| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | St. Michael's Buzzers | OJHL | 50 | 3 | 9 | 12 | 0.240 | 0.0671 | 0.0709 | 0.1656 | 0.1750 |
| 2022-23 | St. Michael's Buzzers | OJHL | 45 | 7 | 9 | 16 | 0.356 | 0.0994 | 0.1000 | 0.2454 | 0.2468 |
| 2023-24 | Pickering Panthers | OJHL | 43 | 9 | 11 | 20 | 0.465 | 0.1299 | 0.1239 | 0.3210 | 0.3062 |
| 2024-25 | Pickering Panthers | OJHL | 49 | 12 | 32 | 44 | 0.898 | 0.2509 | 0.2264 | 0.6197 | 0.5593 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | UMass Dartmouth | D3 | — | FR | 22 | 14 | 18 | 32 | 1.454 |
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.