icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | — | NAHL | 48 | 12 | 30 | 89.2% | 4.16 | 0 | 0.9843 | 83.4% |
| 2020-21 | — | NAHL | 31 | 12 | 12 | 92.1% | 2.48 | 2 | 0.9843 | 90.6% |
| 2019-20 | — | NCDC | 22 | 13 | 5 | 93.0% | 2.43 | 4 | 0.9400 | 87.4% |
| 2018-19 | — | NCDC | 5 | 3 | 2 | 91.7% | 3.20 | 1 | 0.9400 | 90.9% |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2023-24 | Brown | D1 | — | — | — | — | — | — |
| 2022-23 | Brown | D1 | 7 | 1 | 6 | 86.8% | 4.19 | 0 |
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 |
|---|---|---|---|---|---|---|
| Luke Lush | AJHL | 91.9% | 83.0% | Sacred Heart | 91.5% | 2.11 |
| Daniel Hauser | WHL | 91.3% | 83.7% | Wisconsin | 90.0% | 2.49 |
| Thomas Heaney | NAHL | 90.0% | 84.2% | UConn | 86.7% | 4.39 |
| Ryan Snowden | USHL | 89.8% | 82.7% | Ohio State | 90.5% | 2.52 |
| Lukas Renaud | AJHL | 92.4% | 83.4% | Long Island Univ. | 89.7% | 2.57 |
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 |
|---|---|---|---|---|---|---|---|
| Nikolas Trakakis | MJHL | 87.9% | 83.1% | Chatham | D3 | 93.4% | 2.45 |
| 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 |
| Anthony Bonaldi | USPHL-Premier | 90.6% | 82.7% | Nichols | D3 | 81.8% | 7.78 |
| 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.