icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
Winnipeg Jets
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2018-19 | — | BCHL | 47 | 32 | 8 | 91.4% | 1.92 | 5 | 0.9990 | 87.3% |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2023-24 | Miami | D1 | 23 | 4 | 4 | 89.4% | 3.24 | 0 |
| 2022-23 | Miami | D1 | 9 | 0 | 5 | 90.0% | 3.60 | 0 |
| 2021-22 | Miami | D1 | 7 | 1 | 4 | 88.7% | 4.45 | 0 |
| 2020-21 | UMass Lowell | D1 | 3 | 0 | 1 | 85.5% | 4.85 | 0 |
| 2019-20 | UMass Lowell | D1 | 3 | 0 | 2 | 86.9% | 3.85 | 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 |
|---|---|---|---|---|---|---|
| Oliver Auyeung-Ashton | BCHL | 90.9% | 87.4% | Northern Michigan | 93.0% | 2.67 |
| Ryan Manzella | NAHL | 90.4% | 87.7% | Michigan Tech | 90.6% | 2.48 |
| Bryant Marks | NAHL | 89.7% | 87.0% | Alaska Anchorage | 94.1% | 1.33 |
| William Håkansson | NAHL | 91.2% | 88.3% | Lake Superior State | 83.3% | 4.83 |
| Joshua Kotai | SJHL | 93.5% | 88.0% | Augustana | 90.4% | 3.32 |
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 |
|---|---|---|---|---|---|---|---|
| Chad Lowe | USPHL-Premier | 93.5% | 86.9% | SUNY Morrisville | D3 | 90.2% | 4.99 |
| Russ Decoste | USPHL-Premier | 93.1% | 87.0% | Westfield State | D3 | 93.3% | 2.38 |
| Cal Wilcox | NCDC | 89.6% | 86.7% | Suffolk | D3 | 89.1% | 4.18 |
| Jackson Fellner | SJHL | 89.9% | 85.7% | Alvernia | D3 | 92.4% | 2.68 |
| Andrew Doran | NA3HL | 93.4% | 87.1% | Utica | D3 | 100.0% | — |
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.