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 | 14 | 17 | 90.9% | 2.72 | 2 | 0.9843 | 85.4% |
| 2021-22 | — | OJHL | 33 | 25 | 5 | 92.9% | 2.02 | 4 | 0.9700 | 89.0% |
| 2020-21 | — | OJHL | — | — | — | — | — | — | 0.9700 | — |
| 2019-20 | — | OJHL | 17 | 6 | 6 | 89.2% | 3.42 | 0 | 0.9700 | 86.5% |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2025-26 | Salve Regina | D3 | 19 | — | — | 94.0% | 1.55 | 4 |
| 2024-25 | Salve Regina | D3 | 10 | 5 | 2 | 92.3% | 2.38 | 1 |
| 2023-24 | Salve Regina | D3 | 5 | — | — | 92.9% | 2.18 | 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 |
|---|---|---|---|---|---|---|
| Brandon Perrone | NAHL | 91.2% | 85.4% | Alaska Anchorage | 87.2% | 3.66 |
| Matthew DellaRusso | NAHL | 89.6% | 84.3% | Northeastern | 66.7% | 21.30 |
| Carson Dorfman | NAHL | 90.1% | 84.7% | RPI | 100.0% | — |
| Croix Kochendorfer | NAHL | 92.0% | 86.6% | Robert Morris | 90.6% | 2.95 |
| Klayton Knapp | NAHL | 92.1% | 86.5% | Minnesota Duluth | 90.7% | 2.67 |
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 | AJHL | 91.8% | 85.2% | Alvernia | D3 | 93.2% | 2.19 |
| Logan Bateman | OJHL | 91.5% | 85.1% | Elmira | D3 | 91.5% | 2.53 |
| Brady Quackenbush | EHL | 88.2% | 85.2% | Salve Regina | D3 | 88.5% | 2.01 |
| Logan Bateman | CCHL | 91.8% | 84.9% | Elmira | D3 | 91.5% | 2.53 |
| Korbinian Lutz | EHL | 91.0% | 86.4% | Nichols | D3 | 88.8% | 4.09 |
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.