PHI vs MIL prediction for June 13, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects MIL 6.4 - PHI 5.2. MIL is favored with a 59.2% win probability. The run line is -1.5 and the total is 8.5. Model projects 11.7 total runs.
MIL
6.4
Projected Score
VS
O/U 8.5
PHI
5.2
Projected Score
Win Probability
MILPHI
-1.5
Run Line (MIL)
8.5
Total Line
10,000
Simulations
Calibrated accuracy at this confidence: 63.2% (2,321 games)
Projected Runs Range 10th – 90th percentile
PHI
357
MIL
468
Projected
MIL 6.4 — PHI 5.2
Actual
MIL 8 — PHI 9
Starting Pitcher Matchup
Aaron Nola R
PHI
KC34%78 mph37% whiff
FF25%92 mph14% whiff
SI19%91 mph10% whiff
Shane Drohan L
MIL
FF28%95 mph28% whiff
SI20%95 mph10% whiff
SL18%86 mph33% whiff
Weather Impact
American Family Field
83°F13 mph windRoof: retractable
HR: 0.979 Total: 0.985
thin air, 13mph in
Bullpen Comparison
PHI
4.18ERA
3.23FIP
10.40K/9
3.24BB/9
1.34WHIP
MIL
3.72ERA
3.58FIP
9.23K/9
3.92BB/9
1.32WHIP
Betting Edges
RUN_LINE AWAY +1.5
-41.2% EV
-154
TOTAL UNDER 8.5
-29.0% EV
-112
F5 OVER 4.5
+20.7% EV
-120
TOTAL OVER 8.5
+20.5% EV
-108
F5_ML AWAY
-10.3% EV
+120
RUN_LINE HOME -1.5
+5.4% EV
+128
First 5 Innings & NRFI
PHI F5
2.9 runs
35.7% win
MIL F5
3.8 runs
53.3% win
F5 Total
6.8
NRFI
44.7%
YRFI
55.3%
Avg 1st Inn Runs
1.37
HR Spotlight
Avg HRs
3.3
Over 0.5 HR
96%
Over 1.5 HR
83%
No HR
4%
Kyle Schwarber PHI30.0%
ISO: 0.337 | Barrel: 19.1% | vs Shane Drohan
Jake Bauers MIL30.0%
ISO: 0.272 | Barrel: 14.3% | vs Aaron Nola | Platoon: 1.12x
Bryce Harper PHI26.7%
ISO: 0.146 | Barrel: 14.1% | vs Shane Drohan
Pitcher Strikeout Projections
Aaron Nola
0.0 K projected
PHI | K/9: 0.0
Shane Drohan
0.0 K projected
MIL | K/9: 0.0
Injury Report
PHI8 injured
Steward Berroa RFPATERNITY
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
MIL8 injured
Coleman Crow SP15-DAY-IL
Quinn Priester SP60-DAY-IL
Jared Koenig RP15-DAY-IL
Brandon Woodruff SP15-DAY-IL
Brian Fitzpatrick RP60-DAY-IL
DL Hall RP15-DAY-IL
+2 more
AI Intelligence Analysis
STRONG BET +1YELLOW ZONE50.1% WR (n=184)
OVER 8.5 at 20.5% edge is massive but grounded in elite pitcher mismatch (Shane Drohan 3.36 ERA B-grade vs Aaron Nola 6.33 ERA basement-tier F grade). Run-heavy environment (model total 11.65) is supported by hot weather (83F), retractable roof (neutral), and Nola's historically poor performance. Deploy cautiously (1.0 unit) despite HIGH_EDGE due to pitcher-driven fundamentals.
Key Factors
- SP QUALITY DRAMATICALLY FAVORS HOME: Shane Drohan (MIL home) 3.36 ERA (B-grade, 24% K-rate) vs Aaron Nola (PHI away) 6.33 ERA (worst on slate, 23.4% K-rate but high BB rate). 2.97 ERA gap is MASSIVE—second-largest gap only to ATL-NYM (Pérez 3.26 vs Manaea 5.42).
- Aaron Nola 6.33 ERA is historically terrible; this is not small-sample variance but sustained poor performance
- Model 11.65 total vs market 8.5 = 3.15 RUN GAP (extraordinary for baseball; normal is 0.3-0.6). This gap MUST be driven by pitcher quality (Nola weakness) not weather or ballpark.
- Temperature 83F, 12.7 mph wind blowing in = actually REDUCES over expectations by ~0.3 runs, but pitcher gap more than compensates
- Retractable roof at American Family Field (closed) = neutral baseline
Risk Factors
- 20.5% edge is second-highest on slate (after ATL-NYM 21%); historically YELLOW zone totals only 50.1% WR baseline. This is a condition that should reduce confidence by 25-50%.
- Nola 6.33 ERA could be tail-end of recent decline; if he pitches to recent form (4.5-5.0), edge compresses significantly
- MIL lineup has injuries (Brandon Lockridge LF on IL, various RP issues); run production capped vs expectations
PITCHER MISMATCHHIGH EDGE WARNINGWEATHER IMPACTTOTALS VALUE
Edge Analysis
Moneyline
MIL 59.2%
+5.4 pts
Run Line
-1.5
+5.4 pts
Total
8.5
+20.5 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 →