icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2024-25 | Calgary Hitmen | WHL | 47 | 28 | 13 | 91.3% | 2.55 | 5 | 1.0047 | 83.7% |
| 2023-24 | Wenatchee Wild | WHL | 39 | 17 | 16 | 90.0% | 3.50 | 2 | 1.0047 | 86.1% |
| 2022-23 | — | WHL | 42 | 37 | 4 | 91.7% | 2.28 | 2 | 1.0047 | 91.1% |
| 2021-22 | — | WHL | 40 | 34 | 3 | 91.4% | 2.00 | 8 | 1.0047 | 94.0% |
| 2020-21 | — | WHL | 8 | 7 | 0 | 89.8% | 3.10 | 0 | 1.0047 | 90.2% |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2025-26 | Wisconsin | D1 | 33 | 21 | 8 | 90.0% | 2.49 | 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 |
|---|---|---|---|---|---|---|
| Thomas Heaney | NAHL | 90.0% | 84.2% | UConn | 86.7% | 4.39 |
| Jacob Zacharewicz | NAHL | 89.2% | 83.4% | Brown | 86.8% | 4.19 |
| Lukas Renaud | AJHL | 92.4% | 83.4% | Long Island Univ. | 89.7% | 2.57 |
| Cullen DeYoung | NAHL | 91.0% | 85.0% | Sacred Heart | 94.3% | 1.73 |
| Luke Lush | AJHL | 91.9% | 83.0% | 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 |
|---|---|---|---|---|---|---|---|
| Pierce Diamond | SJHL | 91.5% | 84.2% | Albertus Magnus | D3 | 89.4% | 3.82 |
| Nic Tallarico | NOJHL | 92.1% | 83.6% | Adrian | D3 | 90.1% | 2.46 |
| Blake Bjella | USPHL-Premier | 91.5% | 83.1% | Worcester State | D3 | 87.0% | 3.54 |
| Josh Nadler | AJHL | 89.5% | 84.2% | Hamilton | D3 | 68.8% | 12.03 |
| Graham Burke | NAHL | 86.2% | 82.8% | Hobart | D3 | 95.1% | 1.00 |
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.