| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | Northern Cyclones | USPHL-Premier | 40 | 12 | 25 | 37 | 0.925 | 0.3049 | 0.2961 | 0.3147 | 0.3056 |
| 2023-24 | Northern Cyclones | USPHL-Premier | 26 | 6 | 16 | 22 | 0.846 | 0.2789 | 0.2573 | 0.2879 | 0.2656 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Post | D2 | NE10 | — | 19 | 4 | 7 | 11 | 0.579 |
| 2024-25 | Post | D2 | NE10 | — | 26 | 5 | 2 | 7 | 0.269 |
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.