icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | — | USPHL-Premier | 21 | 11 | 9 | 91.6% | 2.99 | 1 | 0.9400 | 77.7% |
| 2020-21 | — | USPHL-Premier | 22 | 19 | 1 | 94.8% | 1.53 | 4 | 0.9400 | 89.1% |
| 2019-20 | — | NCDC | 6 | 0 | 5 | 84.8% | 7.63 | 0 | 0.9400 | 79.7% |
| 2019-20 | — | USPHL-Premier | 30 | 4 | 23 | 86.8% | 5.65 | 0 | 0.9400 | 81.6% |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2023-24 | Salem State | D3 | 2 | 0 | 1 | 85.7% | 5.72 | — |
| 2022-23 | Salem State | D3 | 2 | 1 | 0 | 88.9% | 3.95 | — |
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 |
|---|---|---|---|---|---|---|
| Alexander Tracy | USHL | 89.6% | 77.2% | Minnesota | 87.9% | 2.24 |
| Gavin Moffatt | USHL | 89.3% | 76.3% | Western Michigan | — | — |
| Charles-Edward Gravel | QMJHL | 91.4% | 77.9% | Mercyhurst | 90.7% | 3.22 |
| Ryan Keyes | NCDC | 92.6% | 79.7% | Merrimack | 92.0% | 2.22 |
| Aaron Matthews | NCDC | 90.7% | 77.9% | Providence | — | — |
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 |
| Logan Palmer | USPHL-Premier | 92.1% | 80.5% | Western New England | D3 | 90.9% | 3.11 |
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.