FINAL: PIT 1 — BUF 5. Our Monte Carlo simulation projected PIT 3.64 - BUF 4.01 (BUF at 52.1% win probability). The spread is 1.5 and the total is 6.5.
PIT
3.64
Projected Score
VS
O/U 6.5
BUF
4.01
Projected Score
Win Probability
PITBUF
+1.5
Spread (PIT)
6.5
Total Line
1,000
Simulations
Calibrated accuracy at this confidence: 48.7% (1,083 games)
Projected Goals Range 10th – 90th percentile
BUF
2.94.05.1
PIT
2.63.64.7
Projected
PIT 3.64 — BUF 4.01
Actual
PIT 1 — BUF 5
Pick Results
Under 6.5totalWIN+0.85u
Game Odds
PIT ML
-106
BUF ML
-115
Puck Line
+1.5
Total
6.5
Edge Detail
PIT Edge
-3.6%
BUF Edge
-1.4%
Projected Total
7.65
+1.15 vs line
Goalie Matchup
Alex Lyon
14-92.65 GAA91.5% SV
Stuart Skinner
26-182.74 GAA89.2% SV
Special Teams
Power Play
Penalty Kill
90% Confidence: 40.7% – 55.1% home win probability
AI Intelligence Analysis
LEANYELLOW ZONE48.8% WR (n=80)
BUF is the superior team (36-19-6 vs 31-16-13) and riding 4-1 L5 form, but as an away favorite at -120 they fall in the structurally weak away ML zone and PIT has strong home-goalie proficiency with Skinner.
Key Factors
- BUF record: 36-19-6 (.633 pt%) vs PIT 31-16-13 (.633 pt%) — essentially equal standings, no quality mismatch
- BUF L5: 4-1 (hot), L10: 7-3; PIT L5: 3-2, L10: 6-4 — BUF has moderate form edge
- Goalie matchup: BUF Alex Lyon (.896 SV%, backup tier) vs PIT Stuart Skinner (.896 SV%, backup tier) — dead even, no edge
- BUF PP%: 19.89%, PIT PK%: 84.57% — PIT has elite penalty kill advantage that neutralizes BUF PP
- Away ML favorite zone: YELLOW 48.8% WR (n=80, z=-0.22) — marginal, no structural edge
Risk Factors
- Away ML favorite zone is structurally YELLOW trending RED — 46.4% WR across full away ML sample
- Both teams have backup-tier goalies — high variance, coin-flip goaltending
- PIT has 6 players on IR (most today) but Skinner healthy — depth concern but not top-line critical
GOALIE UNCONFIRMEDAWAY DOG POISON
Edge Analysis
Moneyline
BUF 52.1%
-3.6 pts
Spread
+1.5
-3.6 pts
Total
6.5
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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 1,000 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 →