icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | — | USPHL-Premier | 24 | 16 | 6 | 93.3% | 2.22 | 1 | 0.9400 | 79.7% |
| 2021-22 | — | USPHL-Elite | 13 | 8 | 4 | 91.0% | 2.79 | 1 | 0.9400 | 78.3% |
| 2020-21 | — | USPHL-Elite | 19 | 13 | 4 | 91.6% | 2.16 | 3 | 0.9400 | 86.1% |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2025-26 | Lebanon Valley | D3 | 6 | — | — | 89.4% | 3.80 | 0 |
| 2024-25 | Lebanon Valley | D3 | 15 | 3 | 10 | 90.4% | 3.58 | 0 |
| 2023-24 | Lebanon Valley | D3 | 8 | 2 | 3 | 93.0% | 2.59 | 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 |
|---|---|---|---|---|---|---|
| Austin Elliott | OHL | 92.4% | 79.6% | UMass Lowell | 88.5% | 3.01 |
| Jacob Steinman | QMJHL | 92.3% | 79.8% | Bowling Green | 92.1% | 2.14 |
| Ryan Keyes | NCDC | 92.6% | 79.7% | Merrimack | 92.0% | 2.22 |
| Yan Shostak | USHL | 91.1% | 78.6% | St. Cloud State | 89.7% | 3.08 |
| Ben Bonisteel | OJHL | 92.6% | 79.9% | Canisius | 89.3% | 3.10 |
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 Swanbon | USPHL-Premier | 90.4% | 79.8% | Framingham State | D3 | 83.3% | 8.53 |
| Jeffrey Reda | USPHL-Premier | 90.6% | 80.1% | Franklin Pierce | D2 | 85.9% | 5.85 |
| Nicholas Von Kaufmann | OJHL | 88.9% | 79.9% | Marian | D3 | 88.6% | 3.25 |
| Dean Hahn | USPHL-Premier | 91.6% | 80.0% | Salem State | D3 | 88.9% | 3.95 |
| Jacob Gorinsky | OJHL | 89.9% | 80.7% | Norwich | D3 | 83.3% | 5.00 |
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.