icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | — | NCDC | 24 | 11 | 11 | 91.9% | 2.93 | 1 | 0.9400 | 84.3% |
| 2021-22 | — | NCDC | — | — | — | — | — | — | 0.9400 | — |
| 2019-20 | — | EHLP | 23 | 12 | 13 | 91.2% | 3.20 | 5 | 0.9400 | 85.7% |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2025-26 | Alvernia | D3 | 3 | — | — | 86.5% | 6.08 | 0 |
| 2024-25 | Alvernia | D3 | 17 | 7 | 8 | 89.6% | 3.21 | 1 |
| 2023-24 | Alvernia | D3 | 9 | 5 | 3 | 88.8% | 3.50 | 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 |
|---|---|---|---|---|---|---|
| Sam Scopa | NAHL | 89.7% | 85.6% | Quinnipiac | 100.0% | — |
| Stephen Peck | USHL | 90.9% | 82.5% | Michigan | 91.1% | 2.61 |
| Jake Barczewski | USHL | 90.4% | 82.3% | Canisius | 90.5% | 2.92 |
| Troy Kobryn | NCDC | 92.2% | 83.6% | Merrimack | 89.3% | 3.30 |
| Ethan David | BCHL | 90.9% | 85.5% | RIT | 90.9% | 2.68 |
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 |
|---|---|---|---|---|---|---|---|
| Gustave Bylin | AJHL | 90.4% | 85.5% | Tufts | D3 | 89.8% | 3.01 |
| Caleb Chabot | CCHL | 89.1% | 84.2% | Albertus Magnus | D3 | 93.4% | 1.79 |
| Tyler Laureault | CCHL | 90.6% | 84.7% | St. Olaf | D3 | 88.7% | 3.36 |
| Nolan Mahaffey | NCDC | 87.4% | 85.4% | Lawrence | D3 | 90.5% | 3.39 |
| Maxim Zinchenko | USPHL-Premier | 91.8% | 85.4% | Johnson & Wales | D3 | 90.8% | 3.68 |
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.