icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2023-24 | — | EHL | 31 | 20 | 8 | 92.9% | 2.30 | 2 | 0.9400 | 85.8% |
| 2022-23 | — | USPHL-Premier | 20 | 12 | 4 | 92.2% | 2.44 | 2 | 0.9400 | 86.5% |
| 2021-22 | — | USPHL-Premier | 9 | 7 | 0 | 93.1% | 2.00 | 2 | 0.9400 | 90.5% |
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 |
|---|---|---|---|---|---|---|
| Nick Bevilacqua | NCDC | 94.8% | 86.1% | Bentley | 95.2% | 0.99 |
| Colin Winn | BCHL | 90.2% | 86.1% | St. Lawrence | 88.3% | 4.50 |
| Malachi Klassen | MJHL | 91.7% | 85.4% | Holy Cross | — | 3.04 |
| Connor Murphy | CCHL | 91.7% | 84.9% | Northeastern | 68.8% | 7.04 |
| Michael Sochan | BCHL | 90.6% | 86.1% | Robert Morris | 100.0% | — |
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 |
|---|---|---|---|---|---|---|---|
| Duncan Rolleman | USPHL-Premier | 92.5% | 86.2% | Wilkes | D3 | 90.0% | 3.84 |
| Jeff Zero | NA3HL | 95.0% | 85.9% | Elmira | D3 | 100.0% | — |
| Ben Cunneen | USPHL-Premier | 92.9% | 86.2% | Post | D2 | 89.2% | 4.30 |
| Dane Couture | NAHL | 88.1% | 86.3% | Concordia | D3 | 87.3% | 2.94 |
| Tyler Sayger | NCDC | 89.4% | 86.1% | King's | D3 | 90.5% | 4.40 |
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.