| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Kingston Frontenacs | OHL | 51 | 4 | 5 | 9 | 0.176 | 0.1021 | 0.1137 | 0.4535 | 0.5051 |
| 2022-23 | Kingston Frontenacs | OHL | 66 | 17 | 22 | 39 | 0.591 | 0.3418 | 0.3659 | 1.5183 | 1.6254 |
| 2023-24 | Kingston Frontenacs | OHL | 68 | 21 | 39 | 60 | 0.882 | 0.5105 | 0.5221 | 2.2673 | 2.3186 |
| 2024-25 | Flint Firebirds | OHL | 57 | 22 | 28 | 50 | 0.877 | 0.5075 | 0.4928 | 2.2540 | 2.1887 |
| 2025-26 | Flint Firebirds | OHL | 52 | 16 | 22 | 38 | 0.731 | 0.4228 | 0.3893 | 1.8778 | 1.7290 |
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.