icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | — | NCDC | 26 | 13 | 10 | 92.2% | 2.71 | 1 | 0.9400 | 83.7% |
| 2021-22 | — | EHL | 17 | 11 | 6 | 92.2% | 2.50 | 2 | 0.9400 | 87.9% |
| 2020-21 | — | EHL | 2 | 1 | 1 | 92.6% | 2.48 | 0 | 0.9400 | 87.0% |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2025-26 | Albertus Magnus | D3 | 6 | — | — | 83.3% | 4.00 | — |
| 2024-25 | Suffolk | D3 | — | — | — | — | — | — |
| 2023-24 | Suffolk | D3 | 10 | — | — | 84.7% | 4.78 | 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 |
|---|---|---|---|---|---|---|
| Chad Veltri | USHL | 90.2% | 83.9% | Niagara | 93.1% | 2.10 |
| Jan Spunar | USHL | 90.7% | 84.1% | North Dakota | 91.9% | 1.91 |
| Yan Shostak | USHL | 91.1% | 84.5% | St. Cloud State | 89.7% | 3.08 |
| 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 |
|---|---|---|---|---|---|---|---|
| Gabe Rosek | NOJHL | 91.3% | 83.7% | Concordia | D3 | 90.2% | 4.56 |
| Liam Gross | USPHL-Premier | 90.2% | 83.4% | Buffalo State | D3 | 85.7% | 5.75 |
| Owen Swanbon | USPHL-Premier | 90.4% | 83.4% | Framingham State | D3 | 83.3% | 8.53 |
| Jeffrey Reda | USPHL-Premier | 90.6% | 83.7% | Franklin Pierce | D2 | 85.9% | 5.85 |
| Nathan Loisel | CCHL | 88.3% | 83.8% | Southern New Hampshire | D2 | 92.5% | 2.61 |
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.