OAK vs CWS prediction for July 10, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects CWS 5.0 - OAK 3.4. CWS is favored with a 60.1% win probability. The run line is -1.5 and the total is 9.0. Model projects 8.3 total runs.
CWS
5.0
Projected Score
VS
O/U 9.0
OAK
3.4
Projected Score
Win Probability
CWSOAK
-1.5
Run Line (CWS)
9.0
Total Line
10,000
Simulations
Calibrated accuracy at this confidence: 59.4% (2,790 games)
Projected Runs Range 10th – 90th percentile
OAK
135
CWS
357
Projected
CWS 5.0 — OAK 3.4
Actual
CWS 14 — OAK 1
Starting Pitcher Matchup
Jacob Lopez L
OAK
FF34%90 mph14% whiff
SL30%77 mph21% whiff
FC20%86 mph23% whiff
Sean Burke R
CWS
FF38%95 mph22% whiff
KC21%80 mph23% whiff
SL17%87 mph32% whiff
Weather Impact
Guaranteed Rate Field
74°F7 mph wind
HR: 1.053 Total: 1.028
thin air
Bullpen Comparison
OAK
4.87ERA
3.91FIP
9.81K/9
4.20BB/9
1.44WHIP
CWS
4.29ERA
4.67FIP
8.64K/9
4.97BB/9
1.34WHIP
Betting Edges
RUN_LINE AWAY +1.5
-48.6% EV
-147
RUN_LINE HOME -1.5
+18.9% EV
+122
TOTAL OVER 9.0
-15.2% EV
-102
F5_ML AWAY
-13.6% EV
+146
NRFI NRFI
+6.7% EV
+100
ML HOME
-5.0% EV
-179
First 5 Innings & NRFI
OAK F5
1.7 runs
29.1% win
CWS F5
2.9 runs
55.9% win
F5 Total
4.6
NRFI
57.4%
YRFI
42.6%
Avg 1st Inn Runs
0.90
HR Spotlight
Avg HRs
2.2
Over 0.5 HR
88%
Over 1.5 HR
62%
No HR
12%
Miguel Vargas CWS30.0%
ISO: 0.352 | Barrel: 9.3% | vs Jacob Lopez | Park: 1.01x Platoon: 1.12x
Colson Montgomery CWS30.0%
ISO: 0.285 | Barrel: 14.4% | vs Jacob Lopez | Park: 1.01x
Munetaka Murakami CWS18.1%
ISO: 0.078 | Barrel: 7.8% | vs Jacob Lopez | Park: 1.01x
Pitcher Strikeout Projections
Jacob Lopez
0.0 K projected
OAK | K/9: 0.0
Sean Burke
0.0 K projected
CWS | K/9: 0.0
Injury Report
OAK6 injured
Zack Gelof 3B10-DAY-IL
Brent Rooker DH10-DAY-IL
Denzel Clarke CF60-DAY-IL
Luis Severino SP60-DAY-IL
Brooks Kriske RP60-DAY-IL
Gunnar Hoglund SP60-DAY-IL
CWSHealthy
Edge Analysis
Moneyline
CWS 60.1%
+18.9 pts
Run Line
-1.5
+18.9 pts
Total
9.0
+4.6 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 →