icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | — | EHL | 16 | 6 | 10 | 89.0% | 3.34 | 1 | 0.9400 | 79.9% |
| 2020-21 | — | EHLP | 9 | 2 | 7 | 86.8% | 5.53 | 0 | 0.9400 | 81.6% |
| 2020-21 | — | EHL | 1 | 0 | 1 | 84.4% | 7.00 | 0 | 0.9400 | 79.3% |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2025-26 | Saint Anselm | D2 | 9 | — | — | 86.3% | 3.96 | 0 |
| 2024-25 | Saint Anselm | D2 | 5 | 2 | 3 | 87.9% | 4.31 | 1 |
| 2023-24 | Saint Anselm | D2 | 5 | 1 | 3 | 89.0% | 4.01 | — |
| 2022-23 | Saint Anselm | D2 | 1 | 0 | 0 | 100.0% | — | — |
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 |
|---|---|---|---|---|---|---|
| Jacob Steinman | QMJHL | 92.3% | 79.8% | Bowling Green | 92.1% | 2.14 |
| Ben Bonisteel | OJHL | 92.6% | 79.9% | Canisius | 89.3% | 3.10 |
| Brandon Bussi | USHL | 91.5% | 79.8% | Western Michigan | 91.0% | 2.65 |
| Noah Pak | OJHL | 94.5% | 81.2% | Yale | 87.2% | 3.86 |
| Austin Elliott | OHL | 92.4% | 79.6% | UMass Lowell | 88.5% | 3.01 |
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 |
|---|---|---|---|---|---|---|---|
| Owen Swanbon | USPHL-Premier | 90.4% | 79.8% | Framingham State | D3 | 83.3% | 8.53 |
| Jeffrey Reda | USPHL-Premier | 90.6% | 80.1% | Franklin Pierce | D2 | 85.9% | 5.85 |
| Liam Gross | USPHL-Premier | 90.2% | 80.0% | Buffalo State | D3 | 85.7% | 5.75 |
| Diego D'Alessandro | CCHL | 89.2% | 80.7% | King's | D3 | 86.5% | 4.68 |
| Michael Cammasso | USPHL-Premier | 92.4% | 81.2% | Johnson & Wales | D3 | 82.2% | 8.99 |
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.