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 | 41 | 19 | 16 | 91.3% | 2.65 | 4 | 0.9980 | 77.9% |
| 2021-22 | — | Allsvenskan | 1 | 0 | 0 | 100.0% | — | 0 | 1.0100 | 97.0% |
| 2021-22 | — | SHL | — | — | — | — | — | — | 1.0100 | — |
| 2021-22 | — | SuperElit | 34 | 20 | 13 | 90.0% | 3.05 | 3 | 0.9600 | 79.0% |
| 2021-22 | — | SHL-J20 | 34 | 20 | 13 | 90.0% | 3.05 | 3 | 0.9600 | 79.0% |
| 2020-21 | — | SHL | — | — | — | — | — | — | 1.0100 | — |
| 2020-21 | — | SuperElit | 4 | 3 | 1 | 90.0% | 2.98 | 0 | 0.9600 | 86.4% |
| 2020-21 | — | SHL-J20 | 4 | 3 | 1 | 90.0% | 2.98 | 0 | 0.9600 | 86.4% |
| 2019-20 | — | SuperElit | 1 | 0 | 1 | 80.0% | 6.00 | 0 | 0.9600 | 76.8% |
| 2019-20 | — | SHL-J20 | 1 | 0 | 1 | 80.0% | 6.00 | 0 | 0.9600 | 76.8% |
| 2018-19 | — | SuperElit | — | — | — | — | — | — | 0.9600 | — |
| 2018-19 | — | SHL-J20 | — | — | — | — | — | — | 0.9600 | — |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2025-26 | Merrimack | D1 | 39 | 21 | 16 | 92.0% | 2.55 | 1 |
| 2024-25 | Merrimack | D1 | 24 | 8 | 13 | 90.9% | 2.90 | 1 |
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 |
|---|---|---|---|---|---|---|
| Charles-Edward Gravel | QMJHL | 91.4% | 77.9% | Mercyhurst | 90.7% | 3.22 |
| Aaron Matthews | NCDC | 90.7% | 77.9% | Providence | — | — |
| Ryan Manzella | USHL | 90.4% | 76.7% | Michigan Tech | 89.5% | 3.17 |
| Gavin Moffatt | USHL | 89.3% | 76.3% | Western Michigan | — | — |
| Alexander Tracy | USHL | 89.6% | 77.2% | Minnesota | 87.9% | 2.24 |
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 |
|---|---|---|---|---|---|---|---|
| Nolan Hildebrand | BCHL | 89.3% | 77.6% | Babson | D3 | 87.8% | 3.82 |
| Nolan Hildebrand | AJHL | 87.4% | 77.5% | Babson | D3 | 87.8% | 3.82 |
| Dolan Gilbert | NA3HL | 91.0% | 78.2% | Concordia | D3 | 81.0% | 9.00 |
| Bodee Weiss | BCHL | 87.9% | 76.6% | Aurora | D3 | 87.9% | 2.93 |
| Cameron Hrdlicka | SJHL | 89.6% | 79.6% | Concordia | D3 | 89.0% | 3.97 |
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.