icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | — | NA3HL | 4 | 4 | 0 | 93.7% | 2.99 | 0 | 0.9400 | 77.9% |
| 2022-23 | — | NAHL | — | — | — | — | — | — | 0.9843 | — |
| 2021-22 | — | NA3HL | 10 | 0 | 9 | 89.4% | 5.14 | 0 | 0.9400 | 79.6% |
| 2021-22 | — | USHL | 2 | 1 | 1 | 85.5% | 4.76 | 0 | 0.9980 | 78.0% |
| 2019-20 | — | USHL | — | — | — | — | — | — | 0.9980 | — |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2025-26 | St. Norbert | D3 | — | — | — | — | — | — |
| 2024-25 | St. Norbert | D3 | — | — | — | — | — | — |
| 2023-24 | St. Norbert | D3 | — | — | — | — | — | — |
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 |
|---|---|---|---|---|---|---|
| Lukas Renaud | AJHL | 92.4% | 77.8% | Long Island Univ. | 89.7% | 2.57 |
| Daniel Hauser | WHL | 91.3% | 76.6% | Wisconsin | 90.0% | 2.49 |
| Luke Lush | AJHL | 91.9% | 77.5% | Sacred Heart | 91.5% | 2.11 |
| Aaron Matthews | NCDC | 90.7% | 77.9% | Providence | — | — |
| Jacob Zacharewicz | NAHL | 89.2% | 79.5% | Brown | 86.8% | 4.19 |
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 |
|---|---|---|---|---|---|---|---|
| Brian Tallieu | USPHL-Premier | 91.3% | 77.8% | Lawrence | D3 | 88.6% | 4.50 |
| Hunter Thomas | USPHL-Premier | 90.2% | 77.3% | Salem State | D3 | 87.3% | 5.20 |
| Nic Tallarico | NOJHL | 92.1% | 78.5% | Adrian | D3 | 90.1% | 2.46 |
| Marcus Cumberworth | AJHL | 88.7% | 77.7% | Buffalo State | D3 | 90.8% | 3.33 |
| Blake Bjella | USPHL-Premier | 91.5% | 78.2% | Worcester State | D3 | 87.0% | 3.54 |
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.