icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | — | USHL | 33 | 18 | 6 | 89.0% | 3.16 | 0 | 0.9980 | 93.2% |
| 2020-21 | — | NTDP-U18 | 35 | 20 | 9 | 87.3% | 2.97 | 1 | 0.9200 | 80.3% |
| 2020-21 | — | USHL | 16 | 8 | 6 | 84.8% | 3.49 | 0 | 0.9980 | 84.6% |
| 2019-20 | — | NTDP-U18 | 25 | 10 | 13 | 84.4% | 4.33 | 1 | 0.9200 | 77.6% |
| 2019-20 | — | USHL | 17 | 3 | 9 | 83.1% | 5.27 | 0 | 0.9980 | 82.9% |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2025-26 | North Dakota | D1 | 14 | 9 | 5 | 88.9% | 2.71 | 0 |
| 2024-25 | Arizona State | D1 | 16 | 8 | 5 | 91.9% | 2.56 | 2 |
| 2023-24 | Arizona State | D1 | 14 | 8 | 3 | 93.1% | 2.04 | 1 |
| 2022-23 | Arizona State | D1 | — | — | — | — | — | — |
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 |
|---|---|---|---|---|---|---|
| Michael Hrabal | USHL | 90.8% | 95.2% | UMass | 91.2% | 2.59 |
| Jacob Fowler | USHL | 92.1% | 95.6% | Boston College | 92.6% | 2.14 |
| Nicholas Kempf | USHL | 87.0% | 91.9% | Notre Dame | 89.5% | 3.74 |
| Mikhail Yegorov | USHL | 89.2% | 94.4% | Boston University | 92.7% | 2.15 |
| Jan Korec | USHL | 90.1% | 92.5% | Boston College | 91.8% | 1.75 |
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 |
| 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 |
| Vaughn Makar | NAHL | 90.9% | 95.6% | St. Norbert | D3 | 93.2% | 1.73 |
| Brayden Ingram | EHL | 91.2% | 94.4% | Assumption | D2 | 91.4% | 2.71 |
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.