icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2024-25 | Chicago Steel | USHL | 35 | 12 | 18 | 90.3% | 3.49 | 0 | 0.9980 | 88.2% |
| 2023-24 | — | NTDP-U18 | 33 | 15 | 9 | 86.4% | 3.71 | 0 | 0.9200 | 75.0% |
| 2023-24 | USNTDP Juniors | USHL | 14 | 7 | 4 | 85.4% | 4.13 | 0 | 0.9980 | 89.5% |
| 2022-23 | — | NTDP-U18 | 32 | 20 | 12 | 88.5% | 3.40 | 0 | 0.9200 | 82.6% |
| 2022-23 | — | USHL | 23 | 11 | 7 | 89.0% | 3.51 | 0 | 0.9980 | 97.0% |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2025-26 | Providence | D1 | 19 | 13 | 5 | 92.2% | 2.05 | 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 |
|---|---|---|---|---|---|---|
| Jackson Irving | USHL | 88.8% | 87.2% | UMass | 100.0% | — |
| Blake Pietila | USHL | 91.2% | 89.7% | Michigan Tech | 86.8% | 3.24 |
| Aku Koskenvuo | SM-Liiga-Jr | 89.7% | 88.3% | Harvard | 87.5% | 3.56 |
| Daniel Moor | USHL | 87.9% | 85.9% | Princeton | 85.2% | 2.83 |
| Emmett Croteau | USHL | 91.7% | 89.0% | Clarkson | 83.5% | 3.53 |
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 |
|---|---|---|---|---|---|---|---|
| Brody Haynes | NCDC | 92.5% | 92.3% | Elmira | D3 | 94.8% | 1.22 |
| Nevin Tardif | USPHL-Premier | 90.4% | 88.0% | Worcester State | D3 | 89.8% | 3.54 |
| Cooper Rautenstrauch | NCDC | 90.6% | 93.8% | Colby | D3 | 93.4% | 2.08 |
| Cooper Rautenstrauch | NAHL | 88.9% | 94.0% | Colby | D3 | 93.4% | 2.08 |
| Zach Dosan | NA3HL | 92.1% | 87.8% | 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.