icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2026-27 | Lincoln Stars | USHL | 3 | 1 | 2 | 91.6% | 2.35 | 1 | 0.9987 | 91.5% |
| 2025-26 | Lincoln Stars | USHL | 42 | 19 | 15 | 90.2% | 2.90 | 3 | 0.9987 | 88.9% |
| 2024-25 | Lincoln Stars | USHL | 25 | 15 | 3 | 89.6% | 2.77 | 3 | 0.9987 | 91.5% |
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 |
|---|---|---|---|---|---|---|
| Quentin Miller | BCHL | 92.3% | 89.4% | Denver | 91.6% | 2.39 |
| Carter McPhail | NAHL | 93.1% | 89.6% | Ferris State | 88.6% | 3.74 |
| John Roberts | NAHL | 92.5% | 89.0% | Northern Michigan | 100.0% | — |
| Max Lacroix | NAHL | 91.4% | 88.4% | Boston University | 87.2% | 3.59 |
| Ethan David | BCHL | 90.9% | 88.0% | RIT | 90.9% | 2.68 |
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 |
|---|---|---|---|---|---|---|---|
| Charles Watson | EHL | 93.2% | 91.4% | Castleton | D3 | 89.7% | 3.70 |
| Brody Haynes | NCDC | 92.5% | 92.3% | Elmira | D3 | 94.8% | 1.22 |
| Isak Saldjoughi | EHL | 92.4% | 90.7% | Framingham State | D3 | 92.0% | 3.33 |
| Philippe De Champlain | EHL | 93.7% | 91.6% | Concordia | D3 | 88.9% | 3.91 |
| Jacob Stern | NCDC | 91.9% | 90.5% | Alvernia | D3 | 88.8% | 3.50 |
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.