| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Kingston Frontenacs | OHL | 53 | 6 | 19 | 25 | 0.472 | 0.2729 | 0.3023 | 1.2120 | 1.3428 |
| 2022-23 | Kingston Frontenacs | OHL | 54 | 15 | 27 | 42 | 0.778 | 0.4500 | 0.4791 | 1.9986 | 2.1278 |
| 2023-24 | Kingston Frontenacs | OHL | 66 | 25 | 31 | 56 | 0.849 | 0.4909 | 0.4991 | 2.1802 | 2.2167 |
| 2024-25 | Kingston Frontenacs | OHL | 58 | 18 | 16 | 34 | 0.586 | 0.3391 | 0.3273 | 1.5062 | 1.4537 |
| 2025-26 | Peterborough Petes | OHL | 68 | 19 | 32 | 51 | 0.750 | 0.4339 | 0.3970 | 1.9271 | 1.7630 |
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.