icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2024-25 | Edmonton Oil Kings | WHL | 1 | 0 | 1 | 92.0% | 2.01 | 0 | 1.0047 | 85.4% |
| 2023-24 | Edmonton Oil Kings | WHL | 48 | 22 | 18 | 88.9% | 3.75 | 1 | 1.0047 | 86.0% |
| 2022-23 | — | WHL | 50 | 6 | 36 | 87.3% | 4.89 | 1 | 1.0047 | 87.7% |
| 2021-22 | — | WHL | 25 | 16 | 4 | 88.5% | 3.11 | 0 | 1.0047 | 91.9% |
| 2020-21 | — | WHL | — | — | — | — | — | — | 1.0047 | — |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2025-26 | Augustana | D1 | 1 | 0 | 0 | — | — | 0 |
Historical goalies with similar age-adjusted SVe profiles who went on to play NCAA D1.
| Name | Junior League | Junior SV% | Adj SVe | College | NCAA SV% | NCAA GAA |
|---|---|---|---|---|---|---|
| Austin Elliott | OHL | 92.4% | 85.7% | UMass Lowell | 88.5% | 3.01 |
| Jacob Steinman | QMJHL | 92.3% | 85.4% | Bowling Green | 92.1% | 2.14 |
| Joshua Seeley | NAHL | 90.0% | 84.9% | Bentley | 82.6% | 8.58 |
| Justen Close | SJHL | 92.8% | 86.0% | Minnesota | 78.6% | 6.09 |
| Austin Roden | BCHL | 91.2% | 85.8% | Nebraska Omaha | 90.7% | 2.87 |
Historical goalies with similar age-adjusted SVe profiles who went on to play NCAA D2/D3.
| Name | Junior League | Junior SV% | Adj SVe | College | Div | SV% | GAA |
|---|---|---|---|---|---|---|---|
| Jadon Lee | USPHL-Premier | 93.3% | 86.0% | Lebanon Valley | D3 | 93.0% | 2.59 |
| Nicholas Von Kaufmann | OJHL | 88.9% | 85.5% | Marian | D3 | 88.6% | 3.25 |
| Will Augustine | USPHL-Premier | 94.0% | 86.5% | Rivier | D3 | 91.5% | 2.97 |
| Tucker Hanson | EHL | 89.0% | 85.7% | Saint Anselm | D2 | 100.0% | — |
| Colby Muise | AJHL | 91.6% | 86.8% | Marian | D3 | 93.2% | 1.77 |
How to read this: NCAAe and D3e factors convert a player's junior PPG into expected NCAA scoring at the D1 or D3 level. Harder conferences → lower projected PPG for the same player. A strong junior player (e.g. USHL 0.90 PPG) will project much higher in NESCAC than Big Ten because the D3 scoring environment is lower-difficulty.
Strength factor: conferences above 1.0 are harder than average; below 1.0 are easier. The formula is: Base NCAAe PPG ÷ Conference Strength = Projected PPG.