| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | Regina Rebels | SFMAAAHL-W | 28 | 14 | 26 | 40 | 1.429 | 0.3341 | 0.3341 | — | — |
| 2023-24 | Regina Rebels | SFMAAAHL-W | 27 | 15 | 25 | 40 | 1.482 | 0.3465 | 0.3465 | — | — |
| 2024-25 | Regina Rebels | SFMAAAHL-W | 28 | 27 | 12 | 39 | 1.393 | 0.3258 | 0.3258 | — | — |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Mercyhurst | D1 | CHA-W | — | 37 | 11 | 8 | 19 | 0.513 |
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.