119
F5_ML AWAY
-20.4% EV
+124
TOTAL UNDER 8.0
+15.4% EV
-102
ML AWAY
-13.2% EV
+124
RUN_LINE HOME -1.5
+10.3% EV
+141
First 5 Innings & NRFI
STL F5
1.6 runs
28.4% win
CHC F5
2.7 runs
56.3% win
F5 Total
4.3
NRFI
56.2%
YRFI
43.8%
Avg 1st Inn Runs
0.89
HR Spotlight
Avg HRs
2.7
Over 0.5 HR
93%
Over 1.5 HR
73%
No HR
7%
Pete Crow-Armstrong CHC30.0%
ISO: 0.138 | Barrel: 13.0% | vs Matthew Liberatore | Park: 1.03x
Ian Happ CHC21.4%
ISO: 0.192 | Barrel: 10.4% | vs Matthew Liberatore | Park: 1.03x Platoon: 1.12x
Dansby Swanson CHC20.6%
ISO: 0.172 | Barrel: 11.7% | vs Matthew Liberatore | Park: 1.03x Platoon: 1.12x
Pitcher Strikeout Projections
Matthew Liberatore
0.0 K projected
STL | K/9: 0.0
Javier Assad
0.0 K projected
CHC | K/9: 0.0
Injury Report
STL2 injured
Dustin May SPDAY-TO-DAY
Ramon Urias 3B60-DAY-IL
CHC8 injured
Matt Shaw RF10-DAY-IL
Edward Cabrera SP15-DAY-IL
Jameson Taillon SP15-DAY-IL
Ethan Roberts RP15-DAY-IL
Daniel Palencia RP15-DAY-IL
Hoby Milner RP15-DAY-IL
+2 more
AI Intelligence Analysis
LEAN +1YELLOW ZONE56.0% WR (n=156)
CHC home with strong pitcher quality: Javier Assad (C+ grade, 5.7 K-rate — EXTREMELY low, D stuff score 0.08, but elite command 73.4% score 0.734) vs Matthew Liberatore (B- grade, 8.3 K-rate, 35.9% stuff score). Assad is a contact pitcher with incredible command; Liberatore is a strikeout-prone left-hander. Model shows CHC ML edge of 2.3% (61.2% win prob), which is light, but the RUN LINE at HOME -1.5 shows 10.3% edge (45.8% cover rate). This suggests the model sees a 2-3 run gap favoring CHC, not just a directional flip. Given Assad's elite command (73.4% score is elite), Liberatore's elevated BB rate (8.8% when he's not a top command guy), and CHC home field advantage (+3% park factor at Wrigley), I lean CHC. The UNDER 8.0 at 15.4% edge is also compelling: Assad's low K-rate (5.7) combined with Liberatore's 8.3 K-rate suggests fewer strikeouts but doesn't necessarily mean more runs scored — contact pitchers can suppress runs via weak contact. Weather: 70.6F, windy (11.1 mph, tail wind 1.9 mph away from hitters) — slight under bias. LEAN CHC ML or RUN LINE -1.5, but the -149 odds are fair for a 61% team, so prefer the run line at +103% implied (roughly -110 equivalent).
Key Factors
- Assad vs Liberatore: Assad elite 73.4% command score (contact pitcher, 5.7 K-rate) vs Liberatore 8.3 K-rate with 49.5% command — Assad's control is elite
- Liberatore elevated BB rate 8.8% vs Assad 6.3% — walk suppression favors Assad
- CHC home field: +3% park factor, historical advantage in pitcher-friendly parks
- Weather: 70.6F (cool), 11.1 mph wind with slight tail component away from hitters — reduces offensive production by 0.3-0.7 run
- Run line edge (10.3%) is stronger signal than ML edge (2.3%)
Risk Factors
- Light ML edge (2.3%) within noise range; market (-149) is nearly fair
- STL is respectable team despite lower seed; not a clear underdog offensively
PITCHER MISMATCHELITE COMMAND ADVANTAGEWEATHER IMPACTHOME FIELD ADVANTAGE
Edge Analysis
Moneyline
CHC 63.7%
+10.3 pts
Run Line
-1.5
+10.3 pts
Total
8.0
+15.4 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. Probabilities are calibrated using Bayesian methods and sized via the Kelly Criterion. Full methodology →