| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | — | MHL-RU | 47 | 16 | 8 | 24 | 0.511 | 0.3431 | 0.3415 | 1.1469 | 1.1416 |
| 2022-23 | — | USHL | 50 | 12 | 16 | 28 | 0.560 | 0.3442 | 0.3254 | 1.6499 | 1.5596 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Colorado College | D1 | NCHC | JR | 36 | 11 | 12 | 23 | 0.639 |
| 2024-25 | Colorado College | D1 | NCHC | JR | 36 | 9 | 10 | 19 | 0.528 |
| 2023-24 | Colorado College | D1 | NCHC | SO | 19 | 4 | 6 | 10 | 0.526 |
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.