FINAL: BAL 2 — CWS 8. Our Monte Carlo simulation projected BAL 6.5 - CWS 4.8 (BAL at 65.0% win probability). The run line is -1.5 and the total is 9.5. Model projects 11.3 total runs.
BAL
6.5
Projected Score
VS
O/U 9.5
CWS
4.8
Projected Score
Win Probability
BALCWS
-1.5
Run Line (BAL)
9.5
Total Line
10,000
Simulations
CWS W5BAL L5
Calibrated accuracy at this confidence: 62.8% (2,559 games)
Projected Runs Range 10th – 90th percentile
CWS
357
BAL
568
Projected
BAL 6.5 — CWS 4.8
Actual
BAL 2 — CWS 8
Pick Results
BAL MLmlLOSS-0.50u
Starting Pitcher Matchup
Sean Burke R
CWS
FF37%94 mph21% whiff
KC21%80 mph23% whiff
SL18%87 mph32% whiff
Shane Baz R
BAL
FF34%96 mph13% whiff
KC33%85 mph28% whiff
FC18%90 mph20% whiff
Weather Impact
Oriole Park at Camden Yards
90°F5 mph wind
HR: 1.048 Total: 1.025
thin air
Bullpen Comparison
CWS
4.29ERA
4.67FIP
8.64K/9
4.97BB/9
1.34WHIP
BAL
4.34ERA
4.01FIP
8.76K/9
3.44BB/9
1.30WHIP
Betting Edges
RUN_LINE AWAY +1.5
-47.4% EV
-185
TOTAL UNDER 9.5
-20.0% EV
-120
ML AWAY
-19.3% EV
+116
RUN_LINE HOME -1.5
+18.7% EV
+150
F5_ML AWAY
-16.7% EV
+104
TOTAL OVER 9.5
+11.4% EV
-102
First 5 Innings & NRFI
CWS F5
2.7 runs
34.2% win
BAL F5
3.7 runs
53.4% win
F5 Total
6.4
NRFI
49.2%
YRFI
50.8%
Avg 1st Inn Runs
1.18
HR Spotlight
Avg HRs
2.9
Over 0.5 HR
94%
Over 1.5 HR
78%
No HR
6%
Colson Montgomery CWS30.0%
ISO: 0.249 | Barrel: 14.9% | vs Shane Baz | Park: 1.03x Platoon: 1.12x
Miguel Vargas CWS27.5%
ISO: 0.200 | Barrel: 14.0% | vs Shane Baz | Park: 1.03x
Pete Alonso BAL26.2%
ISO: 0.250 | Barrel: 12.7% | vs Sean Burke | Park: 1.03x
Pitcher Strikeout Projections
Sean Burke
0.0 K projected
CWS | K/9: 0.0
Shane Baz
0.0 K projected
BAL | K/9: 0.0
Injury Report
CWSHealthy
BAL8 injured
Chris Bassitt SP15-DAY-IL
Dean Kremer SP60-DAY-IL
Felix Bautista RP60-DAY-IL
Yaramil Hiraldo RP60-DAY-IL
Ryan Mountcastle 1B60-DAY-IL
Jhonkensy Noel RFDAY-TO-DAY
+2 more
Edge Analysis
Moneyline
BAL 65.0%
+18.7 pts
Run Line
-1.5
+18.7 pts
Total
9.5
+11.4 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 →