| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Okotoks Oilers | AJHL | 59 | 12 | 19 | 31 | 0.525 | 0.1743 | 0.1896 | 0.4869 | 0.5297 |
| 2022-23 | Okotoks Oilers | AJHL | 45 | 22 | 30 | 52 | 1.156 | 0.3834 | 0.3981 | 1.0710 | 1.1120 |
| 2023-24 | Okotoks Oilers | AJHL | 42 | 28 | 33 | 61 | 1.452 | 0.4819 | 0.4776 | 1.3461 | 1.3342 |
| 2024-25 | Waterloo Black Hawks | USHL | 60 | 16 | 10 | 26 | 0.433 | 0.2663 | 0.2440 | 1.2766 | 1.1695 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Western Michigan | D1 | NCHC | — | 23 | 4 | 4 | 8 | 0.348 |
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.