icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2023-24 | — | AJHL | 13 | 7 | 3 | 91.1% | 2.47 | 1 | 0.9700 | 78.3% |
| 2022-23 | — | AJHL | 19 | 10 | 7 | 87.8% | 3.87 | 2 | 0.9700 | 81.1% |
| 2021-22 | — | AJHL | 33 | 19 | 9 | 91.8% | 2.75 | 1 | 0.9700 | 91.0% |
| 2020-21 | — | AJHL | 4 | 1 | 3 | 92.1% | 2.78 | 0 | 0.9700 | 89.3% |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2023-24 | Albertus Magnus | D3 | 4 | 2 | 1 | 89.3% | 2.76 | — |
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 |
| Cole Plowman | MJHL | 93.4% | 80.7% | Alaska Fairbanks | 100.0% | — |
| Luke Lush | AJHL | 91.9% | 77.5% | Sacred Heart | 91.5% | 2.11 |
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 |
|---|---|---|---|---|---|---|---|
| Cameron Hrdlicka | SJHL | 89.6% | 79.6% | Concordia | D3 | 89.0% | 3.97 |
| Anthony Bonaldi | USPHL-Premier | 90.6% | 78.2% | Nichols | D3 | 81.8% | 7.78 |
| Paul Knapik | USPHL-Premier | 90.5% | 77.5% | Roger Williams | D3 | — | — |
| Nolan Hildebrand | BCHL | 89.3% | 77.6% | Babson | D3 | 87.8% | 3.82 |
| Bodee Weiss | BCHL | 87.9% | 76.6% | Aurora | D3 | 87.9% | 2.93 |
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.