| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | Milton Menace | OJHL | 47 | 7 | 11 | 18 | 0.383 | 0.0939 | 0.0987 | 0.2637 | 0.2771 |
| 2023-24 | Buffalo Jr. Sabres | OJHL | 56 | 23 | 35 | 58 | 1.036 | 0.2539 | 0.2536 | 0.7131 | 0.7122 |
| 2024-25 | Buffalo Jr. Sabres | OJHL | 50 | 24 | 26 | 50 | 1.000 | 0.2451 | 0.2322 | 0.6885 | 0.6522 |
| 2025-26 | Lone Star Brahmas | NAHL | 37 | 13 | 15 | 28 | 0.757 | 0.2780 | 0.2581 | 0.7988 | 0.7417 |
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.