icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2024-25 | — | NCDC | 3 | 1 | 1 | 87.2% | 4.68 | 0 | 0.9400 | 81.5% |
| 2024-25 | — | USPHL-Premier | 13 | 9 | 4 | 93.5% | 2.29 | 0 | 0.9400 | 86.0% |
| 2023-24 | — | USPHL-Premier | 11 | 8 | 2 | 93.7% | 2.01 | 3 | 0.9400 | 90.0% |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2025-26 | SUNY Morrisville | D3 | 16 | — | — | 90.2% | 4.99 | — |
| 2025-26 | Morrisville | D3 | 16 | — | — | 90.2% | 4.99 | — |
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 |
|---|---|---|---|---|---|---|
| Justin Robbins | USHL | 87.4% | 83.7% | Arizona State | 92.3% | 4.00 |
| Conor Callaghan | USHL | 88.4% | 84.5% | Princeton | 85.3% | 5.02 |
| Remington Keopple | USHL | 89.3% | 85.6% | Cornell | 85.2% | 3.10 |
| Axel Mangbo | USHL | 89.0% | 85.4% | Vermont | 85.7% | 5.00 |
| Jaxson Stauber | USHL | 88.3% | 85.0% | Minnesota | 93.3% | 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 |
|---|---|---|---|---|---|---|---|
| Brandon Shantz | NA3HL | 89.7% | 82.9% | Plymouth State | D3 | 92.1% | 3.00 |
| Jackson Fellner | SJHL | 89.9% | 86.4% | Alvernia | D3 | 92.4% | 2.68 |
| Carson Ironside | AJHL | 87.8% | 86.2% | Albertus Magnus | D3 | 89.3% | 2.76 |
| Clément Labillois | SJHL | 88.9% | 85.2% | Assumption | D2 | 93.6% | 2.08 |
| Cal Wilcox | NCDC | 89.6% | 87.9% | Suffolk | D3 | 89.1% | 4.18 |
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.