| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Youngstown Phantoms | USHL | 3 | 1 | 1 | 2 | 0.667 | 0.4098 | 0.4490 | 1.9642 | 2.1520 |
| 2022-23 | Omaha Lancers | USHL | 55 | 4 | 9 | 13 | 0.236 | 0.1453 | 0.1516 | 0.6965 | 0.7269 |
| 2023-24 | Sioux City Musketeers | USHL | 59 | 10 | 14 | 24 | 0.407 | 0.2501 | 0.2486 | 1.1985 | 1.1913 |
| 2024-25 | Sioux City Musketeers | USHL | 60 | 15 | 11 | 26 | 0.433 | 0.2663 | 0.2511 | 1.2766 | 1.2038 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Miami | D1 | NCHC | FR | 31 | 3 | 5 | 8 | 0.258 |
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.