| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | — | NAHL | 51 | 3 | 1 | 4 | 0.078 | 0.0278 | 0.0283 | 0.0823 | 0.0837 |
| 2023-24 | — | NAHL | 63 | 9 | 23 | 32 | 0.508 | 0.1804 | 0.1748 | 0.5332 | 0.5167 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Bowdoin | D3 | NESCAC | SO | 24 | 4 | 4 | 8 | 0.333 |
| 2024-25 | Bowdoin | D3 | NESCAC | — | 17 | 0 | 3 | 3 | 0.176 |
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.