MLB Baseball

COL vs CHC Prediction

June 16, 2026

10,000 Monte Carlo simulations

COL vs CHC prediction for June 16, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects CHC 6.2 - COL 5.8. CHC is favored with a 54.1% win probability. The run line is -1.5 and the total is 9.5. Model projects 11.9 total runs.

CHC
6.2
Projected Score
VS O/U 9.5
COL
5.8
Projected Score
Win Probability
54.1%
45.9%
CHCCOL
-1.5
Run Line (CHC)
9.5
Total Line
10,000
Simulations
Calibrated accuracy at this confidence: 57.3% (2,386 games)

Projected Runs Range 10th – 90th percentile

COL
468
CHC
468
FINALCHC 2 — COL 5
Projected
CHC 6.2 — COL 5.8
Actual
CHC 2 — COL 5

Starting Pitcher Matchup

Ryan Feltner R
COL
FF26%95 mph8% whiff
SL25%89 mph22% whiff
CH16%86 mph48% whiff
Edward Cabrera R
CHC
CH32%93 mph28% whiff
SI20%96 mph4% whiff
CU18%85 mph32% whiff

Weather Impact

Wrigley Field
69°F14 mph wind
HR: 0.967 Total: 0.978
thin air, 13mph in

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
-28.3% EV
-122
TOTAL UNDER 9.5
-24.1% EV
-104
F5 OVER 5.5
+19.6% EV
-108
ML AWAY
+16.8% EV
+166
ML HOME
-15.3% EV
-196
F5_ML HOME
-14.1% EV
-182

First 5 Innings & NRFI

COL F5
3.4 runs
41.7% win
CHC F5
3.7 runs
47.5% win
F5 Total
7.1
NRFI
41.6%
YRFI
58.4%
Avg 1st Inn Runs
1.48

HR Spotlight

Avg HRs
3.6
Over 0.5 HR
97%
Over 1.5 HR
87%
No HR
3%
Hunter Goodman COL30.0%
ISO: 0.297 | Barrel: 16.2% | vs Edward Cabrera | Park: 1.03x
Ian Happ CHC30.0%
ISO: 0.275 | Barrel: 14.4% | vs Ryan Feltner | Park: 1.03x Platoon: 1.12x
Pete Crow-Armstrong CHC30.0%
ISO: 0.251 | Barrel: 10.8% | vs Ryan Feltner | Park: 1.03x Platoon: 1.12x

Pitcher Strikeout Projections

Ryan Feltner
0.0 K projected
COL | K/9: 0.0
Edward Cabrera
0.0 K projected
CHC | K/9: 0.0

Injury Report

COL8 injured
Chase Dollander SP60-DAY-IL
Brenton Doyle CF10-DAY-IL
Jordan Beck LF10-DAY-IL
Mickey Moniak LF10-DAY-IL
Jimmy Herget RP15-DAY-IL
Tanner Gordon RP15-DAY-IL
+2 more
CHC8 injured
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
Hunter Harvey RP60-DAY-IL
+2 more

AI Intelligence Analysis

STRONG BET +1YELLOW ZONE50.1% WR (n=198)
OVER 9.5 has +13.3% edge (61.3% model vs 48.0% market) — strongest total edge on slate. Model projects 11.94 runs (2.44 swing favoring over). Both pitchers are poor (Edward Cabrera 5.25 ERA, Ryan Feltner 5.62 ERA). Park factor 1.03 (Wrigley +3%), weather cool (68.6F) with 13.9 mph wind blowing IN (-12.8 tail) is SUPPRESSIVE but insufficient to overcome pitcher weakness. F5 shows massive +19.6% edge (62.0% prob OVER 5.5) — early-inning explosion likely.

Key Factors

  • BOTH pitchers are poor: Cabrera 5.25 ERA (0.406 grade, 0.36 stuff) and Feltner 5.62 ERA (0.434 grade, 0.26 stuff) — combined they're replacement-level
  • F5 advantage HUGE: +19.6% edge (62.0% prob OVER 5.5 in first 5 innings) — market is severely underestimating early run explosion
  • Park factor 1.03 (Wrigley) adds marginal inflation to run expectation; helps overs
  • Weather: 68.6F cold, 13.9 mph wind in (-12.8 tail-wind) SUPPRESSES but only by ~0.5-1.0 runs. Model baseline 11.94 accounts for this
  • CHC lineup projects 6.16 runs (home), COL 5.78 (away) — high totals expected

Risk Factors

  • HIGH-EDGE TRAP: +13.3% edge is in RED zone historically (high edges correlate to WORST WR). Calibration data shows edges >10% in totals have poor track record. CAP UNIT at 0.75-1.0, not 1.5
  • YELLOW zone totals only 50.1% WR (n=198) — no edge. Historical data doesn't support big total edges
  • Wind blowing in (-12.8 tail) is real suppression; could reduce runs 0.5-1.0 from model baseline
PITCHER MISMATCHTOTALS VALUEHIGH EDGE WARNINGF5 EDGEPARK FACTORWEATHER IMPACT

Edge Analysis

Moneyline
CHC 54.1%
-13.5 pts
Run Line
-1.5
-13.5 pts
Total
9.5
+13.3 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 →

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