| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Boston Jr. Bruins | USPHL-Premier | 33 | 9 | 19 | 28 | 0.849 | 0.0957 | 0.1040 | 0.2887 | 0.3137 |
| 2022-23 | Selkirk Steelers | MJHL | 53 | 7 | 9 | 16 | 0.302 | 0.0581 | 0.0601 | 0.1903 | 0.1969 |
| 2023-24 | Selkirk Steelers | MJHL | 38 | 4 | 10 | 14 | 0.368 | 0.0709 | 0.0696 | 0.2322 | 0.2281 |
| 2024-25 | Selkirk Steelers | MJHL | 44 | 14 | 21 | 35 | 0.795 | 0.1531 | 0.1420 | 0.5013 | 0.4648 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Neumann | D3 | MAC | — | 21 | 0 | 4 | 4 | 0.191 |
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.