icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | — | USHL | 46 | 25 | 14 | 89.3% | 2.97 | 3 | 0.9980 | 80.5% |
| 2021-22 | — | NCDC | 36 | 15 | 15 | 92.4% | 2.71 | 2 | 0.9400 | 89.3% |
| 2021-22 | — | USHL | 4 | 3 | 1 | 87.8% | 2.91 | 0 | 0.9980 | 85.5% |
| 2019-20 | — | USPHL-Premier | 14 | 7 | 7 | 92.5% | 2.49 | 3 | 0.9400 | 87.0% |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2025-26 | Ohio State | D1 | 26 | 10 | 13 | 88.5% | 3.35 | 1 |
| 2024-25 | Ohio State | D1 | 17 | 12 | 4 | 91.5% | 2.28 | 2 |
| 2023-24 | Ohio State | D1 | 14 | 3 | 8 | 91.1% | 2.98 | 0 |
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 |
|---|---|---|---|---|---|---|
| Collin MacKenzie | OHL | 88.4% | 79.5% | RIT | 81.5% | 3.90 |
| Christian Manz | USHL | 88.0% | 79.9% | Augustana | 89.4% | 2.84 |
| Josh Fleming | QMJHL | 90.8% | 81.4% | Penn State | 92.4% | 2.61 |
| Jackson Unger | WHL | 89.9% | 81.5% | Colorado College | 91.1% | 2.53 |
| Julian Molinaro | AJHL | 91.6% | 83.1% | Northern Michigan | 95.7% | 1.81 |
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 |
|---|---|---|---|---|---|---|---|
| Nikolas Charles | USPHL-Premier | 89.1% | 80.4% | Roger Williams | D3 | 85.4% | 6.79 |
| Sean Guerin | NOJHL | 90.2% | 81.9% | Southern New Hampshire | D2 | 90.7% | 3.28 |
| Owen Carlson | NA3HL | 92.1% | 83.0% | Lawrence | D3 | 90.2% | 3.41 |
| Jeb Lindy | USPHL-Premier | 89.3% | 81.3% | Arcadia | D3 | 89.6% | 4.06 |
| Dylan Dewatcher | OJHL | 86.3% | 81.7% | Western Connecticut | D3 | 85.8% | 5.91 |
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.