icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2024-25 | — | BCHL | 21 | 18 | 3 | 94.3% | 1.37 | 6 | 0.9990 | 93.5% |
| 2024-25 | Victoria Royals | WHL | 15 | 10 | 4 | 90.9% | 2.69 | 0 | 1.0047 | 86.6% |
| 2023-24 | — | AJHL | 30 | 26 | 3 | 90.9% | 1.98 | 7 | 0.9700 | 93.4% |
| 2023-24 | — | BCHL | 8 | 7 | 1 | 91.9% | 2.13 | 0 | 0.9990 | 97.0% |
| 2022-23 | — | BCHL | 27 | 8 | 10 | 91.7% | 3.53 | 0 | 0.9990 | 97.0% |
| 2021-22 | — | BCHL | 24 | 0 | 16 | 89.4% | 5.24 | 0 | 0.9990 | 97.0% |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2025-26 | Denver | D1 | 21 | 15 | 0 | 95.5% | 1.25 | 3 |
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 |
|---|---|---|---|---|---|---|
| Danick Leroux | NAHL | 92.7% | 92.6% | Holy Cross | 90.6% | 2.62 |
| Petter Wickström Stumer | NAHL | 91.4% | 91.6% | Canisius | 90.4% | 3.52 |
| Nils Wallström | NAHL | 91.9% | 92.5% | American International | 92.0% | 2.27 |
| Luca Di Pasquo | BCHL | 92.2% | 91.1% | Michigan | 91.0% | 2.41 |
| Connor McDonough | NAHL | 90.9% | 90.6% | Ferris State | 25.0% | 26.21 |
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 |
| Nathan Pickett | EHL | 93.9% | 94.1% | Suffolk | D3 | 90.5% | 4.16 |
| Connor Carbo | EHL | 89.3% | 90.3% | Wentworth | D3 | 92.3% | 3.00 |
| Noel Friedman | NCDC | 95.0% | 96.8% | Chatham | D3 | 89.5% | 3.68 |
| Marko Belak | MJHL | 90.3% | 91.2% | Gustavus Adolphus | D3 | 87.8% | 3.08 |
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.