| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Wisconsin Rapids Riverkings | USPHL-Premier | 44 | 8 | 17 | 25 | 0.568 | 0.0743 | 0.0856 | 0.1928 | 0.2221 |
| 2022-23 | Jersey Hitmen | NCDC | 47 | 4 | 5 | 9 | 0.192 | 0.0781 | 0.0873 | 0.1539 | 0.1720 |
| 2023-24 | Bonnyville Pontiacs | AJHL | 49 | 10 | 15 | 25 | 0.510 | 0.1711 | 0.1787 | 0.4721 | 0.4932 |
| 2024-25 | Brooks Bandits | BCHL | 39 | 2 | 12 | 14 | 0.359 | 0.1383 | 0.1378 | 0.5225 | 0.5207 |
| 2025-26 | Brooks Bandits | BCHL | 38 | 5 | 19 | 24 | 0.632 | 0.2434 | 0.2336 | 0.9192 | 0.8821 |
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.