NHL Hockey

MTL vs BUF Prediction

May 18, 2026

10,000 Monte Carlo simulations

MTL vs BUF prediction for May 18, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects BUF 3.02 - MTL 2.43. BUF is favored with a 58.6% win probability. The spread is -1.5 and the total is 5.5.

BUF
3.02
Projected Score
VS O/U 5.5
MTL
2.43
Projected Score
Win Probability
58.6%
41.4%
BUFMTL
-1.5
Spread (BUF)
5.5
Total Line
10,000
Simulations
Calibrated accuracy at this confidence: 59.7% (1,083 games)

Projected Goals Range 10th – 90th percentile

MTL
1.32.43.5
BUF
1.93.04.1
FINALBUF 2 — MTL 3
Projected
BUF 3.02 — MTL 2.43
Actual
BUF 2 — MTL 3

Game Odds

BUF ML
-115
MTL ML
-104
Puck Line
-1.5
Total
5.5
Model Quality58/100 (GOOD)

Edge Detail

BUF Edge
+5.1%
MTL Edge
-9.6%
Projected Total
5.45
-0.05 vs line

Goalie Matchup

Jakub Dobes
7-42.72 GAA90.3% SV
VS
Ukko-Pekka Luukkonen
24-242.49 GAA90.9% SV

Special Teams

Power Play
MTL
23.2%
BUF
19.7%
Penalty Kill
MTL
77.4%
BUF
81.3%
90% Confidence: 58.4% – 60.0% home win probability

AI Intelligence Analysis

NEUTRALYELLOW ZONE52.0% WR (n=76)
This Game 7 playoff matchup is already resolved with MTL winning 3-2 in OT (May 18, 2026) — cannot be analyzed or wagered on. Post-hoc analysis reveals model underweighted MTL's superior L5 form advantage and power play edge in a high-variance playoff environment.

Key Factors

  • MTL 3-2 L5 form (4.4 GF, 3.4 GA) vs BUF 2-3 L5 form (3.4 GF, 4.4 GA) — Montreal had +1.0 goal differential advantage in recent sample
  • Power play edge: MTL 23.21% PP vs BUF 19.73% PP (2.48% advantage) — critical in OT playoff scenarios where special teams dominate
  • Goalie matchup: Dobes (.902 SV%) vs Luukkonen (.906 SV%) — marginal advantage to BUF starter, not enough to overcome form disadvantage
  • Home ice advantage (BUF): ~0.25 goals estimated value, partially negated by MTL's superior L5 form and fresher defensive structure
  • Zone: Home favorite ML with 5.1% edge lands in YELLOW zone (52.0% WR, n=76) — marginal expectancy that market correctly identified as near-coin-flip

Risk Factors

  • Playoff hockey eliminates xGF predictability: single-goal games are variance-driven, and a one-goal swing (Game 7 OT winner) is not modeled effectively by Pinnacle engine
  • Postseason goalie performance is streaky and hard to quantify; Dobes had hot-goalie performance that xGF/SV% metrics don't fully capture
  • Market efficiently priced this as toss-up despite BUF home advantage; model's 5.1% edge was in the weakest zone (YELLOW) where high-edge claims often fail
GAME RESOLVEDPLAYOFF GAMEOUTCOME KNOWNMTL WINNER 3-2 OTMODEL PREDICTION WRONGHIGH VARIANCE ENVIRONMENT

Edge Analysis

Moneyline
BUF 58.6%
+5.1 pts
Spread
-1.5
+5.1 pts
Total
5.5
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How this prediction was generated: This page shows output from the Olympus Bets NHL Hockey 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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