| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | Whitecourt Wolverines | AJHL | 50 | 19 | 27 | 46 | 0.920 | 0.3053 | 0.3251 | 0.8527 | 0.9080 |
| 2023-24 | Madison Capitols | USHL | 57 | 9 | 13 | 22 | 0.386 | 0.2373 | 0.2358 | 1.1372 | 1.1300 |
| 2024-25 | Madison Capitols | USHL | 62 | 22 | 37 | 59 | 0.952 | 0.5849 | 0.5514 | 2.8036 | 2.6429 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Cornell | D1 | ECAC | FR | 34 | 9 | 11 | 20 | 0.588 |
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.