| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | North Bay Battalion | OHL | 59 | 4 | 7 | 11 | 0.186 | 0.1078 | 0.1172 | 0.4790 | 0.5206 |
| 2022-23 | — | OHL | 61 | 6 | 10 | 16 | 0.262 | 0.1517 | 0.1583 | 0.6740 | 0.7035 |
| 2023-24 | Saginaw Spirit | OHL | 60 | 8 | 10 | 18 | 0.300 | 0.1736 | 0.1729 | 0.7709 | 0.7677 |
| 2024-25 | Saginaw Spirit | OHL | 62 | 18 | 17 | 35 | 0.565 | 0.3266 | 0.3084 | 1.4505 | 1.3696 |
| 2025-26 | Saginaw Spirit | OHL | 66 | 19 | 25 | 44 | 0.667 | 0.3857 | 0.3448 | 1.7131 | 1.5314 |
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.