icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2023-24 | — | AJHL | 45 | 27 | 16 | 91.6% | 2.60 | 6 | 0.9700 | 83.1% |
| 2022-23 | — | OJHL | 20 | 15 | 5 | 90.8% | 2.15 | 1 | 0.9700 | 87.5% |
| 2021-22 | — | OJHL | 33 | 4 | 27 | 88.7% | 4.47 | 1 | 0.9700 | 91.7% |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2024-25 | Northern Michigan | D1 | 1 | 0 | 0 | 95.7% | 1.81 | 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 |
|---|---|---|---|---|---|---|
| Merek Pipes | MJHL | 92.4% | 83.6% | Union | 66.7% | 15.52 |
| Jake Barczewski | USHL | 90.4% | 82.3% | Canisius | 90.5% | 2.92 |
| Josh Fleming | QMJHL | 90.8% | 81.4% | Penn State | 92.4% | 2.61 |
| Kristoffer Eberly | USHL | 89.3% | 80.5% | Ohio State | 91.1% | 2.98 |
| Matthew DellaRusso | NAHL | 89.6% | 84.3% | Northeastern | 66.7% | 21.30 |
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 |
|---|---|---|---|---|---|---|---|
| Owen Carlson | NA3HL | 92.1% | 83.0% | Lawrence | D3 | 90.2% | 3.41 |
| Sean Guerin | NOJHL | 90.2% | 81.9% | Southern New Hampshire | D2 | 90.7% | 3.28 |
| Hunter Virostek | AJHL | 90.1% | 83.5% | Albertus Magnus | D3 | 75.0% | 6.00 |
| Jake Horoho | USPHL-Premier | 92.0% | 83.3% | Middlebury | D3 | 89.4% | 3.02 |
| Caleb Chabot | CCHL | 89.1% | 84.2% | Albertus Magnus | D3 | 93.4% | 1.79 |
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.