icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2018-19 | — | NCDC | 13 | 4 | 7 | 89.4% | 4.02 | 0 | 0.9400 | 78.5% |
| 2018-19 | — | USPHL-Premier | 12 | 4 | 7 | 90.8% | 3.31 | 1 | 0.9400 | 79.0% |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2023-24 | King's | D3 | 13 | 3 | 8 | 89.2% | 3.89 | 0 |
| 2022-23 | King's | D3 | 11 | 4 | 5 | 92.9% | 3.08 | — |
| 2021-22 | King's | D3 | 6 | 1 | 4 | 86.0% | 5.00 | — |
| 2020-21 | King's | D3 | — | — | — | — | — | — |
| 2019-20 | King's | D3 | 11 | 1 | 9 | 90.5% | 4.40 | 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 |
|---|---|---|---|---|---|---|
| Ethan Dahlmeir | USHL | 90.0% | 79.5% | Miami | 87.0% | 4.04 |
| Patriks Berzins | USHL | 90.1% | 79.5% | Maine | 90.0% | 1.79 |
| Mathis Rousseau | QMJHL | 90.5% | 80.1% | Maine | 89.6% | 2.59 |
| Charlie Schenkel | OHL | 89.7% | 78.8% | Robert Morris | 90.9% | 2.80 |
| Kyle Chauvette | USHL | 89.2% | 79.5% | Union | 90.5% | 2.87 |
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 |
|---|---|---|---|---|---|---|---|
| Alexander Timmons | USPHL-Premier | 90.5% | 81.5% | Framingham State | D3 | 84.9% | 5.20 |
| Joshua Bordeaux | USPHL-Premier | 85.1% | 76.2% | Fitchburg State | D3 | 100.0% | — |
| Kannon Flageolle | NOJHL | 91.3% | 81.7% | Suffolk | D3 | 89.7% | 3.99 |
| Tyler Roy | USPHL-Premier | 91.1% | 81.8% | Neumann | D3 | 87.2% | 3.68 |
| Will Pinney | NA3HL | 90.3% | 78.8% | Gustavus Adolphus | D3 | 85.8% | 4.05 |
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.