| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | Green Bay Gamblers | USHL | 3 | 0 | 0 | 0 | 0.000 | — | — | — | — |
| 2023-24 | Green Bay Gamblers | USHL | 42 | 0 | 2 | 2 | 0.048 | 0.0281 | 0.0292 | 0.1430 | 0.1488 |
| 2024-25 | Nanaimo Clippers | BCHL | 51 | 3 | 28 | 31 | 0.608 | 0.2342 | 0.2380 | 0.8845 | 0.8988 |
| 2025-26 | Sioux City Musketeers | USHL | 12 | 0 | 1 | 1 | 0.083 | 0.0491 | 0.0462 | 0.2502 | 0.2355 |
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.