MLB Baseball

PHI vs PIT Prediction

May 15, 2026

10,000 Monte Carlo simulations

PHI vs PIT prediction for May 15, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects PIT 3.8 - PHI 3.4. PIT is favored with a 56.3% win probability. The run line is -1.5 and the total is 8.0. Model projects 7.1 total runs.

PIT
3.8
Projected Score
VS O/U 8.0
PHI
3.4
Projected Score
Win Probability
56.3%
43.7%
PITPHI
-1.5
Run Line (PIT)
8.0
Total Line
10,000
Simulations
Calibrated accuracy at this confidence: 52.4% (2,085 games)

Projected Runs Range 10th – 90th percentile

PHI
135
PIT
246
FINALPIT 9 — PHI 11
Projected
PIT 3.8 — PHI 3.4
Actual
PIT 9 — PHI 11

Starting Pitcher Matchup

Aaron Nola R
PHI
KC32%78 mph39% whiff
FF27%92 mph14% whiff
SI18%91 mph10% whiff
Braxton Ashcraft R
PIT
FF32%97 mph14% whiff
CU27%85 mph42% whiff
SL20%92 mph40% whiff

Weather Impact

PNC Park
70°F5 mph wind
HR: 1.004 Total: 1.000
neutral

Bullpen Comparison

PHI
4.25ERA
3.22FIP
10.21K/9
3.35BB/9
1.37WHIP
PIT
4.29ERA
4.17FIP
8.75K/9
4.31BB/9
1.37WHIP

Betting Edges

RUN_LINE AWAY +1.5
-42.5% EV
-182
TOTAL OVER 8.0
-30.9% EV
-115
F5_ML AWAY
-14.4% EV
+116
F5 UNDER 4.5
+14.1% EV
-114
TOTAL UNDER 8.0
+11.1% EV
-105
RUN_LINE HOME -1.5
-6.5% EV
+150

First 5 Innings & NRFI

PHI F5
1.6 runs
30.9% win
PIT F5
2.3 runs
49.8% win
F5 Total
3.9
NRFI
60.1%
YRFI
39.9%
Avg 1st Inn Runs
0.77

HR Spotlight

Avg HRs
2.0
Over 0.5 HR
86%
Over 1.5 HR
59%
No HR
14%
Kyle Schwarber PHI30.0%
ISO: 0.424 | Barrel: 20.0% | vs Braxton Ashcraft | Park: 0.95x Platoon: 1.12x
Brandon Lowe PIT30.0%
ISO: 0.333 | Barrel: 16.1% | vs Aaron Nola | Park: 0.95x Platoon: 1.12x
Oneil Cruz PIT30.0%
ISO: 0.201 | Barrel: 12.7% | vs Aaron Nola | Park: 0.95x Platoon: 1.12x

Pitcher Strikeout Projections

Aaron Nola
0.0 K projected
PHI | K/9: 0.0
Braxton Ashcraft
0.0 K projected
PIT | K/9: 0.0

Injury Report

PHI8 injured
Kyle Backhus RP15-DAY-IL
Trea Turner SSDAY-TO-DAY
Zach Pop RP15-DAY-IL
Keaton Anthony 1BDAY-TO-DAY
Johan Rojas CFSUSPENSION
Rene Pinto CDAY-TO-DAY
+2 more
PIT8 injured
Jared Jones SP60-DAY-IL
Joey Bart C10-DAY-IL
Jake Mangum LF10-DAY-IL
Anthony Solometo SPDAY-TO-DAY
Chris Devenski RP15-DAY-IL
Oddanier Mosqueda RPDAY-TO-DAY
+2 more

AI Intelligence Analysis

LEANYELLOW ZONE50.4% WR (n=258)
Pitcher mismatch favors PIT (Ashcraft 2.99 ERA vs Nola 5.55 ERA) — 2.56 ERA gap is significant — but market is only slightly mispricing at -1.8% ML edge on home. UNDER 8.0 has 11.1% edge in YELLOW zone (50.4% WR), so expecting regression. F5 UNDER 4.5 at 14.1% edge is the cleaner play here; NRFI at 5.6% edge offers modest value.

Key Factors

  • SP mismatch: Ashcraft 2.99 ERA, 26.7% K (B-grade) vs Nola 5.55 ERA, 23.5% K (C+ grade) — 2.56 ERA gap is meaningful pitcher advantage PIT
  • UNDER 8.0 has 11.1% edge (57% model vs 50% implied) — totals market underperforming but YELLOW zone 50.4% WR means no edge exists long-term
  • Weather neutral: 70°F, 4.7mph wind, park factor 1.0 — no weather tail
  • Park-neutral game: PNC Park 1.0x factor — no ballpark advantage either side
  • F5 UNDER 4.5 (14.1% edge, 60.7% model) is cleaner play than full game; NRFI (5.6% edge, 58% model) offers modest first-inning value

Risk Factors

  • Total market in F-grade calibration: Spreads/totals completely disabled. 50.4% historical WR on YELLOW totals means we're betting a coin flip market.
  • High edge (11.1%) on total is RED FLAG in calibration: Historical pattern shows 11-15% edge on totals = worse performance than 5-10% edge. Edge paradox: bigger disagreement with market = worse outcomes.
  • Nola recent struggles not in Bayesian ERA yet — if he's deteriorating faster than stats show, under could hit but model doesn't capture late-season collapse risk.
PITCHER MISMATCHYELLOW ZONEHIGH EDGE WARNING

Edge Analysis

Moneyline
PIT 56.3%
-6.5 pts
Run Line
-1.5
-6.5 pts
Total
8.0
+11.1 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. Full methodology →

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