icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Omaha Lancers | USHL | 33 | 8 | 19 | 88.8% | 4.08 | 0 | 0.9983 | 81.7% |
| 2024-25 | — | NAHL | 45 | 24 | 15 | 90.0% | 2.79 | 3 | 0.9843 | 87.7% |
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 |
|---|---|---|---|---|---|---|
| Aaron Matthews | NCDC | 90.7% | 81.4% | Providence | — | — |
| Bruno Bruveris | USHL | 89.7% | 82.4% | Miami | 86.6% | 4.15 |
| Ryan Snowden | USHL | 89.8% | 82.7% | Ohio State | 90.5% | 2.52 |
| Ryan Manzella | USHL | 90.4% | 83.1% | Michigan Tech | 89.5% | 3.17 |
| Andrew Oke | OHL | 87.6% | 80.8% | Lake Superior State | 87.9% | 3.95 |
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 |
|---|---|---|---|---|---|---|---|
| Hayden Williamson | OJHL | 85.8% | 82.1% | Arcadia | D3 | 92.0% | 3.36 |
| Paul Knapik | USPHL-Premier | 90.5% | 82.3% | Roger Williams | D3 | — | — |
| Jeffrey Dreger | MJHL | 86.4% | 82.1% | SUNY Morrisville | D3 | 84.5% | 4.37 |
| Jeffrey Dreger | MJHL | 86.4% | 82.1% | Morrisville | D3 | 84.5% | 4.37 |
| Bodee Weiss | BCHL | 87.9% | 80.7% | Aurora | D3 | 87.9% | 2.93 |
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.