| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | North York Rangers | OJHL | 50 | 10 | 19 | 29 | 0.580 | 0.1422 | 0.1512 | 0.3970 | 0.4222 |
| 2022-23 | North York Rangers | OJHL | 44 | 6 | 16 | 22 | 0.500 | 0.1226 | 0.1241 | 0.3422 | 0.3464 |
| 2023-24 | Flin Flon Bombers | SJHL | 50 | 18 | 21 | 39 | 0.780 | 0.1998 | 0.1966 | 0.5781 | 0.5689 |
| 2024-25 | Flin Flon Bombers | SJHL | 49 | 14 | 23 | 37 | 0.755 | 0.1935 | 0.1800 | 0.5596 | 0.5207 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Alvernia | D3 | MAC | — | 24 | 11 | 10 | 21 | 0.875 |
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.