icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2018-19 | — | USPHL-Premier | 14 | 9 | 3 | 92.3% | 2.51 | 1 | 0.9400 | 83.8% |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2023-24 | Anna Maria | D3 | — | — | — | — | — | — |
| 2022-23 | Anna Maria | D3 | 13 | 5 | 5 | 93.4% | 2.25 | — |
| 2021-22 | Lebanon Valley | D3 | 9 | 1 | 6 | 85.2% | 5.95 | — |
| 2020-21 | Lebanon Valley | D3 | 4 | 1 | 1 | 90.9% | 2.61 | 0 |
| 2019-20 | Lebanon Valley | D3 | 8 | 2 | 5 | 90.5% | 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 |
|---|---|---|---|---|---|---|
| Vinnie Purpura | USHL | 87.9% | 83.0% | Boston University | 86.0% | 4.90 |
| Kyle Chauvette | USHL | 89.2% | 84.0% | Union | 90.5% | 2.87 |
| Collin MacKenzie | OHL | 88.4% | 83.7% | RIT | 81.5% | 3.90 |
| Josh Fleming | QMJHL | 90.8% | 85.6% | Penn State | 92.4% | 2.61 |
| Matthew DellaRusso | NAHL | 89.6% | 86.1% | 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 |
|---|---|---|---|---|---|---|---|
| Jeb Lindy | USPHL-Premier | 89.3% | 83.7% | Arcadia | D3 | 89.6% | 4.06 |
| Nikolas Charles | USPHL-Premier | 89.1% | 83.2% | Roger Williams | D3 | 85.4% | 6.79 |
| Sean Guerin | NOJHL | 90.2% | 84.5% | Southern New Hampshire | D2 | 90.7% | 3.28 |
| Owen Carlson | NA3HL | 92.1% | 84.2% | Lawrence | D3 | 90.2% | 3.41 |
| Jake Horoho | USPHL-Premier | 92.0% | 86.0% | Middlebury | D3 | 89.4% | 3.02 |
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.