| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | Kingston Frontenacs | OHL | 15 | 1 | 3 | 4 | 0.267 | 0.1543 | 0.1710 | 0.6853 | 0.7593 |
| 2023-24 | Kingston Frontenacs | OHL | 38 | 3 | 7 | 10 | 0.263 | 0.1523 | 0.1615 | 0.6763 | 0.7170 |
| 2024-25 | Kingston Frontenacs | OHL | 68 | 2 | 25 | 27 | 0.397 | 0.2297 | 0.2317 | 1.0203 | 1.0290 |
| 2025-26 | Kingston Frontenacs | OHL | 68 | 3 | 34 | 37 | 0.544 | 0.3148 | 0.3017 | 1.3981 | 1.3397 |
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.