icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | — | USPHL-Premier | 11 | 7 | 2 | 90.2% | 2.68 | 2 | 0.9400 | 81.0% |
| 2022-23 | — | NAHL | — | — | — | — | — | — | 0.9843 | — |
| 2021-22 | — | USPHL-Premier | 1 | 0 | 0 | 94.1% | 0.92 | 0 | 0.9400 | 87.7% |
| 2021-22 | — | NAHL | 1 | 0 | 1 | 83.3% | 3.64 | 0 | 0.9843 | 82.0% |
| 2020-21 | — | NAHL | 2 | 2 | 0 | 90.9% | 3.00 | 0 | 0.9843 | 89.5% |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2025-26 | Buffalo State | D3 | 2 | — | — | 87.2% | 5.64 | 0 |
| 2024-25 | Buffalo State | D3 | 1 | 0 | 0 | 100.0% | — | — |
| 2023-24 | Buffalo State | D3 | 3 | 0 | 1 | 85.7% | 5.75 | — |
| 2022-23 | Buffalo State | D3 | 5 | 0 | 3 | 86.9% | 5.47 | — |
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 |
|---|---|---|---|---|---|---|
| Raythan Robbins | USHL | 88.6% | 82.2% | Bemidji State | 80.0% | 5.38 |
| Aaron Randazzo | USHL | 88.8% | 82.5% | Air Force | 82.4% | 5.23 |
| Alec Calvaruso | USHL | 89.0% | 83.1% | RPI | 86.9% | 3.91 |
| Ben Bonisteel | OJHL | 92.6% | 84.6% | Canisius | 89.3% | 3.10 |
| Jack Williams | USHL | 90.8% | 84.5% | Notre Dame | 88.9% | 2.90 |
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 |
|---|---|---|---|---|---|---|---|
| Will Pinney | NA3HL | 90.3% | 81.2% | Gustavus Adolphus | D3 | 85.8% | 4.05 |
| Karl Zodda | NA3HL | 92.0% | 82.6% | Chatham | D3 | 86.8% | 4.66 |
| Gabe Rosek | NOJHL | 91.3% | 83.7% | Concordia | D3 | 90.2% | 4.56 |
| Nathan Loisel | CCHL | 88.3% | 83.8% | Southern New Hampshire | D2 | 92.5% | 2.61 |
| John Simon | NA3HL | 92.1% | 83.2% | Post | D2 | 91.6% | 3.15 |
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.