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 | 49 | 24 | 19 | 91.5% | 2.92 | 5 | 0.9843 | 85.7% |
| 2021-22 | — | NAHL | 38 | 23 | 11 | 91.8% | 2.56 | 1 | 0.9843 | 89.3% |
| 2020-21 | — | NAHL | 31 | 18 | 10 | 90.8% | 2.60 | 3 | 0.9843 | 89.4% |
| 2019-20 | — | NA3HL | 22 | 19 | 3 | 93.7% | 1.46 | 9 | 0.9400 | 88.1% |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2024-25 | Augustana | D1 | — | — | — | — | — | — |
| 2023-24 | Augustana | D1 | 9 | 4 | 3 | 92.0% | 2.72 | 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 |
|---|---|---|---|---|---|---|
| Ethan Robertson | NAHL | 91.5% | 85.7% | Canisius | 90.4% | 3.25 |
| Andrew Takacs | NAHL | 91.8% | 86.0% | Colgate | 81.8% | 4.32 |
| J.J. Cataldo | NAHL | 91.8% | 86.1% | Army | 92.2% | 2.41 |
| Henry Levy | BCHL | 91.8% | 86.0% | Arizona State | 100.0% | — |
| Teagan Kendrick | BCHL | 91.5% | 85.7% | Sacred Heart | 92.0% | 2.42 |
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 |
|---|---|---|---|---|---|---|---|
| Ford DeLoss | NCDC | 90.0% | 85.7% | Stevenson | D3 | 88.9% | 3.00 |
| Matthew Dore | USPHL-Premier | 94.4% | 85.8% | Rivier | D3 | 88.8% | 4.78 |
| Jeffrey Fillion | NCDC | 89.6% | 85.2% | Wilkes | D3 | 92.4% | 1.96 |
| Kael DePape | NAHL | 89.1% | 85.9% | Williams | D3 | 88.2% | 3.14 |
| Sebastian Woods | NCDC | 90.6% | 85.9% | Manhattanville | D3 | 91.4% | 3.07 |
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.