| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | Virden Oil Capitals | MJHL | 55 | 5 | 7 | 12 | 0.218 | 0.0420 | 0.0428 | 0.1375 | 0.1400 |
| 2023-24 | Virden Oil Capitals | MJHL | 55 | 7 | 15 | 22 | 0.400 | 0.0770 | 0.0743 | 0.2521 | 0.2434 |
| 2024-25 | Virden Oil Capitals | MJHL | 56 | 10 | 17 | 27 | 0.482 | 0.0928 | 0.0845 | 0.3038 | 0.2766 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Marian | D3 | NCHA | FR | 14 | 1 | 0 | 1 | 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.