icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
Ottawa Senators
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2023-24 | Dubuque Fighting Saints | USHL | 39 | 27 | 5 | 90.2% | 2.86 | 3 | 0.9980 | 85.9% |
| 2022-23 | — | Allsvenskan | — | — | — | — | — | — | 1.0100 | — |
| 2022-23 | — | SHL-J20 | 32 | 14 | 16 | 91.1% | 2.89 | 0 | 0.9600 | 88.9% |
| 2021-22 | — | Allsvenskan | — | — | — | — | — | — | 1.0100 | — |
| 2021-22 | — | SuperElit | 3 | 1 | 1 | 84.7% | 4.33 | 0 | 0.9600 | 88.1% |
| 2021-22 | — | SHL-J20 | 3 | 1 | 1 | 84.7% | 4.33 | 0 | 0.9600 | 88.1% |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2025-26 | Penn State | D1 | 18 | 11 | 7 | 90.1% | 3.31 | 0 |
| 2024-25 | Nebraska Omaha | D1 | 8 | 4 | 1 | 92.0% | 2.74 | 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 |
|---|---|---|---|---|---|---|
| Johnny Hicks | WHL | 90.9% | 86.6% | Denver | 95.5% | 1.25 |
| Freddie Halyk | AJHL | 91.0% | 86.7% | Denver | 88.3% | 2.91 |
| Dawson Cowan | WHL | 90.5% | 86.5% | Nebraska Omaha | 90.1% | 3.21 |
| Jacob Biron | CCHL | 90.9% | 86.1% | Army | 92.3% | 1.68 |
| Jared Moe | USHL | 90.7% | 85.9% | Minnesota | 91.5% | 2.46 |
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 |
|---|---|---|---|---|---|---|---|
| Zach Dosan | NA3HL | 92.1% | 87.8% | Gustavus Adolphus | D3 | 72.5% | 6.60 |
| Michael Paterson-Jones | USPHL-Premier | 92.0% | 88.7% | Wilkes | D3 | 89.5% | 3.08 |
| Connor Carbo | EHL | 89.3% | 90.3% | Wentworth | D3 | 92.3% | 3.00 |
| Tyler Fromolz | NA3HL | 92.0% | 87.1% | Marian | D3 | 88.3% | 3.85 |
| Nevin Tardif | USPHL-Premier | 90.4% | 88.0% | Worcester State | D3 | 89.8% | 3.54 |
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.