| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | Whitby Wolves | OWHL-U22 | 63 | 9 | 17 | 26 | 0.413 | 0.1443 | 0.1443 | — | — |
| 2023-24 | Whitby Wolves | OWHL-U22 | 54 | 21 | 27 | 48 | 0.889 | 0.3108 | 0.3108 | — | — |
| 2024-25 | Whitby Wolves | OWHL-U22 | 33 | 6 | 27 | 33 | 1.000 | 0.3496 | 0.3496 | — | — |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Robert Morris | D1 | CHA-W | — | 28 | 0 | 2 | 2 | 0.071 |
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.