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 | 11 | 4 | 6 | 92.2% | 3.20 | 0 | 0.9400 | 85.0% |
| 2018-19 | — | USHL | 15 | 6 | 6 | 89.5% | 2.66 | 1 | 0.9983 | 85.5% |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2022-23 | American International | D1 | 8 | 0 | 2 | 89.7% | 2.79 | 0 |
| 2021-22 | Merrimack | D1 | 1 | 0 | 1 | 83.3% | 5.05 | — |
| 2020-21 | Merrimack | D1 | 3 | 0 | 3 | 83.9% | 5.72 | 0 |
| 2019-20 | Merrimack | D1 | 19 | 4 | 9 | 89.3% | 3.30 | 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 |
|---|---|---|---|---|---|---|
| Dylan Silverstein | USHL | 88.8% | 84.6% | Quinnipiac | 90.3% | 2.25 |
| Joey Lamoreaux | USHL | 89.7% | 85.6% | St. Cloud State | 89.3% | 3.25 |
| Conor Callaghan | USHL | 88.4% | 84.5% | Princeton | 85.3% | 5.02 |
| Sam Hillebrandt | OHL | 90.3% | 86.3% | Ohio State | 87.0% | 3.76 |
| Jackson Unger | WHL | 89.9% | 85.7% | Colorado College | 91.1% | 2.53 |
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 |
|---|---|---|---|---|---|---|---|
| Clément Labillois | SJHL | 88.9% | 85.2% | Assumption | D2 | 93.6% | 2.08 |
| Nolan Mahaffey | NCDC | 87.4% | 86.2% | Lawrence | D3 | 90.5% | 3.39 |
| Dylan Dewatcher | OJHL | 86.3% | 85.2% | Western Connecticut | D3 | 85.8% | 5.91 |
| Maxim Zinchenko | USPHL-Premier | 91.8% | 87.0% | Johnson & Wales | D3 | 90.8% | 3.68 |
| Nick Anderson | USPHL-Premier | 92.6% | 87.8% | Nichols | D3 | 87.4% | 4.17 |
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.