| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | — | USHL | 57 | 17 | 28 | 45 | 0.789 | 0.4853 | 0.5309 | 2.3260 | 2.5444 |
| 2023-24 | Muskegon Lumberjacks | USHL | 61 | 36 | 32 | 68 | 1.115 | 0.6853 | 0.7156 | 3.2844 | 3.4297 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Boston University | D1 | HockeyEast | SO | 26 | 3 | 14 | 17 | 0.654 |
| 2024-25 | North Dakota | D1 | NCHC | — | 37 | 18 | 14 | 32 | 0.865 |
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.