Net Goals 101 · component 10 of 11
Shootout
The shootout component prices every shootout attempt by how much it changed the odds of winning the extra standings point. This page works one real season through from the raw events to the number on the card. Every figure is recomputed from the model’s own data and checked against the published value.
Step 01 · The odds
A shootout as a win-probability table
A shootout decides the extra standings point and nothing else in net goals sees it: the on-ice components and Finishing stop at the end of overtime. Each attempt is priced by how much it moved the shooting team’s chance of winning the shootout, given the round, the score and who shoots next, with both teams converting at the season’s league rate (32.6% in 2025-26, 119 shootouts):
| State | Goals on attempts | First team wins |
|---|---|---|
| Before the first attempt | 0–0 on 0–0 | 50.0% |
| First shooter scores | 1–0 on 1–0 | 72.2% |
| First shooter misses | 0–0 on 1–0 | 39.3% |
| First team up 1-0 after two rounds | 1–0 on 2–2 | 89.0% |
| First team down 0-1 after two rounds | 0–1 on 2–2 | 11.0% |
| 1-1, second team's last shooter to come | 1–1 on 3–2 | 33.7% |
| Tied after three: sudden death | 1–1 on 3–3 | 50.0% |
Step 02 · Every attempt
McTavish’s 6 attempts
One shootout win is the extra point, which is three goals at the site’s six goals per win, so each attempt is worth three goals times the change in the odds. His rows are highlighted; the goalie he faced gets the mirror image in his GSAx.
| # | Team | Shooter | Result | Score after | Shooting team’s odds | Goals |
|---|---|---|---|---|---|---|
| 1 | ANA | Leo Carlsson | no goal | 0-0 | 50.0% → 39.3% | −0.321 |
| 2 | FLA | Sam Reinhart | no goal | 0-0 | 60.7% → 50.0% | −0.321 |
| 3 | ANA | Troy Terry | goal | 1-0 | 50.0% → 76.3% | +0.789 |
| 4 | FLA | Anton Lundell | goal | 1-1 | 23.7% → 50.0% | +0.789 |
| 5 | ANA | Mason McTavish | goal | 2-1 | 50.0% → 83.7% | +1.011 |
| 6 | FLA | Evan Rodrigues | no goal | 2-1 | 16.3% → 0.0% | −0.489 |
| # | Team | Shooter | Result | Score after | Shooting team’s odds | Goals |
|---|---|---|---|---|---|---|
| 1 | ANA | Leo Carlsson | no goal | 0-0 | 50.0% → 39.3% | −0.321 |
| 2 | LAK | Kevin Fiala | no goal | 0-0 | 60.7% → 50.0% | −0.321 |
| 3 | ANA | Troy Terry | goal | 1-0 | 50.0% → 76.3% | +0.789 |
| 4 | LAK | Adrian Kempe | no goal | 1-0 | 23.7% → 11.0% | −0.382 |
| 5 | ANA | Mason McTavish | goal | 2-0 | 89.0% → 100.0% | +0.330 |
| # | Team | Shooter | Result | Score after | Shooting team’s odds | Goals |
|---|---|---|---|---|---|---|
| 1 | ANA | Leo Carlsson | no goal | 0-0 | 50.0% → 39.3% | −0.321 |
| 2 | WSH | Dylan Strome | no goal | 0-0 | 60.7% → 50.0% | −0.321 |
| 3 | ANA | Troy Terry | goal | 1-0 | 50.0% → 76.3% | +0.789 |
| 4 | WSH | Anthony Beauvillier | goal | 1-1 | 23.7% → 50.0% | +0.789 |
| 5 | ANA | Mason McTavish | goal | 2-1 | 50.0% → 83.7% | +1.011 |
| 6 | WSH | Ethen Frank | no goal | 2-1 | 16.3% → 0.0% | −0.489 |
| # | Team | Shooter | Result | Score after | Shooting team’s odds | Goals |
|---|---|---|---|---|---|---|
| 1 | LAK | Adrian Kempe | no goal | 0-0 | 50.0% → 39.3% | −0.321 |
