icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2023-24 | — | OJHL | 42 | 37 | 5 | 94.5% | 1.30 | 12 | 0.9700 | 81.2% |
| 2022-23 | — | OJHL | 38 | 29 | 5 | 91.7% | 2.01 | 5 | 0.9700 | 85.3% |
| 2021-22 | — | OJHL | 41 | 22 | 16 | 92.2% | 2.28 | 4 | 0.9700 | 92.2% |
| 2020-21 | — | OJHL | — | — | — | — | — | — | 0.9700 | — |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2025-26 | Yale | D1 | 22 | 6 | 14 | 90.2% | 3.22 | 0 |
| 2024-25 | Yale | D1 | 8 | 3 | 4 | 87.2% | 3.86 | 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 |
|---|---|---|---|---|---|---|
| Brendan Holahan | NAHL | 89.7% | 82.1% | Union | 85.7% | 4.48 |
| Owen Say | BCHL | 92.3% | 82.7% | Mercyhurst | 90.3% | 3.39 |
| Joshua Seeley | NAHL | 90.0% | 81.6% | Bentley | 82.6% | 8.58 |
| Justen Close | SJHL | 92.8% | 82.4% | Minnesota | 78.6% | 6.09 |
| Austin Roden | BCHL | 91.2% | 81.1% | 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 |
|---|---|---|---|---|---|---|---|
| Michael Cammasso | USPHL-Premier | 92.4% | 81.2% | Johnson & Wales | D3 | 82.2% | 8.99 |
| Josh Koziol | NA3HL | 93.3% | 81.2% | Augsburg | D3 | 71.4% | 5.76 |
| Cam Prodin | USPHL-Premier | 93.6% | 81.8% | Roger Williams | D3 | 75.8% | 9.18 |
| Diego D'Alessandro | CCHL | 89.2% | 80.7% | King's | D3 | 86.5% | 4.68 |
| Dylan Kruss | NCDC | 88.5% | 81.6% | Lake Forest | D3 | 91.8% | 2.84 |
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.