icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2018-19 | — | MJHL | 31 | 20 | 8 | 92.4% | 2.45 | 4 | 0.9700 | 83.6% |
| 2018-19 | — | SJHL | 5 | 1 | 3 | 90.6% | 3.66 | 0 | 0.9700 | 83.4% |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2022-23 | Union | D1 | 2 | 0 | 0 | 100.0% | — | 0 |
| 2021-22 | Union | D1 | — | — | — | — | — | — |
| 2020-21 | Union | D1 | — | — | — | — | — | — |
| 2019-20 | Union | D1 | 1 | 0 | 0 | 66.7% | 15.52 | 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 |
| Julian Molinaro | AJHL | 91.6% | 83.1% | Northern Michigan | 95.7% | 1.81 |
| Josh Fleming | QMJHL | 90.8% | 81.4% | Penn State | 92.4% | 2.61 |
| Brandon Perrone | NAHL | 91.2% | 85.4% | Alaska Anchorage | 87.2% | 3.66 |
| 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 |
|---|---|---|---|---|---|---|---|
| Hunter Virostek | AJHL | 90.1% | 83.5% | Albertus Magnus | D3 | 75.0% | 6.00 |
| 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 |
| Topher Chirico | SJHL | 90.8% | 84.6% | Wentworth | D3 | 91.6% | 3.05 |
| Jack McGovern | CCHL | 90.2% | 83.3% | Wentworth | D3 | 90.2% | 3.16 |
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.