icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2023-24 | — | EHL | 1 | 0 | 0 | 88.0% | 6.00 | 0 | 0.9400 | 82.5% |
| 2023-24 | — | USPHL-Premier | 24 | 15 | 7 | 91.8% | 2.39 | 4 | 0.9400 | 82.9% |
| 2022-23 | — | MHL-RU | 4 | 2 | 1 | 87.8% | 2.98 | 0 | 0.9600 | 82.8% |
| 2022-23 | — | USPHL-Premier | 8 | 6 | 1 | 93.1% | 2.10 | 1 | 0.9400 | 90.0% |
| 2021-22 | — | VHL | — | — | — | — | — | — | 1.0100 | — |
| 2021-22 | — | KHL | — | — | — | — | — | — | 1.0100 | — |
| 2021-22 | — | MHL-RU | 2 | 0 | 2 | 75.0% | 5.72 | 0 | 0.9600 | 75.8% |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2025-26 | Johnson & Wales | D3 | 9 | — | — | 91.9% | 3.38 | 0 |
| 2024-25 | Johnson & Wales | D3 | 6 | 2 | 3 | 90.8% | 3.68 | 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 |
|---|---|---|---|---|---|---|
| Joey Lamoreaux | USHL | 89.7% | 82.0% | St. Cloud State | 89.3% | 3.25 |
| Stephen Peck | USHL | 90.9% | 82.5% | Michigan | 91.1% | 2.61 |
| Troy Kobryn | USHL | 89.5% | 82.1% | Merrimack | 89.3% | 3.30 |
| Sam Hillebrandt | OHL | 90.3% | 82.7% | Ohio State | 87.0% | 3.76 |
| Jake Barczewski | USHL | 90.4% | 82.3% | Canisius | 90.5% | 2.92 |
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 |
|---|---|---|---|---|---|---|---|
| Dylan Dewatcher | OJHL | 86.3% | 81.7% | Western Connecticut | D3 | 85.8% | 5.91 |
| Brandon Shantz | NA3HL | 89.7% | 82.6% | Plymouth State | D3 | 92.1% | 3.00 |
| Nolan Mahaffey | NCDC | 87.4% | 85.4% | Lawrence | D3 | 90.5% | 3.39 |
| Clément Labillois | SJHL | 88.9% | 84.4% | Assumption | D2 | 93.6% | 2.08 |
| Owen Carlson | NA3HL | 92.1% | 83.0% | Lawrence | D3 | 90.2% | 3.41 |
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.