| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | — | USHL | 61 | 15 | 19 | 34 | 0.557 | 0.3426 | 0.3672 | 1.6422 | 1.7599 |
| 2023-24 | Dubuque Fighting Saints | USHL | 53 | 20 | 40 | 60 | 1.132 | 0.6959 | 0.7112 | 3.3354 | 3.4090 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Denver | D1 | NCHC | SO | 43 | 10 | 23 | 33 | 0.767 |
| 2024-25 | Denver | D1 | NCHC | — | 44 | 11 | 10 | 21 | 0.477 |
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.