icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Buffalo Jr. Sabres | OJHL | 37 | 16 | 13 | 92.6% | 2.61 | 4 | 0.9700 | 91.4% |
| 2024-25 | — | OJHL | 31 | 18 | 10 | 92.3% | 2.35 | 2 | 0.9700 | 94.7% |
| 2023-24 | — | OJHL | 2 | 0 | 0 | 86.1% | 4.25 | 0 | 0.9700 | 91.5% |
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 |
|---|---|---|---|---|---|---|
| Ben Kraws | USHL | 89.5% | 90.4% | Miami | 87.1% | 4.12 |
| Kaidan Mbereko | USHL | 89.8% | 90.6% | Colorado College | 92.5% | 2.30 |
| Jan Korec | USHL | 90.1% | 91.3% | Boston College | 91.8% | 1.75 |
| Louka Cloutier | USHL | 88.2% | 89.0% | Boston College | 91.0% | 2.34 |
| Mathis Langevin | QMJHL | 91.2% | 91.3% | Miami | 93.8% | 2.00 |
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 |
|---|---|---|---|---|---|---|---|
| Brody Haynes | NCDC | 92.5% | 92.3% | Elmira | D3 | 94.8% | 1.22 |
| Cooper Rautenstrauch | NCDC | 90.6% | 92.2% | Colby | D3 | 93.4% | 2.08 |
| Cooper Rautenstrauch | NAHL | 88.9% | 92.2% | Colby | D3 | 93.4% | 2.08 |
| Vaughn Makar | NAHL | 90.9% | 94.0% | St. Norbert | D3 | 93.2% | 1.73 |
| Justin Damon | USPHL-Premier | 94.0% | 91.2% | Gustavus Adolphus | D3 | 92.9% | 2.27 |
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.