| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | St. Mary's Academy Prep | CSSHL-U18W | 19 | 1 | 5 | 6 | 0.316 | 0.0723 | 0.0788 | — | — |
| 2022-23 | St. Mary's Academy Prep | CSSHL-U18W | 29 | 1 | 3 | 4 | 0.138 | 0.0316 | 0.0329 | — | — |
| 2023-24 | St. Mary's Academy Prep | CSSHL-U18W | 30 | 3 | 5 | 8 | 0.267 | 0.0611 | 0.0605 | — | — |
| 2024-25 | St. Mary's Academy Prep | CSSHL-U18W | 28 | 7 | 5 | 12 | 0.429 | 0.0982 | 0.0923 | — | — |
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.