icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2019-20 | — | EHL | 10 | 7 | 3 | 90.4% | 2.66 | 1 | 0.9400 | 85.0% |
| 2018-19 | — | EHL | 24 | 13 | 9 | 89.3% | 2.56 | 2 | 0.9400 | 86.0% |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2023-24 | Wentworth | D3 | — | — | — | — | — | — |
| 2022-23 | Wentworth | D3 | 1 | 0 | 1 | 73.3% | 12.00 | — |
| 2021-22 | Wentworth | D3 | 5 | 1 | 4 | 80.9% | 5.03 | — |
| 2020-21 | Wentworth | D3 | — | — | — | — | — | — |
| 2019-20 | Wentworth | D3 | 11 | 4 | 6 | 92.3% | 3.00 | 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 |
|---|---|---|---|---|---|---|
| Kevin Reidler | USHL | 90.2% | 85.9% | Nebraska Omaha | 92.0% | 2.74 |
| Johnny Hicks | WHL | 90.9% | 86.6% | Denver | 95.5% | 1.25 |
| Dawson Cowan | WHL | 90.5% | 86.5% | Nebraska Omaha | 90.1% | 3.21 |
| Freddie Halyk | AJHL | 91.0% | 86.7% | Denver | 88.3% | 2.91 |
| Louden Hogg | USHL | 89.4% | 86.1% | Holy Cross | 87.3% | 3.29 |
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 |
|---|---|---|---|---|---|---|---|
| Zach Dosan | NA3HL | 92.1% | 87.8% | Gustavus Adolphus | D3 | 72.5% | 6.60 |
| Michael Paterson-Jones | USPHL-Premier | 92.0% | 88.7% | Wilkes | D3 | 89.5% | 3.08 |
| Nevin Tardif | USPHL-Premier | 90.4% | 88.0% | Worcester State | D3 | 89.8% | 3.54 |
| Tyler Fromolz | NA3HL | 92.0% | 87.1% | Marian | D3 | 88.3% | 3.85 |
| Ryan Kenny | USPHL-Premier | 93.5% | 89.3% | Stevenson | D3 | 89.6% | 2.95 |
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.