FINAL: WSH 5 — PIT 3. Our Monte Carlo simulation projected WSH 3.09 - PIT 3.49 (PIT at 53.3% win probability).
WSH
3.09
Projected Score
VS
PIT
3.49
Projected Score
Win Probability
WSHPIT
N/A
Spread
N/A
Total Line
10,000
Simulations
PIT L4WSH W5
Calibrated accuracy at this confidence: 47.8% (1,241 games)
Projected Goals Range 10th – 90th percentile
PIT
2.43.54.6
WSH
2.03.14.2
Projected
WSH 3.09 — PIT 3.49
Actual
WSH 5 — PIT 3
Pick Results
PIT MLmlLOSS-0.50u
PIT MLmlLOSS-0.50u
Goalie Matchup
Arturs Silovs
19-122.47 GAA88.6% SV
Charlie Lindgren
9-82.08 GAA93.1% SV
Special Teams
Power Play
Penalty Kill
90% Confidence: 42.7% – 44.3% home win probability
AI Intelligence Analysis
LEAN +1
Market prices WSH at 61.9% implied (vs model's 51.1%) and the gap is justified, not a trap — Logan Thompson's elite.939 SV% start, a rest advantage (WSH 4 days fresh vs PIT on a 3-in-4), and home ice all point toward the model underweighting WSH, making WSH ML the lean play tonight.
Key Factors
- Goalie gap: Thompson.939 SV% (elite) vs Silovs.886 SV% (struggling) = 5.3-point gap, worth ~0.15-0.2 goals to WSH
- Rest advantage: WSH 4 rest days (fatigue 1.0) vs PIT 2 days + 3-in-4 flag (fatigue 0.95) = real second/third-period edge
- Home ML historical support performance: a supportive track record broad historical support, a supportive track record in the tighter home combo historical support — our best-performing NHL category
- PIT offensive quality real but countered: Crosby/Malkin/Rakell driving 3.37 GPG, but Silovs' struggles could offset gains
- Model-market gap of 10.8pp (51.1% vs 61.9%) in this instance reflects the model underweighting goaltending/rest, not market overreaction
Risk Factors
- Thompson has only 1 start this season (.939 SV%) — small sample risk of regression toward a more pedestrian.915-.920 true-talent level
- Crosby/Malkin/Rakell core gives PIT high-end finishing ability that can beat even a hot goalie on a given night
- Matt Roy's absence (WSH top-pair D, 19.3 TOI/g) could open more high-danger chances against, partially offsetting the goalie edge
Edge Analysis
Moneyline
PIT 53.3%
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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 →
Permanent record: this game page is retired 90 days after the event. The full graded NHL 2026 record — every pick, win rate, units and ROI — lives on the NHL 2026 season report card.