| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | White Bear Lake | USHS-MN | 26 | 3 | 8 | 11 | 0.423 | 0.0536 | 0.0536 | 0.1028 | 0.1028 |
| 2023-24 | White Bear Lake | USHS-MN | 30 | 7 | 21 | 28 | 0.933 | 0.1182 | 0.1182 | — | — |
| 2024-25 | Austin Bruins | NAHL | 18 | 0 | 2 | 2 | 0.111 | 0.0408 | 0.0440 | 0.1173 | 0.1265 |
| 2025-26 | Coquitlam Express | BCHL | 48 | 3 | 13 | 16 | 0.333 | 0.1284 | 0.1315 | 0.4851 | 0.4969 |
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.