icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2024-25 | — | EHL | 31 | 14 | 17 | 92.4% | 2.89 | 2 | 0.9400 | 83.7% |
| 2023-24 | — | EHL | 28 | 9 | 13 | 92.4% | 2.78 | 2 | 0.9400 | 87.0% |
| 2022-23 | — | NAHL | 1 | 0 | 0 | 100.0% | — | 0 | 0.9843 | 97.0% |
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 Zacharewicz | NAHL | 89.2% | 83.4% | Brown | 86.8% | 4.19 |
| Luke Lush | AJHL | 91.9% | 83.0% | Sacred Heart | 91.5% | 2.11 |
| Daniel Hauser | WHL | 91.3% | 83.7% | Wisconsin | 90.0% | 2.49 |
| Ryan Snowden | USHL | 89.8% | 82.7% | Ohio State | 90.5% | 2.52 |
| Ryan Manzella | USHL | 90.4% | 83.1% | Michigan Tech | 89.5% | 3.17 |
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 |
|---|---|---|---|---|---|---|---|
| Logan Gorbitz | USPHL-Premier | 91.8% | 83.9% | Neumann | D3 | 84.4% | 5.24 |
| Colby Entz | SJHL | 89.8% | 82.9% | St. Norbert | D3 | 93.0% | 1.88 |
| Dawson Rodin | NOJHL | 92.8% | 84.5% | Marian | D3 | 89.3% | 3.24 |
| Anthony Bonaldi | USPHL-Premier | 90.6% | 82.7% | Nichols | D3 | 81.8% | 7.78 |
| Nikolas Trakakis | MJHL | 87.9% | 83.1% | Chatham | D3 | 93.4% | 2.45 |
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.