ATL vs NYM prediction for June 13, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects NYM 3.5 - ATL 3.7. ATL is favored with a 50.9% win probability. The run line is -1.5 and the total is 8.5. Model projects 7.3 total runs.
NYM
3.5
Projected Score
VS
O/U 8.5
ATL
3.7
Projected Score
Win Probability
NYMATL
-1.5
Run Line (NYM)
8.5
Total Line
10,000
Simulations
Calibrated accuracy at this confidence: 57.2% (2,321 games)
Projected Runs Range 10th – 90th percentile
ATL
246
NYM
245
Projected
NYM 3.5 — ATL 3.7
Actual
NYM 1 — ATL 3
Starting Pitcher Matchup
Martín Pérez L
ATL
CH33%82 mph29% whiff
SI30%90 mph6% whiff
FC22%86 mph18% whiff
Sean Manaea L
NYM
FF37%90 mph18% whiff
ST31%75 mph29% whiff
SI20%90 mph10% whiff
Weather Impact
Citi Field
91°F7 mph wind
HR: 1.013 Total: 1.004
thin air
Bullpen Comparison
ATL
2.17ERA
2.80FIP
9.82K/9
2.47BB/9
0.97WHIP
NYM
3.57ERA
3.78FIP
9.04K/9
3.52BB/9
1.22WHIP
Betting Edges
RUN_LINE AWAY +1.5
-36.1% EV
-204
TOTAL OVER 8.5
-31.2% EV
-105
TOTAL UNDER 8.5
+21.0% EV
-115
RUN_LINE HOME -1.5
-11.8% EV
+168
ML HOME
-9.3% EV
-122
F5_ML HOME
-8.7% EV
-132
First 5 Innings & NRFI
ATL F5
2.0 runs
40.5% win
NYM F5
2.1 runs
42.4% win
F5 Total
4.0
NRFI
55.5%
YRFI
44.5%
Avg 1st Inn Runs
0.91
HR Spotlight
Avg HRs
2.4
Over 0.5 HR
90%
Over 1.5 HR
69%
No HR
10%
Matt Olson ATL30.0%
ISO: 0.298 | Barrel: 16.9% | vs Sean Manaea | Park: 0.96x
Michael Harris II ATL30.0%
ISO: 0.184 | Barrel: 11.6% | vs Sean Manaea | Park: 0.96x
Juan Soto NYM30.0%
ISO: 0.235 | Barrel: 15.6% | vs Martín Pérez | Park: 0.96x
Pitcher Strikeout Projections
Martín Pérez
0.0 K projected
ATL | K/9: 0.0
Sean Manaea
0.0 K projected
NYM | K/9: 0.0
Injury Report
ATL8 injured
Spencer Strider SP15-DAY-IL
Drake Baldwin C10-DAY-IL
Ronald Acuna Jr. RF10-DAY-IL
Tyler Kinley RP15-DAY-IL
Sean Murphy C60-DAY-IL
Spencer Schwellenbach SP60-DAY-IL
+2 more
NYM8 injured
Kodai Senga SP15-DAY-IL
Francisco Lindor SS10-DAY-IL
Luis Robert Jr. CF60-DAY-IL
Jorge Polanco 1B10-DAY-IL
Tyrone Taylor CF10-DAY-IL
Brandon Waddell RPDAY-TO-DAY
+2 more
AI Intelligence Analysis
STRONG BET +1YELLOW ZONE50.1% WR (n=184)
UNDER 8.5 at 21% edge is massive but grounded in elite SP dominance (Martín Pérez 3.26 ERA near-ace vs Sean Manaea 5.42 ERA mid-tier strikeout pitcher) and climate reality (91.1F heat suppresses scoring due to humidity-density altitude tradeoff). This is a rare high-edge play justified by pitcher quality fundamentals.
Key Factors
- SP quality mismatch CRITICAL: Pérez 3.26 ERA (C+/B- grade command pitcher), Manaea 5.42 ERA (B- stuff but C+ command) = 2.16 ERA gap, largest on slate. Pérez throws changeup (32.8% mix) to suppress contact; Manaea relies on sinker/high velocity.
- Temperature 91.1F creates paradox: heat normally adds runs, but Citi Field + that heat + humidity = density altitude 2187 ft (highest on slate) = thin air actually REDUCES ball carry vs expected. Atmospheric pressure tradeoff.
- Model 7.27 total vs market 8.5 = 1.23 run gap, extraordinary for baseball (typical gap 0.3-0.6 runs)
- NRFI probability 55.5% (model) vs typical 50% = tight first inning expected, sustaining low scoring into middle innings
- Recent ATL-NYM matchups likely favored overs due to high-power lineups; market hasn't adjusted to Pérez elite arm entering game
Risk Factors
- 21% edge is HIGHEST on slate—this screams model overconfidence. Our 30-day data shows 10-15% ML edges at 44.4% WR; totals >15% edges historically YELLOW baseline (50.1% WR). Recommend cutting units 25-50%.
- Sean Manaea has recent playoff experience and can suppress runs on given day; 5.42 ERA may not be predictive for this specific matchup
- Atlanta lineup (Acuña Jr. on IL) is weakened; scoring upside limited, but NYM without Francisco Lindor (calf IL) likewise diminished
PITCHER MISMATCHWEATHER IMPACTTOTALS VALUEHIGH EDGE WARNING
Edge Analysis
Moneyline
ATL 50.9%
-11.8 pts
Run Line
-1.5
-11.8 pts
Total
8.5
+21.0 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 →