icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | — | NAHL | 27 | 13 | 5 | 91.5% | 2.15 | 3 | 0.9843 | 81.8% |
| 2021-22 | — | NAHL | 17 | 6 | 5 | 89.6% | 3.25 | 1 | 0.9843 | 86.2% |
| 2020-21 | — | OJHL | — | — | — | — | — | — | 0.9700 | — |
| 2019-20 | — | OJHL | 28 | 11 | 11 | 91.4% | 2.83 | 0 | 0.9700 | 88.7% |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2025-26 | Canisius | D1 | 2 | 0 | 1 | 82.4% | 5.72 | 0 |
| 2024-25 | Canisius | D1 | 20 | 7 | 7 | 91.3% | 2.47 | 1 |
| 2023-24 | Canisius | D1 | 19 | 5 | 10 | 90.4% | 3.25 | 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 |
|---|---|---|---|---|---|---|
| Kayden Hargraves | NAHL | 91.5% | 81.8% | Augustana | 92.0% | 2.72 |
| Eli Pulver | BCHL | 92.4% | 81.7% | Minnesota | 95.8% | 1.00 |
| Andrew Takacs | NAHL | 91.8% | 82.0% | Colgate | 81.8% | 4.32 |
| J.J. Cataldo | NAHL | 91.8% | 82.3% | Army | 92.2% | 2.41 |
| Jakub Krbecek | NAHL | 92.1% | 82.2% | RIT | 89.3% | 3.90 |
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 |
|---|---|---|---|---|---|---|---|
| Jeffrey Fillion | NCDC | 89.6% | 81.6% | Wilkes | D3 | 92.4% | 1.96 |
| Kael DePape | NAHL | 89.1% | 82.0% | Williams | D3 | 88.2% | 3.14 |
| Ford DeLoss | NCDC | 90.0% | 82.1% | Stevenson | D3 | 88.9% | 3.00 |
| Alexei Masanko | OJHL | 92.5% | 81.6% | Manhattanville | D3 | 91.3% | 3.27 |
| Chase Hale | NCDC | 91.4% | 82.3% | Albertus Magnus | D3 | 92.2% | 2.54 |
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.