icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | — | BCHL | 22 | 11 | 8 | 90.2% | 2.83 | 1 | 0.9990 | 90.1% |
| 2024-25 | — | NAHL | 30 | 7 | 17 | 90.0% | 3.49 | 2 | 0.9843 | 92.2% |
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 |
|---|---|---|---|---|---|---|
| Aksel Reid | NAHL | 91.1% | 90.1% | Union | 80.0% | 2.77 |
| Connor McDonough | NAHL | 90.9% | 90.1% | Ferris State | 25.0% | 26.21 |
| Zack Rose | BCHL | 90.6% | 89.2% | Bowling Green | 90.5% | 2.20 |
| Roan Clarke | BCHL | 90.8% | 89.9% | Dartmouth | 86.0% | 3.93 |
| Jared Moe | USHL | 90.7% | 88.1% | Minnesota | 91.5% | 2.46 |
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 |
|---|---|---|---|---|---|---|---|
| Ryan Kenny | USPHL-Premier | 93.5% | 89.9% | Stevenson | D3 | 89.6% | 2.95 |
| Ryan Nolan | NAHL | 88.9% | 90.6% | St. Olaf | D3 | 93.5% | 2.31 |
| Brody Haynes | NCDC | 92.5% | 92.3% | Elmira | D3 | 94.8% | 1.22 |
| Marko Belak | MJHL | 90.3% | 91.0% | Gustavus Adolphus | D3 | 87.8% | 3.08 |
| Primo Baldassarre | NCDC | 92.8% | 92.7% | Connecticut College | D3 | 87.1% | 4.43 |
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.