icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | London Knights | OHL | 38 | 24 | 8 | 91.6% | 2.37 | 3 | 1.0008 | 87.2% |
| 2024-25 | — | BCHL | 29 | 19 | 6 | 89.3% | 2.87 | 1 | 0.9990 | 90.1% |
| 2023-24 | — | OJHL | 30 | 17 | 9 | 92.8% | 2.23 | 4 | 0.9700 | 93.4% |
| 2022-23 | — | USHL | 3 | 0 | 1 | 82.2% | 6.49 | 0 | 0.9987 | 87.4% |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2026-27 | Dartmouth | 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 |
|---|---|---|---|---|---|---|
| Sam Scopa | NAHL | 89.7% | 86.9% | Quinnipiac | 100.0% | — |
| Stephen Peck | USHL | 90.9% | 86.4% | Michigan | 91.1% | 2.61 |
| Joey Lamoreaux | USHL | 89.7% | 85.6% | St. Cloud State | 89.3% | 3.25 |
| Jake Barczewski | USHL | 90.4% | 86.1% | Canisius | 90.5% | 2.92 |
| Jackson Unger | WHL | 89.9% | 85.7% | Colorado College | 91.1% | 2.53 |
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 |
|---|---|---|---|---|---|---|---|
| Maxim Zinchenko | USPHL-Premier | 91.8% | 87.0% | Johnson & Wales | D3 | 90.8% | 3.68 |
| Anthony Beaulieu | EHL | 89.2% | 87.7% | New England College | D3 | 93.0% | 2.37 |
| Nolan Mahaffey | NCDC | 87.4% | 86.2% | Lawrence | D3 | 90.5% | 3.39 |
| Nick Anderson | USPHL-Premier | 92.6% | 87.8% | Nichols | D3 | 87.4% | 4.17 |
| Gustave Bylin | AJHL | 90.4% | 88.1% | Tufts | D3 | 89.8% | 3.01 |
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.