| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Sudbury Wolves | OHL | 66 | 8 | 19 | 27 | 0.409 | 0.2367 | 0.2610 | 1.0512 | 1.1592 |
| 2022-23 | — | OHL | 66 | 12 | 29 | 41 | 0.621 | 0.3594 | 0.3808 | 1.5962 | 1.6911 |
| 2023-24 | Niagara IceDogs | OHL | 45 | 8 | 19 | 27 | 0.600 | 0.3471 | 0.3511 | 1.5417 | 1.5595 |
| 2024-25 | Niagara IceDogs | OHL | 38 | 14 | 18 | 32 | 0.842 | 0.4872 | 0.4677 | 2.1638 | 2.0771 |
| 2025-26 | Barrie Colts | OHL | 37 | 5 | 15 | 20 | 0.540 | 0.3127 | 0.2844 | 1.3888 | 1.2633 |
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.