| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Cobourg Cougars | OJHL | 49 | 17 | 12 | 29 | 0.592 | 0.1778 | 0.1901 | 0.4051 | 0.4332 |
| 2022-23 | Cobourg Cougars | OJHL | 48 | 38 | 31 | 69 | 1.438 | 0.4318 | 0.4397 | 0.9840 | 1.0020 |
| 2023-24 | Cobourg Cougars | OJHL | 52 | 35 | 60 | 95 | 1.827 | 0.5488 | 0.5303 | 1.2505 | 1.2084 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Niagara | D1 | AHA | SO | 34 | 1 | 8 | 9 | 0.265 |
| 2024-25 | Niagara | D1 | AHA | — | 32 | 1 | 7 | 8 | 0.250 |
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.