| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2016-17 | Georgetown Raiders | OJHL | 3 | 0 | 2 | 2 | 0.667 | 0.1634 | 0.1884 | 0.4590 | 0.5291 |
| 2017-18 | Georgetown Raiders | OJHL | 54 | 0 | 15 | 15 | 0.278 | 0.0681 | 0.0752 | 0.1913 | 0.2113 |
| 2018-19 | Georgetown Raiders | OJHL | 55 | 2 | 11 | 13 | 0.236 | 0.0579 | 0.0611 | 0.1628 | 0.1719 |
| 2019-20 | Georgetown Raiders | OJHL | 53 | 1 | 30 | 31 | 0.585 | 0.1434 | 0.1434 | 0.4027 | 0.4027 |
| 2020-21 | Georgetown Raiders | OJHL | 0 | 0 | 0 | 0 | 0.000 | — | — | — | — |
| 2021-22 | North York Rangers | OJHL | 53 | 9 | 34 | 43 | 0.811 | 0.1988 | 0.1809 | 0.5586 | 0.5083 |
| 2023-24 | Toronto Metro Univ. | USports-M | 5 | 1 | 2 | 3 | 0.600 | 0.3166 | 0.3218 | 1.7586 | 1.7875 |
| 2024-25 | Toronto Metro Univ. | USports-M | 28 | 5 | 18 | 23 | 0.821 | 0.4334 | 0.4197 | 2.4075 | 2.3314 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | Aurora | D3 | NCHA | — | 29 | 6 | 9 | 15 | 0.517 |
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.