| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | OHA Mavericks Tardiff U22 | OWHL-U22 | 67 | 10 | 19 | 29 | 0.433 | 0.1516 | 0.1516 | — | — |
| 2023-24 | OHA Mavericks Tardiff U22 | OWHL-U22 | 65 | 17 | 26 | 43 | 0.661 | 0.2317 | 0.2317 | — | — |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Saint Anselm | D1 | NEWHA | — | 38 | 13 | 13 | 26 | 0.684 |
| 2024-25 | Saint Anselm | D1 | NEWHA | — | 38 | 8 | 8 | 16 | 0.421 |
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.