icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2018-19 | — | BCHL | 46 | 17 | 25 | 91.8% | 2.95 | 3 | 0.9990 | 83.9% |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2022-23 | Canisius | D1 | 13 | 4 | 4 | 91.2% | 2.66 | 1 |
| 2021-22 | Canisius | D1 | 10 | 3 | 1 | 93.5% | 2.32 | 0 |
| 2020-21 | Northern Michigan | D1 | 4 | 0 | 1 | 87.2% | 4.59 | 0 |
| 2019-20 | Northern Michigan | D1 | 17 | 5 | 5 | 88.2% | 3.10 | 1 |
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 |
|---|---|---|---|---|---|---|
| Rorke Applebee | BCHL | 90.2% | 83.3% | Lake Superior State | 90.7% | 3.00 |
| Gergely Orosz | NAHL | 91.9% | 85.4% | Alaska Anchorage | 91.5% | 2.75 |
| Nick Bevilacqua | NCDC | 94.8% | 83.4% | Bentley | 95.2% | 0.99 |
| Malachi Klassen | MJHL | 91.7% | 82.2% | Holy Cross | — | 3.04 |
| Ben Charette | AJHL | 92.5% | 82.7% | Harvard | 90.9% | 2.77 |
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 |
|---|---|---|---|---|---|---|---|
| Jeff Zero | NA3HL | 95.0% | 83.7% | Elmira | D3 | 100.0% | — |
| Duncan Rolleman | USPHL-Premier | 92.5% | 83.2% | Wilkes | D3 | 90.0% | 3.84 |
| Tyler Sayger | NCDC | 89.4% | 83.4% | King's | D3 | 90.5% | 4.40 |
| Matthew O'Donnell | NAHL | 88.6% | 84.8% | Aurora | D3 | 91.0% | 2.97 |
| Cameron Smith | OJHL | 91.4% | 84.0% | Curry | D3 | 87.0% | 2.11 |
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.