NHL Projected Goals Against This Week
Goals against projections help you avoid bad goalie matchups. Our GA projections show which goalies are facing tough offensive opponents this week. Use this data to bench goalies in difficult spots and stream netminders with favorable matchups (Oct 12-18 (Week 3)). (Oct 12-18 (Week 3))
Sorted by Projected Goaltending Goals Against(Oct 12-18 (Week 3))
55 playersGoalies55 of 55
| Player | Team | Pos | Rost% | GA ↑ | GS | W | L | OTL | SV | SA | SV% | GAA† | MIN† | FPTS |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Scott Wedgewood | COL | G | 88.9% | 2.4 | 1.00 | 0.68 | 0.33 | 0.09 | 23.3 | 25.7 | 90.6% | 2.43 | 59:55 | 10.65 |
| Brandon Bussi | CAR | G | 93.8% | 2.6 | 1.00 | 0.60 | 0.31 | 0.09 | 22.5 | 25.1 | 89.6% | 2.61 | 60:03 | 8.72 |
| Jordan Binnington | STL | G | 26.8% | 2.7 | 1.00 | 0.42 | 0.37 | 0.10 | 22.7 | 25.4 | 89.4% | 2.69 | 59:55 | 7.76 |
| Casey DeSmith | DAL | G | 15.6% | 2.7 | 1.00 | 0.43 | 0.46 | 0.11 | 25.2 | 28.0 | 90.2% | 2.74 | 60:06 | 9.17 |
| Daniil Tarasov | DET | G | 11.5% | 2.8 | 1.00 | 0.55 | 0.36 | 0.09 | 24.0 | 26.8 | 89.5% | 2.80 | 60:23 | 8.86 |
| Joseph Woll | PHI | G | 39.4% | 2.9 | 1.00 | 0.41 | 0.53 | 0.16 | 26.3 | 29.2 | 90.1% | 2.89 | 59:55 | 9.08 |
| Jakub Dobes | MTL | G | 93.0% | 2.9 | 1.00 | 0.50 | 0.40 | 0.10 | 24.5 | 27.4 | 89.4% | 2.91 | 59:55 | 8.85 |
| Alex Nedeljkovic | SJS | G | 16.7% | 2.9 | 1.00 | 0.44 | 0.45 | 0.11 | 25.0 | 27.9 | 89.5% | 2.90 | 60:24 | 8.37 |
| Connor Hellebuyck | WPG | G | 91.3% | 3.0 | 1.00 | 0.60 | 0.50 | 0.10 | 30.8 | 33.7 | 91.1% | 3.00 | 59:56 | 12.80 |
| Tristan Jarry | EDM | G | 26.1% | 3.0 | 1.00 | 0.48 | 0.42 | 0.10 | 25.5 | 28.6 | 89.4% | 3.03 | 60:01 | 8.66 |
| Arturs Silovs | PIT | G | 57.0% | 3.2 | 1.00 | 0.39 | 0.50 | 0.11 | 25.1 | 28.3 | 88.8% | 3.18 | 59:56 | 7.88 |
| Dylan Garand | NYR | G | 53.2% | 4.2 | 2.00 | 0.84 | 0.40 | 0.16 | 42.9 | 47.1 | 91.1% | 2.98 | 84:06 | 18.21 |
| Clay Stevenson | WPG | G | 11.4% | 4.4 | 2.00 | 0.85 | 0.35 | 0.20 | 38.7 | 43.2 | 89.7% | 3.45 | 77:25 | 14.03 |
| Matt Murray | NSH | G | 0.1% | 4.6 | 2.00 | 0.85 | 0.31 | 0.24 | 39.5 | 44.1 | 89.6% | 3.65 | 75:38 | 14.53 |
| Joel Hofer | STL | G | 83.0% | 4.6 | 2.00 | 0.95 | 0.80 | 0.25 | 45.0 | 49.7 | 90.6% | 2.32 | 120:02 | 19.02 |
| Jake Oettinger | DAL | G | 99.1% | 4.7 | 2.00 | 1.10 | 0.71 | 0.19 | 45.5 | 50.2 | 90.6% | 2.37 | 119:46 | 19.73 |
| Pyotr Kochetkov | CAR | G | 53.7% | 4.9 | 2.00 | 1.25 | 0.61 | 0.14 | 45.4 | 50.3 | 90.3% | 2.43 | 120:01 | 19.33 |
| Jet Greaves | CBJ | G | 79.8% | 4.9 | 2.00 | 0.99 | 0.81 | 0.20 | 46.4 | 51.3 | 90.4% | 2.46 | 120:32 | 18.41 |
| Andrei Vasilevskiy | TBL | G | 99.2% | 5.0 | 2.00 | 1.27 | 0.62 | 0.12 | 43.1 | 48.1 | 89.7% | 2.49 | 119:37 | 17.97 |
