| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Deerfield Academy | NE-Prep | 24 | 1 | 0 | 1 | 0.042 | 0.0084 | 0.0084 | 0.0191 | 0.0191 |
| 2022-23 | Deerfield Academy | NE-Prep | 26 | 3 | 1 | 4 | 0.154 | 0.0309 | 0.0309 | 0.0703 | 0.0703 |
| 2023-24 | Deerfield Academy | NE-Prep | 26 | 1 | 6 | 7 | 0.269 | 0.0541 | 0.0541 | 0.1231 | 0.1231 |
| 2024-25 | Deerfield Academy | NE-Prep | 27 | 1 | 11 | 12 | 0.444 | 0.0894 | 0.0894 | 0.2032 | 0.2032 |
| 2025-26 | — | NCDC | 48 | 8 | 25 | 33 | 0.688 | 0.2803 | 0.2731 | 0.5501 | 0.5360 |
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.