| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | — | USHL | 53 | 10 | 13 | 23 | 0.434 | 0.2560 | 0.2690 | 1.3035 | 1.3696 |
| 2022-23 | — | USHL | 59 | 28 | 20 | 48 | 0.814 | 0.4799 | 0.4793 | 2.4436 | 2.4405 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Western Michigan | D1 | NCHC | JR | 39 | 17 | 13 | 30 | 0.769 |
| 2024-25 | Colorado College | D1 | NCHC | — | 36 | 8 | 13 | 21 | 0.583 |
| 2023-24 | Colorado College | D1 | NCHC | — | 33 | 10 | 10 | 20 | 0.606 |
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.