| 2 | ANA | Mikael Granlund | no goal | 0-0 | 60.7% → 50.0% | −0.321 |
| 3 | LAK | Brandt Clarke | goal | 1-0 | 50.0% → 76.3% | +0.789 |
| 4 | ANA | Beckett Sennecke | goal | 1-1 | 23.7% → 50.0% | +0.789 |
| 5 | LAK | Kevin Fiala | no goal | 1-1 | 50.0% → 33.7% | −0.489 |
| 6 | ANA | Mason McTavish | goal | 1-2 | 66.3% → 100.0% | +1.011 |
| # | Team | Shooter | Result | Score after | Shooting team’s odds | Goals |
|---|---|---|---|---|---|---|
| 1 | ANA | Leo Carlsson | goal | 1-0 | 50.0% → 72.2% | +0.664 |
| 2 | CGY | Morgan Frost | no goal | 1-0 | 27.9% → 17.1% | −0.321 |
| 3 | ANA | Beckett Sennecke | no goal | 1-0 | 82.9% → 76.3% | −0.197 |
| 4 | CGY | Nazem Kadri | goal | 1-1 | 23.7% → 50.0% | +0.789 |
| 5 | ANA | Mason McTavish | goal | 2-1 | 50.0% → 83.7% | +1.011 |
| 6 | CGY | Matvei Gridin | no goal | 2-1 | 16.3% → 0.0% | −0.489 |
| # | Team | Shooter | Result | Score after | Shooting team’s odds | Goals |
|---|---|---|---|---|---|---|
| 1 | ANA | Leo Carlsson | no goal | 0-0 | 50.0% → 39.3% | −0.321 |
| 2 | MTL | Cole Caufield | no goal | 0-0 | 60.7% → 50.0% | −0.321 |
| 3 | ANA | Beckett Sennecke | no goal | 0-0 | 50.0% → 37.3% | −0.382 |
| 4 | MTL | Nick Suzuki | no goal | 0-0 | 62.7% → 50.0% | −0.382 |
| 5 | ANA | Mason McTavish | no goal | 0-0 | 50.0% → 33.7% | −0.489 |
| 6 | MTL | Kirby Dach | no goal | 0-0 | 66.3% → 50.0% | −0.489 |
| 7 | ANA | Cutter Gauthier | goal | 1-0 | 50.0% → 83.7% | +1.011 |
| 8 | MTL | Ivan Demidov | goal | 1-1 | 16.3% → 50.0% | +1.011 |
| 9 | ANA | Chris Kreider | no goal | 1-1 | 50.0% → 33.7% | −0.489 |
| 10 | MTL | Lane Hutson | no goal | 1-1 | 66.3% → 50.0% | −0.489 |
| 11 | ANA | Alex Killorn | goal | 2-1 | 50.0% → 83.7% | +1.011 |
| 12 | MTL | Oliver Kapanen | no goal | 2-1 | 16.3% → 0.0% | −0.489 |
Step 03 · The season
5 of 6
Step 04 · Position
Measured against the average forward
After every other step, each component is re-centred once more, separately for forwards and for defencemen, so the average forward in 2025-26 is exactly zero in every column. The games-weighted mean shootout value of all forwards that season was +0.00014 net goals per game, so 75 games of it come off:
Step 05 · Result
Per 84 games
Ratings are quoted per 84 games, one full schedule, so a part season and a full one sit on the same scale.
Recomputed +4.34; his 2025-26 row on the player card and the Players table shows +4.3. They match.
Step 06 · Context
How unusual is this?
| Percentile | 5th | 25th | Median | 75th | 95th | Best |
|---|---|---|---|---|---|---|
| Shootout NG/84 | −1.2 | −0.0 | −0.0 | +0.0 | +1.4 | +4.3 |
Skaters with 40 or more games in 2025-26 (612 players). Mason McTavish ranks 1 of 612.
It is real value, since those points counted, but it barely repeats: a player’s shootout number correlates about 0.04 with his next season’s. Careers are shrunk by attempts, not games: at about 86 attempts a record is half his own, half average.
The numbers on this page were rebuilt on 2026-10-08 from the same files the cards are built from. The model behind every step is described on Net Goals 101; definitions are in the Reference.