icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2023-24 | — | NCDC | 6 | 3 | 2 | 94.2% | 2.47 | 1 | 0.9400 | 84.3% |
| 2023-24 | — | NAHL | 2 | 1 | 0 | 89.8% | 2.88 | 0 | 0.9843 | 84.8% |
| 2022-23 | — | NCDC | 33 | 18 | 11 | 93.1% | 2.68 | 2 | 0.9400 | 90.2% |
| 2021-22 | — | NA3HL | 21 | 18 | 0 | 94.6% | 1.38 | 7 | 0.9400 | 95.3% |
| 2020-21 | — | USPHL-Premier | 20 | 9 | 9 | 91.9% | 2.85 | 0 | 0.9400 | 86.4% |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2025-26 | Nazareth | D3 | 8 | — | — | 95.5% | 1.76 | 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 |
|---|---|---|---|---|---|---|
| Matthew DellaRusso | NAHL | 89.6% | 84.3% | Northeastern | 66.7% | 21.30 |
| Brandon Perrone | NAHL | 91.2% | 85.4% | Alaska Anchorage | 87.2% | 3.66 |
| Merek Pipes | MJHL | 92.4% | 83.6% | Union | 66.7% | 15.52 |
| Carson Dorfman | NAHL | 90.1% | 84.7% | RPI | 100.0% | — |
| Callum Tung | BCHL | 91.7% | 85.8% | UConn | 93.3% | 2.01 |
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 |
|---|---|---|---|---|---|---|---|
| Aidan Richardson | USPHL-Premier | 92.3% | 83.6% | Lebanon Valley | D3 | 90.5% | 3.10 |
| Jake Horoho | USPHL-Premier | 92.0% | 83.3% | Middlebury | D3 | 89.4% | 3.02 |
| Hunter Virostek | AJHL | 90.1% | 83.5% | Albertus Magnus | D3 | 75.0% | 6.00 |
| Topher Chirico | SJHL | 90.8% | 84.6% | Wentworth | D3 | 91.6% | 3.05 |
| Kyle Curtin | OJHL | 90.2% | 84.4% | Elmira | D3 | 91.9% | 2.66 |
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.