icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2026-27 | Dubuque Fighting Saints | USHL | 3 | 1 | 2 | 84.4% | 4.10 | 0 | 0.9987 | 84.3% |
| 2025-26 | U.S. National U18 Team | NTDP-U18 | 36 | 15 | 18 | 88.8% | 3.28 | 3 | 0.9200 | 79.1% |
| 2025-26 | USNTDP Juniors | USHL | 11 | 5 | 4 | 89.9% | 2.63 | 1 | 0.9987 | 92.2% |
| 2024-25 | U.S. National U17 Team | NTDP-U18 | 32 | 12 | 18 | 85.2% | 4.96 | 0 | 0.9200 | 79.1% |
| 2024-25 | USNTDP Juniors | USHL | 22 | 2 | 15 | 83.3% | 6.15 | 0 | 0.9987 | 88.4% |
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 |
|---|---|---|---|---|---|---|
| Paxton Geisel | USHL | 86.5% | 85.5% | Denver | 85.7% | 4.41 |
| Michael Chambre | USHL | 87.4% | 86.3% | Mercyhurst | 89.4% | 4.34 |
| Martin Holtet Lundberg | SHL-J20 | 90.3% | 85.7% | Ferris State | 83.6% | 5.17 |
| Martin Holtet Lundberg | SuperElit | 90.3% | 85.7% | Ferris State | 83.6% | 5.17 |
| Daniel Moor | USHL | 87.9% | 86.8% | Princeton | 85.2% | 2.83 |
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 |
|---|---|---|---|---|---|---|---|
| Nevin Tardif | USPHL-Premier | 90.4% | 87.8% | Worcester State | D3 | 89.8% | 3.54 |
| Brody Haynes | NCDC | 92.5% | 92.3% | Elmira | D3 | 94.8% | 1.22 |
| Cooper Rautenstrauch | NCDC | 90.6% | 92.2% | Colby | D3 | 93.4% | 2.08 |
| Cooper Rautenstrauch | NAHL | 88.9% | 92.2% | Colby | D3 | 93.4% | 2.08 |
| Zach Dosan | NA3HL | 92.1% | 86.7% | Gustavus Adolphus | D3 | 72.5% | 6.60 |
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.