icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | — | MJHL | 35 | 25 | 9 | 92.4% | 2.22 | 5 | 0.9700 | 81.9% |
| 2022-23 | — | NAHL | 1 | 0 | 1 | 85.7% | 3.00 | 0 | 0.9843 | 78.7% |
| 2021-22 | — | NAHL | 28 | 15 | 10 | 89.0% | 3.31 | 0 | 0.9843 | 87.8% |
| 2020-21 | — | NAHL | 10 | 7 | 2 | 93.1% | 1.70 | 2 | 0.9843 | 91.6% |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2025-26 | Air Force | D1 | 34 | 17 | 12 | 90.7% | 2.47 | 4 |
| 2024-25 | Air Force | D1 | — | — | — | — | — | — |
| 2023-24 | Air Force | 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 |
|---|---|---|---|---|---|---|
| Adam Manji | BCHL | 90.4% | 82.2% | American International | 92.1% | 2.70 |
| Brendan Holahan | NAHL | 89.7% | 82.1% | Union | 85.7% | 4.48 |
| Michael Sochan | BCHL | 90.6% | 82.1% | Robert Morris | 100.0% | — |
| Cooper Black | BCHL | 92.4% | 82.9% | Dartmouth | 89.9% | 3.07 |
| Owen Say | BCHL | 92.3% | 82.7% | Mercyhurst | 90.3% | 3.39 |
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 |
|---|---|---|---|---|---|---|---|
| Dylan Grover | OJHL | 90.4% | 82.2% | St. John Fisher | D3 | 91.3% | 2.94 |
| Freddy Soderberg | USPHL-Premier | 93.1% | 82.6% | Fitchburg State | D3 | 93.0% | 2.48 |
| Dylan Kruss | NCDC | 88.5% | 81.6% | Lake Forest | D3 | 91.8% | 2.84 |
| Kolby Thornton | AJHL | 91.3% | 82.8% | Aurora | D3 | 91.5% | 3.36 |
| John Simon | NA3HL | 92.1% | 81.0% | Post | D2 | 91.6% | 3.15 |
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.