| Sergei Murashov | PIT | G | 61.8% | 5.0 | 2.00 | 0.54 | 0.54 | 0.22 | 42.5 | 47.5 | 89.5% | 3.59 | 83:19 | 13.52 |
| Jacob Fowler | MTL | G | 52.3% | 5.2 | 2.00 | 1.15 | 0.80 | 0.14 | 47.5 | 52.6 | 90.2% | 2.58 | 120:06 | 19.22 |
| Mackenzie Blackwood | COL | G | 91.0% | 5.2 | 2.00 | 1.34 | 0.54 | 0.12 | 46.2 | 51.5 | 89.8% | 2.62 | 119:51 | 19.25 |
| Joey Daccord | SEA | G | 67.3% | 5.2 | 2.00 | 0.84 | 0.89 | 0.17 | 49.7 | 54.9 | 90.4% | 2.64 | 119:16 | 18.92 |
| Jeremy Swayman | BOS | G | 96.6% | 5.3 | 2.00 | 0.96 | 0.78 | 0.16 | 50.7 | 56.0 | 90.5% | 2.66 | 119:55 | 20.10 |
| Ilya Sorokin | NYI | G | 97.3% | 5.3 | 2.00 | 1.03 | 0.86 | 0.20 | 46.8 | 52.1 | 89.8% | 2.66 | 119:48 | 18.17 |
| John Gibson | DET | G | 63.9% | 5.4 | 2.00 | 1.08 | 0.89 | 0.23 | 47.4 | 52.8 | 89.7% | 2.74 | 118:30 | 17.74 |
| Philipp Grubauer | SEA | G | 15.2% | 5.4 | 2.00 | 0.84 | 0.85 | 0.21 | 50.1 | 55.5 | 90.2% | 2.70 | 120:48 | 18.14 |
| Stuart Skinner | WPG | G | 62.1% | 5.6 | 2.00 | 0.99 | 0.80 | 0.21 | 50.1 | 55.6 | 90.0% | 2.79 | 119:43 | 18.16 |
| Logan Thompson | WSH | G | 99.8% | 5.6 | 2.00 | 1.06 | 0.69 | 0.15 | 54.5 | 60.1 | 90.7% | 2.81 | 119:45 | 21.84 |
| Cam Talbot | CBJ | G | 6.6% | 5.6 | 2.00 | 0.79 | 1.14 | 0.17 | 48.5 | 54.2 | 89.6% | 2.80 | 120:33 | 15.93 |
| Anthony Stolarz | TOR | G | 36.4% | 5.6 | 2.00 | 1.07 | 0.87 | 0.15 | 51.7 | 57.3 | 90.2% | 2.83 | 119:34 | 19.86 |
| Anton Forsberg | LAK | G | 20.9% | 5.7 | 2.00 | 1.08 | 0.74 | 0.18 | 45.3 | 51.1 | 88.8% | 2.83 | 121:32 | 15.96 |
| Karel Vejmelka | UTA | G | 97.9% | 5.8 | 2.00 | 1.09 | 0.67 | 0.15 | 45.7 | 51.5 | 88.8% | 2.87 | 120:34 | 16.13 |
| Darcy Kuemper | LAK | G | 51.2% | 5.8 | 2.00 | 1.04 | 0.88 | 0.18 | 45.8 | 51.6 | 88.8% | 2.93 | 118:40 | 15.78 |
| Lukas Dostal | ANA | G | 83.2% | 5.8 | 2.00 | 1.12 | 0.89 | 0.19 | 49.4 | 55.2 | 89.5% | 2.91 | 119:30 | 17.69 |
| Leevi Merilainen | VAN | G | 20.4% | 5.8 | 2.00 | 0.58 | 0.85 | 0.17 | 45.5 | 51.3 | 88.7% | 3.88 | 89:50 | 12.37 |
| Kevin Lankinen | VAN | G | 22.4% | 5.9 | 2.00 | 0.49 | 0.84 | 0.17 | 41.5 | 47.5 | 87.5% | 4.83 | 73:46 | 9.60 |
| Daniel Vladar | PHI | G | 61.4% | 6.0 | 2.00 | 0.75 | 0.99 | 0.26 | 51.4 | 57.4 | 89.5% | 3.02 | 119:47 | 16.86 |
| Sergei Bobrovsky | TOR | G | 84.8% | 6.0 | 2.00 | 0.86 | 0.99 | 0.26 | 52.5 | 58.5 | 89.7% | 3.02 | 119:48 | 18.00 |
| Devon Levi | EDM | G | 54.0% | 6.0 | 2.00 | 1.03 | 0.81 | 0.16 | 53.1 | 59.1 | 89.8% | 3.02 | 119:54 | 18.99 |
| Spencer Knight | CHI | G | 73.3% | 6.1 | 2.00 | 0.92 | 1.06 | 0.21 | 50.4 | 56.4 | 89.3% | 3.03 | 119:52 | 16.70 |
| Juuse Saros | NSH | G | 85.3% | 6.2 | 2.00 | 0.95 | 1.00 | 0.25 | 51.5 | 57.7 | 89.3% | 3.09 | 119:36 | 17.44 |
| Yaroslav Askarov | SJS | G | 74.8% | 6.4 | 2.00 | 0.81 | 0.97 | 0.21 | 48.9 | 55.3 | 88.5% | 3.20 | 119:13 | 14.17 |
