San Jose Sharks at Florida Panthers, NHL forecast
Win probability
Starts from the pregame forecast, then moves with every score and the time left. Above the line favors FLA; hover for each play.
Game center
From the ESPN box score.
Top performers
Sharks- Fabian ZetterlundGoals1
- William EklundAssists1
- Fabian ZetterlundPoints1
Panthers- Carter VerhaegheGoals1
- Matthew TkachukAssists2
- Matthew TkachukPoints2
Scoring summary
- P319:58Kevin Stenlund Goal (2) Wrist Shot, assists: Matthew Tkachuk (6), Anton Lundell (1)1–3
- P215:23Sam Reinhart Goal (7) Wrist Shot, assists: Oliver Ekman-Larsson (2), Evan Rodrigues (6)1–2
- P29:48Carter Verhaeghe Goal (3) Wrist Shot, assists: Matthew Tkachuk (5), Eetu Luostarinen (1)1–1
- P28:30Fabian Zetterlund Goal (2) Wrist Shot, assists: William Eklund (1), Thomas Bordeleau (1)1–0
Turning points
The 4 plays that swung the win chance most, each judged at its own moment: the chance with the score just before it against just after.
- P28:30Fabian Zetterlund Goal (2) Wrist Shot, assists: William Eklund (1), Thomas Bordeleau (1)SJ 1 – 0 FLA · SJ 46% → 65% +20SJ 46% → 65%+20 pts
- P29:48Carter Verhaeghe Goal (3) Wrist Shot, assists: Matthew Tkachuk (5), Eetu Luostarinen (1)SJ 1 – 1 FLA · FLA 34% → 54% +20FLA 34% → 54%+20 pts
- P215:23Sam Reinhart Goal (7) Wrist Shot, assists: Oliver Ekman-Larsson (2), Evan Rodrigues (6)SJ 1 – 2 FLA · FLA 54% → 75% +21FLA 54% → 75%+21 pts
- P319:58Kevin Stenlund Goal (2) Wrist Shot, assists: Matthew Tkachuk (6), Anton Lundell (1)SJ 1 – 3 FLA · FLA 100% → 100% +0FLA 100% → 100%+0 pts
The pick
Reconstructed from what was known before the game: the ratings at that point.
Panthers 56%
Forecast Elo ratings alone
How often that comes true: NHL favorites the forecast gave 55–60% have won 56.4% of 1,035 graded games.
- Market
- No line yet
- Pre-line forecast
- FLA 56%
- Elo + market-implied
- Elo ratings
- FLA 60%
- Fair odds
- FLA -127
- SJ +127 · the forecast as odds, no margin
- Pregame projection
- SJ 2.9 – 3.3 FLA
- Margin from the forecast, total from team scoring ratings
How the number is built
Elo inputs in rating points (higher favors that team; 25–28 Elo is about a point of spread in football and basketball), then how the pieces combine.
| Factor | SJ | FLA | Why |
|---|---|---|---|
| Team rating | 1479 | 1495 | Elo entering the game; 1500 is league average |
| Home field | — | +35 | Worth 35 Elo in the NHL |
| Starting goalies | −16 | +1 | SJ: Mackenzie Blackwood: team allows 0.41 more goals than with its usual starter (≈3 weighted starts) · FLA: Anthony Stolarz (no track record yet) |
| Elo ratings | FLA +68 Elo | FLA 59.7% | |
| Market-implied ratings | FLA 55.0% | Team strength as past closing lines priced it, same game context | |
| Pre-line forecast | FLA 56.0% | 20% Elo, 80% market-implied (log-odds blend) | |
Tale of the tape
This season coming into the game, regular season, each number with its league rank (the longer the bar, the higher). Home and road: the host's record at home against the visitor's on the road. Overtime and shootout losses count as losses in these records. Shot share is a team's share of the shots on goal in its games. PDO adds shooting and save percentages: far from 100 tends to even out.
| SJ | Stat | FLA |
|---|---|---|
| 30th of 311.4 | Goals scored | 2.821st of 31 |
| 27th of 314.0 | Goals allowed | 3.419th of 31 |
| 31st of 31−2.6 | Margin | −0.620th of 31 |
| 31st of 3137.8% | Shot share | 52.1%13th of 31 |
| 17th of 3190.3% | Save percentage | 89.9%20th of 31 |
| 24th of 310–1 | Road vs home | 1–115th of 31 |
Rating history
Each team's Elo over the last two seasons. Hover or drag to compare on any date.
Recent form
Last five results, and whether the forecast hit.