| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Connecticut Jr. Rangers | NCDC | 5 | 1 | 1 | 2 | 0.400 | 0.2230 | 0.2411 | — | — |
| 2022-23 | Maryland Black Bears | NAHL | 45 | 7 | 9 | 16 | 0.356 | 0.1409 | 0.1459 | 0.3733 | 0.3866 |
| 2023-24 | Maryland Black Bears | NAHL | 60 | 10 | 27 | 37 | 0.617 | 0.2443 | 0.2413 | 0.6475 | 0.6396 |
| 2024-25 | Maryland Black Bears | NAHL | 56 | 16 | 12 | 28 | 0.500 | 0.1981 | 0.1853 | 0.5250 | 0.4910 |
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.