icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2018-19 | — | NCDC | 21 | 7 | 11 | 89.6% | 3.70 | 2 | 0.9400 | 81.6% |
| 2018-19 | — | USPHL-Premier | 3 | 3 | 0 | 92.9% | 2.27 | 0 | 0.9400 | 83.9% |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2022-23 | Suffolk | D3 | 21 | 6 | 12 | 90.1% | 3.23 | — |
| 2021-22 | Suffolk | D3 | 23 | 7 | 11 | 90.9% | 3.40 | — |
| 2020-21 | Suffolk | D3 | 2 | 1 | 1 | 86.8% | 3.52 | 0 |
| 2019-20 | Suffolk | D3 | 17 | 4 | 10 | 89.1% | 4.18 | 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 |
|---|---|---|---|---|---|---|
| Conor Callaghan | USHL | 88.4% | 81.0% | Princeton | 85.3% | 5.02 |
| Justin Robbins | USHL | 87.4% | 80.6% | Arizona State | 92.3% | 4.00 |
| Remington Keopple | USHL | 89.3% | 82.4% | Cornell | 85.2% | 3.10 |
| Melvin Strahl | USHL | 90.3% | 83.0% | Michigan | 92.2% | 2.27 |
| Melvin Strahl | USHL | 90.3% | 83.0% | Michigan State | 92.2% | 2.27 |
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% | 82.6% | Plymouth State | D3 | 92.1% | 3.00 |
| Carson Ironside | AJHL | 87.8% | 84.2% | Albertus Magnus | D3 | 89.3% | 2.76 |
| Clément Labillois | SJHL | 88.9% | 84.4% | Assumption | D2 | 93.6% | 2.08 |
| Dylan Dewatcher | OJHL | 86.3% | 81.7% | Western Connecticut | D3 | 85.8% | 5.91 |
| Ford DeLoss | USPHL-Premier | 92.0% | 85.8% | Stevenson | D3 | 50.0% | 3.85 |
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.