KC vs CWS prediction for June 29, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects CWS 3.6 - KC 4.2. KC is favored with a 53.9% win probability. The run line is -1.5 and the total is 8.5. Model projects 7.7 total runs.
CWS
3.6
Projected Score
VS
O/U 8.5
KC
4.2
Projected Score
Win Probability
CWSKC
-1.5
Run Line (CWS)
8.5
Total Line
10,000
Simulations
Calibrated accuracy at this confidence: 54.7% (2,485 games)
Projected Runs Range 10th – 90th percentile
KC
246
CWS
246
Starting Pitcher Matchup
Michael Wacha R
KC
FF28%93 mph18% whiff
CH22%81 mph27% whiff
FC15%89 mph13% whiff
Davis Martin R
CWS
FF26%94 mph23% whiff
SI17%93 mph9% whiff
CH15%90 mph15% whiff
Weather Impact
Guaranteed Rate Field
76°F10 mph wind
HR: 1.082 Total: 1.045
thin air, 9mph out
Bullpen Comparison
KC
4.34ERA
5.00FIP
8.61K/9
4.51BB/9
1.45WHIP
CWS
4.29ERA
4.67FIP
8.64K/9
4.97BB/9
1.34WHIP
Betting Edges
RUN_LINE AWAY +1.5
-28.2% EV
-182
TOTAL OVER 8.5
-19.8% EV
-122
RUN_LINE HOME -1.5
-19.7% EV
+150
ML HOME
-16.5% EV
-135
F5_ML HOME
-16.0% EV
-139
ML AWAY
+12.4% EV
+116
First 5 Innings & NRFI
KC F5
2.1 runs
44.4% win
CWS F5
1.9 runs
38.9% win
F5 Total
3.9
NRFI
58.7%
YRFI
41.3%
Avg 1st Inn Runs
0.84
HR Spotlight
Avg HRs
2.1
Over 0.5 HR
87%
Over 1.5 HR
60%
No HR
13%
Colson Montgomery CWS29.9%
ISO: 0.249 | Barrel: 14.9% | vs Michael Wacha | Park: 1.01x Platoon: 1.12x
Miguel Vargas CWS23.2%
ISO: 0.200 | Barrel: 14.0% | vs Michael Wacha | Park: 1.01x
Braden Montgomery CWS20.5%
ISO: 0.151 | Barrel: 15.1% | vs Michael Wacha | Park: 1.01x Platoon: 1.12x
Pitcher Strikeout Projections
Michael Wacha
0.0 K projected
KC | K/9: 0.0
Davis Martin
0.0 K projected
CWS | K/9: 0.0
Injury Report
KC8 injured
Cole Ragans SP60-DAY-IL
Kris Bubic SP15-DAY-IL
Stephen Kolek SPDAY-TO-DAY
Carlos Estevez RP60-DAY-IL
Nick Mears RP15-DAY-IL
Maikel Garcia 3B10-DAY-IL
+2 more
CWSHealthy
Edge Analysis
Moneyline
KC 53.9%
-19.7 pts
Run Line
-1.5
-19.7 pts
Total
8.5
+11.9 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. Probabilities are calibrated using Bayesian methods and sized via the Kelly Criterion. Full methodology →