| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Proctor | USHS-MN | 25 | 11 | 13 | 24 | 0.960 | 0.1215 | 0.1215 | 0.2332 | 0.2332 |
| 2022-23 | Proctor | USHS-MN | 25 | 8 | 14 | 22 | 0.880 | 0.1114 | 0.1114 | 0.2138 | 0.2138 |
| 2023-24 | Proctor | USHS-MN | 27 | 6 | 30 | 36 | 1.333 | 0.1688 | 0.1688 | 0.3239 | 0.3239 |
| 2024-25 | Colorado Grit | NAHL | 48 | 3 | 8 | 11 | 0.229 | 0.0842 | 0.0881 | 0.2419 | 0.2532 |
| 2025-26 | West Kelowna Warriors | BCHL | 54 | 2 | 13 | 15 | 0.278 | 0.1070 | 0.1062 | 0.4043 | 0.4013 |
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.