| Dustin Wolf | CGY | G | 54.5% | 6.9 | 2.00 | 0.63 | 1.16 | 0.21 | 51.8 | 58.7 | 88.3% | 3.46 | 119:23 | 14.22 |
| Linus Ullmark | OTT | G | 88.9% | 7.2 | 3.00 | 1.87 | 0.89 | 0.24 | 68.8 | 75.9 | 90.6% | 2.40 | 179:01 | 29.92 |
| Carter Hart | VGK | G | 89.0% | 7.6 | 3.00 | 1.92 | 0.88 | 0.20 | 69.9 | 77.6 | 90.2% | 2.55 | 179:32 | 28.76 |
| Adin Hill | VGK | G | 27.3% | 7.7 | 3.00 | 2.02 | 0.84 | 0.25 | 69.8 | 77.5 | 90.1% | 2.57 | 179:23 | 29.30 |
| Jacob Markstrom | FLA | G | 91.8% | 7.8 | 3.00 | 1.75 | 0.84 | 0.31 | 64.4 | 72.2 | 89.2% | 2.61 | 178:36 | 25.46 |
| Jake Allen | NJD | G | 53.8% | 8.0 | 3.00 | 1.61 | 1.04 | 0.24 | 69.2 | 77.2 | 89.7% | 2.66 | 180:05 | 26.07 |
| Jesper Wallstedt | MIN | G | 96.4% | 8.0 | 3.00 | 1.78 | 1.10 | 0.32 | 75.3 | 83.3 | 90.4% | 2.66 | 180:04 | 30.33 |
| Akira Schmid | FLA | G | 24.4% | 8.1 | 3.00 | 1.71 | 0.97 | 0.32 | 68.6 | 76.7 | 89.4% | 2.66 | 182:33 | 26.02 |
| Colten Ellis | BUF | G | 16.3% | 8.4 | 3.00 | 1.34 | 1.06 | 0.30 | 70.9 | 79.3 | 89.4% | 2.81 | 179:13 | 25.50 |
| Ukko-Pekka Luukkonen | BUF | G | 66.1% | 8.5 | 3.00 | 1.49 | 1.06 | 0.35 | 70.3 | 78.8 | 89.3% | 2.81 | 180:59 | 24.73 |
| Samuel Ersson | OTT | G | 10.6% | 8.8 | 3.00 | 1.39 | 1.21 | 0.30 | 67.7 | 76.5 | 88.5% | 2.91 | 181:03 | 21.87 |
| Calvin Pickard | MIN | G | 4.1% | 8.8 | 3.00 | 1.43 | 1.53 | 0.14 | 72.3 | 81.1 | 89.2% | 2.93 | 180:21 | 24.29 |
† Edgehalla model: derived from LineupExperts' goals, assists and ice-time projection plus NHL history. +/-, shorthanded goals, assists and points are high-variance: the projections are small expected values ranked mostly by ice-time role, and actual totals swing a lot. How the model works
Goalie shots against, saves, goals against, SV%, GAA, wins and OTL are an Edgehalla blend: LineupExperts' goalie line averaged 50/50 with Edgehalla's own goalie model.
Why GA matters
Goals against directly impact fantasy scoring. In most formats, each GA costs 1-3 points, potentially negating saves and win bonuses.
GA risk factors
- Opponent offense: Elite offenses score 3.5+ goals per game - Goalie quality: Weaker goalies allow more goals - Team defense: Bad defense leads to high-danger chances - Special teams: Facing good power plays increases GA risk
GA benchmarks
- Low risk: 2.0-2.5 expected GA - Medium risk: 2.5-3.0 expected GA - High risk: 3.0+ expected GA
Avoid These Matchups
Identify high-GA risk matchups. Goalies facing elite offenses may struggle regardless of talent level.
Games This WeekSafe Goalie Starts
Low-GA projections indicate safe matchups. Target these starts when protecting your goalie categories.
All GoaliesGA vs. Saves Analysis
High GA often comes with high saves. Determine if the saves are worth the goals against risk.
Saves ProjectionsRelated Projections
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