icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2023-24 | Sioux City Musketeers | USHL | 20 | 11 | 5 | 88.8% | 3.09 | 0 | 0.9980 | 81.0% |
| 2021-22 | — | NTDP-U18 | 20 | 10 | 7 | 87.8% | 3.52 | 2 | 0.9200 | 77.0% |
| 2021-22 | — | USHL | 9 | 6 | 2 | 84.6% | 3.92 | 0 | 0.9980 | 89.2% |
| 2020-21 | — | NTDP-U18 | 16 | 10 | 2 | 89.0% | 3.61 | 0 | 0.9200 | 81.9% |
| 2020-21 | — | USHL | 9 | 4 | 1 | 87.8% | 4.60 | 0 | 0.9980 | 87.6% |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2025-26 | Quinnipiac | D1 | 18 | 10 | 6 | 91.2% | 2.09 | 2 |
| 2024-25 | Quinnipiac | D1 | 24 | 12 | 9 | 90.3% | 2.25 | 1 |
| 2022-23 | Boston College | 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 |
|---|---|---|---|---|---|---|
| Conor Callaghan | USHL | 88.4% | 81.0% | Princeton | 85.3% | 5.02 |
| Joey Lamoreaux | USHL | 89.7% | 82.0% | St. Cloud State | 89.3% | 3.25 |
| Troy Kobryn | USHL | 89.5% | 82.1% | Merrimack | 89.3% | 3.30 |
| Jackson Unger | WHL | 89.9% | 81.5% | Colorado College | 91.1% | 2.53 |
| Justin Robbins | USHL | 87.4% | 80.6% | Arizona State | 92.3% | 4.00 |
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 Dewatcher | OJHL | 86.3% | 81.7% | Western Connecticut | D3 | 85.8% | 5.91 |
| Brandon Shantz | NA3HL | 89.7% | 82.6% | Plymouth State | D3 | 92.1% | 3.00 |
| Clément Labillois | SJHL | 88.9% | 84.4% | Assumption | D2 | 93.6% | 2.08 |
| Nolan Mahaffey | NCDC | 87.4% | 85.4% | Lawrence | D3 | 90.5% | 3.39 |
| Maxim Zinchenko | USPHL-Premier | 91.8% | 85.4% | Johnson & Wales | D3 | 90.8% | 3.68 |
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.