MLB Baseball

MIA vs PHI Prediction

June 17, 2026

10,000 Monte Carlo simulations

MIA vs PHI prediction for June 17, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects PHI 4.2 - MIA 5.2. MIA is favored with a 53.7% win probability. The run line is 1.5 and the total is 9.5. Model projects 9.4 total runs.

PHI
4.2
Projected Score
VS O/U 9.5
MIA
5.2
Projected Score
Win Probability
46.3%
53.7%
PHIMIA
+1.5
Run Line (PHI)
9.5
Total Line
10,000
Simulations
Calibrated accuracy at this confidence: 55.8% (2,410 games)

Projected Runs Range 10th – 90th percentile

MIA
357
PHI
246
FINALPHI 4 — MIA 12
Projected
PHI 4.2 — MIA 5.2
Actual
PHI 4 — MIA 12

Starting Pitcher Matchup

Sandy Alcantara R
MIA
SI24%97 mph8% whiff
CH22%91 mph28% whiff
FF20%97 mph16% whiff
Andrew Painter R
PHI
FF34%96 mph8% whiff
SL21%88 mph37% whiff
FS14%87 mph33% whiff

Weather Impact

Citizens Bank Park
83°F10 mph wind
HR: 0.995 Total: 0.994
thin air, 7mph in

Bullpen Comparison

MIA
3.85ERA
3.56FIP
9.97K/9
4.48BB/9
1.21WHIP
PHI
4.19ERA
3.22FIP
10.30K/9
3.17BB/9
1.34WHIP

Betting Edges

RUN_LINE HOME +1.5
-43.3% EV
-192
F5_ML HOME
-15.6% EV
-108
ML HOME
-13.1% EV
-120
TOTAL OVER 9.5
-10.8% EV
+100
NRFI NRFI
+8.7% EV
+114
RUN_LINE AWAY -1.5
+8.3% EV
+160

First 5 Innings & NRFI

MIA F5
2.9 runs
49.1% win
PHI F5
2.2 runs
35.5% win
F5 Total
5.1
NRFI
54.7%
YRFI
45.3%
Avg 1st Inn Runs
0.94

HR Spotlight

Avg HRs
2.4
Over 0.5 HR
90%
Over 1.5 HR
69%
No HR
10%
Liam Hicks MIA30.0%
ISO: 0.230 | Barrel: 11.7% | vs Andrew Painter | Park: 1.02x Platoon: 1.12x
Esteury Ruiz MIA30.0%
ISO: 0.172 | Barrel: 15.6% | vs Andrew Painter | Park: 1.02x
Kyle Stowers MIA30.0%
ISO: 0.171 | Barrel: 7.5% | vs Andrew Painter | Park: 1.02x Platoon: 1.12x

Pitcher Strikeout Projections

Sandy Alcantara
0.0 K projected
MIA | K/9: 0.0
Andrew Painter
0.0 K projected
PHI | K/9: 0.0

Injury Report

MIA8 injured
Griffin Conine LF60-DAY-IL
Eury Perez SP15-DAY-IL
Thomas White SPDAY-TO-DAY
Josh Ekness RP15-DAY-IL
Andrew Nardi RP60-DAY-IL
Janson Junk SP15-DAY-IL
+2 more
PHI8 injured
Brad Keller RP15-DAY-IL
Adolis Garcia RF60-DAY-IL
Johan Rojas CFOUT
Kyle Backhus RP15-DAY-IL
Andrew Walling RPDAY-TO-DAY
Carson DeMartini SSDAY-TO-DAY
+2 more

AI Intelligence Analysis

STRONG BET +1YELLOW ZONE51.3% WR (n=6)
MIA ML away at +102 (49.5% implied) is underpriced vs model 52.5% win prob (6.1% edge). Alcantara (4.59 ERA, B- stuff, elite command 0.774) is a significant upgrade over Painter (6.94 ERA, C+ stuff, weaker command 0.595). Model also sees NRFI edge (8.7%, 50.8% prob). Take MIA ML + lean NRFI.

Key Factors

  • Pitcher mismatch significant: Alcantara (4.59 ERA, B- grade, 17.7% K rate, elite 0.774 command) vs Painter (6.94 ERA, C+ grade, 17.5% K rate, weak 0.595 command). Same K-rate tiers but command differential is 18% — massive edge
  • Alcantara Bayesian ERA 4.59 vs Painter 6.94 = 2.35 ERA gap = ~2.5 run swing over 7 innings for starting pitcher advantage
  • Market-implied 49.5% (PHI -120) vs model 52.5% MIA = 3% value to away side
  • NRFI edge 8.7% (50.8% prob) adds high-quality secondary play; Alcantara excels at slow-start games
  • Weather: 82.9°F, 7.3 mph wind in at Citizens Bank; modest suppression (0.994 total multiplier) favors under

Risk Factors

  • Away ML combo zone (40.5% WR, n=62) is RED-tagged; historical underperformance in this zone — mitigated by edge quality but noted
  • PHI on heels of 12-4 loss yesterday (public perception of bounce-back); may see heavy money vs away team
  • Sample size on away ML 5-10% edge zone small (n=6), win rate 51.3% — limited precedent
Sharp MoneyWith ModelModest public lean to home team (PHI -120 at 54.5% implied); sharp action may support away value. Model sees 6.1% edge on MIA ML.
BETPITCHER MISMATCHNRFI VALUEML VALUE

Edge Analysis

Moneyline
MIA 53.7%
-43.3 pts
Run Line
+1.5
-43.3 pts
Total
9.5
+0.8 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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