icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2024-25 | — | BCHL | 15 | 10 | 3 | 93.0% | 1.98 | 1 | 0.9990 | 87.5% |
| 2024-25 | Saint John Sea Dogs | QMJHL | 28 | 14 | 14 | 91.4% | 2.82 | 3 | 0.9938 | 84.0% |
| 2023-24 | Baie-Comeau Drakkar | QMJHL | 51 | 31 | 17 | 90.9% | 2.48 | 2 | 0.9938 | 86.8% |
| 2022-23 | — | QMJHL | 47 | 15 | 24 | 89.6% | 3.62 | 2 | 0.9938 | 88.8% |
| 2021-22 | — | QMJHL | 43 | 16 | 18 | 88.8% | 3.44 | 1 | 0.9938 | 91.2% |
| 2020-21 | — | QMJHL | 7 | 3 | 3 | 88.1% | 3.84 | 0 | 0.9938 | 87.5% |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2025-26 | Mercyhurst | D1 | 27 | 3 | 21 | 90.7% | 3.22 | 2 |
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 |
|---|---|---|---|---|---|---|
| Matt Vernon | NAHL | 93.4% | 87.6% | Colorado College | 90.1% | 3.43 |
| Ryan Keane | NAHL | 92.7% | 86.8% | UConn | 100.0% | — |
| Simon Bucheler | NAHL | 92.2% | 86.7% | Mercyhurst | 90.1% | 3.92 |
| Carter Clafton | NAHL | 91.9% | 86.2% | Air Force | 100.0% | — |
| Eli Pulver | BCHL | 92.4% | 86.7% | Minnesota | 95.8% | 1.00 |
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 |
|---|---|---|---|---|---|---|---|
| Connor Strobel | NCDC | 92.3% | 88.0% | Plymouth State | D3 | 81.8% | 4.00 |
| Tyler Franchi | EHL | 91.9% | 87.7% | Lebanon Valley | D3 | 90.8% | 3.98 |
| Cameron Reardon | EHL | 92.2% | 87.7% | Keene State | D3 | 86.4% | 5.61 |
| Hunter Garvey | NAHL | 89.7% | 86.8% | St. Norbert | D3 | 92.2% | 1.90 |
| Blake Carlson | USPHL-Premier | 94.7% | 86.6% | Framingham State | D3 | 91.9% | 3.26 |
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.