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 | 38 | 17 | 15 | 90.2% | 3.21 | 2 | 0.9843 | 84.2% |
| 2021-22 | — | NAHL | 26 | 12 | 13 | 89.1% | 3.04 | 3 | 0.9843 | 89.2% |
| 2020-21 | — | NA3HL | 21 | 19 | 2 | 94.9% | 1.30 | 6 | 0.9400 | 89.2% |
| 2020-21 | — | NAHL | — | — | — | — | — | — | 0.9843 | — |
| 2019-20 | — | NA3HL | 13 | 11 | 1 | 92.0% | 1.76 | 3 | 0.9400 | 86.5% |
| 2019-20 | — | USHL | — | — | — | — | — | — | 0.9980 | — |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2025-26 | Clarkson | D1 | 35 | 17 | 14 | 90.5% | 2.54 | 2 |
| 2024-25 | Curry | D3 | 28 | 24 | 4 | 94.5% | 1.47 | — |
| 2023-24 | Curry | D3 | 21 | — | — | 94.9% | 1.59 | — |
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 |
|---|---|---|---|---|---|---|
| Carson Dorfman | NAHL | 90.1% | 84.7% | RPI | 100.0% | — |
| Rorke Applebee | BCHL | 90.2% | 83.3% | Lake Superior State | 90.7% | 3.00 |
| John Hawthorne | BCHL | 91.8% | 83.9% | Northern Michigan | 88.2% | 3.10 |
| Ben Charette | AJHL | 92.5% | 82.7% | Harvard | 90.9% | 2.77 |
| Matthew DellaRusso | NAHL | 89.6% | 84.3% | Northeastern | 66.7% | 21.30 |
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 |
|---|---|---|---|---|---|---|---|
| Connor Graham | MJHL | 89.9% | 84.3% | Alvernia | D3 | 93.2% | 2.19 |
| Kyle Curtin | OJHL | 90.2% | 84.4% | Elmira | D3 | 91.9% | 2.66 |
| Jeff Zero | NA3HL | 95.0% | 83.7% | Elmira | D3 | 100.0% | — |
| Matthew O'Donnell | NAHL | 88.6% | 84.8% | Aurora | D3 | 91.0% | 2.97 |
| Conor Sullivan | NAHL | 88.2% | 85.2% | Middlebury | D3 | 92.1% | 2.46 |
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.