MLB Baseball

COL vs CHC Prediction

June 17, 2026

10,000 Monte Carlo simulations

COL vs CHC prediction for June 17, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects CHC 5.3 - COL 4.6. CHC is favored with a 56.2% win probability. The run line is -1.5 and the total is 10.0. Model projects 9.9 total runs.

CHC
5.3
Projected Score
VS O/U 10.0
COL
4.6
Projected Score
Win Probability
56.2%
43.8%
CHCCOL
-1.5
Run Line (CHC)
10.0
Total Line
10,000
Simulations
Calibrated accuracy at this confidence: 57.9% (2,410 games)

Projected Runs Range 10th – 90th percentile

COL
357
CHC
357
FINALCHC 8 — COL 6
Projected
CHC 5.3 — COL 4.6
Actual
CHC 8 — COL 6

Starting Pitcher Matchup

Sean Sullivan L
COL
FF59%88 mph14% whiff
FC16%83 mph0% whiff
CH14%78 mph0% whiff
Javier Assad R
CHC
SI40%93 mph7% whiff
FC16%88 mph14% whiff
FF16%93 mph13% whiff

Weather Impact

Wrigley Field
66°F4 mph wind
HR: 1.020 Total: 1.008
thin air

Bullpen Comparison

COL
5.45ERA
4.65FIP
8.19K/9
4.48BB/9
1.58WHIP
CHC
4.04ERA
5.13FIP
8.17K/9
4.04BB/9
1.34WHIP

Betting Edges

RUN_LINE AWAY +1.5
-34.2% EV
-114
TOTAL OVER 10.0
-17.7% EV
-114
ML AWAY
+14.6% EV
+172
F5 UNDER 5.5
+14.4% EV
+100
ML HOME
-13.8% EV
-204
RUN_LINE HOME -1.5
-12.4% EV
-105

First 5 Innings & NRFI

COL F5
2.2 runs
34.5% win
CHC F5
2.9 runs
50.5% win
F5 Total
5.1
NRFI
55.8%
YRFI
44.2%
Avg 1st Inn Runs
0.95

HR Spotlight

Avg HRs
2.3
Over 0.5 HR
89%
Over 1.5 HR
66%
No HR
11%
Ian Happ CHC30.0%
ISO: 0.192 | Barrel: 14.4% | vs Sean Sullivan | Park: 1.03x Platoon: 1.12x
Seiya Suzuki CHC30.0%
ISO: 0.146 | Barrel: 8.8% | vs Sean Sullivan | Park: 1.03x Platoon: 1.12x
Hunter Goodman COL26.9%
ISO: 0.297 | Barrel: 16.2% | vs Javier Assad | Park: 1.03x

Pitcher Strikeout Projections

Sean Sullivan
0.0 K projected
COL | K/9: 0.0
Javier Assad
0.0 K projected
CHC | K/9: 0.0

Injury Report

COL8 injured
Brenton Doyle CF10-DAY-IL
Jordan Beck LF10-DAY-IL
Mickey Moniak LF10-DAY-IL
Chase Dollander SP60-DAY-IL
Tanner Gordon RP15-DAY-IL
Welinton Herrera RP60-DAY-IL
+2 more
CHC8 injured
Edward Cabrera SPDAY-TO-DAY
Daniel Palencia RP15-DAY-IL
Justin Steele SP60-DAY-IL
Matthew Boyd SP15-DAY-IL
Jaxon Wiggins SPDAY-TO-DAY
Jameson Taillon SP15-DAY-IL
+2 more

AI Intelligence Analysis

LEAN +1YELLOW ZONE45.1% WR (n=106)
COL ML at +172 (away underdog, 36.8% market implied) is underpriced vs model 42.1% prob (14.6% edge). Sean Sullivan (B- grade, 16.7% K rate, excellent 0.875 command) is ace-lite arm; Javier Assad (C+ grade, 16.5% K rate, weak 0.117 stuff) is mop-up pitcher. Model sees sharp disagreement. Take COL ML at 0.75 units, cap risk due to zone warning (away ML historically weak).

Key Factors

  • Pitcher mismatch: Sean Sullivan (B- grade, 0.875 command, 16.7% K rate) is elite-command arm vs Javier Assad (C+ grade, 0.117 stuff, low-K pitcher). Sullivan's command is 7.5x higher; massive edge
  • Market heavily disrespecting: 172 underdog odds = 36.8% implied prob vs model 42.1% = 5.3% value to COL
  • First-inning edge: NRFI +6.0% (52.5% prob) suggests Sullivan's command leads to no early runs; COL could score first, setting tone
  • Weather: 66°F at Wrigley, 3.9 mph wind neutral. Moderate conditions, no scoring environment advantage
  • Park: Wrigley Field 1.03 factor (slight run boost) favors over slightly

Risk Factors

  • Away ML zone historically weak (45.1% WR, n=106, 40.5% RED combo) — model may be overestimating away value despite pitcher advantage
  • CHC home field advantage typically 3-5 pct pts; model may underestimate
  • 14.6% edge is substantial but within normal variance range (not HIGH-EDGE TRAP); zone data suggests away ML struggles broadly
Sharp MoneyWith Model172 underdog odds are heavy; market is extremely disrespecting COL. Model sees 42.1% win prob, market only 36.8% — potential sharp disagreement.
PITCHER MISMATCHML VALUEAWAY CAUTIONNRFI VALUE

Edge Analysis

Moneyline
CHC 56.2%
-12.4 pts
Run Line
-1.5
-12.4 pts
Total
10.0
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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 →

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