icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Grant MacEwan Univ. | USports-M | 5 | 3 | 1 | 92.1% | 2.48 | 0 | 1.0100 | 94.1% |
| 2024-25 | Grant MacEwan Univ. | USports-M | 6 | 2 | 1 | 85.0% | 4.39 | 0 | 1.0100 | 90.3% |
| 2023-24 | — | AJHL | 13 | 7 | 3 | 91.1% | 2.47 | 1 | 0.9700 | 83.0% |
| 2022-23 | — | AJHL | 19 | 10 | 7 | 87.8% | 3.87 | 2 | 0.9700 | 83.0% |
| 2021-22 | — | AJHL | 33 | 19 | 9 | 91.8% | 2.75 | 1 | 0.9700 | 90.1% |
| 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 |
|---|---|---|---|---|---|---|
| Noah Giesbrecht | USports-M | 94.1% | 96.9% | Ferris State | 90.8% | 3.08 |
| Tyler Palmer | USports-M | 91.5% | 98.1% | Bowling Green | 89.9% | 2.35 |
| Matteo Drobac | USports-M | 90.4% | 97.3% | Miami | 91.3% | 2.69 |
| Max Beckford | NAHL | 94.0% | 88.0% | Bentley | 90.2% | 1.84 |
| Jack LaFontaine | BCHL | 92.3% | 85.8% | Minnesota | 91.9% | 2.55 |
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 |
|---|---|---|---|---|---|---|---|
| Brody Haynes | NCDC | 92.5% | 92.3% | Elmira | D3 | 94.8% | 1.22 |
| Artur Dzhilavyan | EHL | 92.3% | 87.4% | Keene State | D3 | 95.9% | 1.48 |
| Joey Lovullo | NAHL | 91.2% | 87.6% | Hamilton | D3 | — | — |
| Avery Sturtz | NAHL | 90.4% | 86.7% | Utica | D3 | 84.2% | 3.16 |
| Marcus Ouellet | NCDC | 92.8% | 88.1% | St. John Fisher | D3 | 87.9% | 1.86 |
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.