| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Stouffville Spirit | OJHL | 6 | 1 | 1 | 2 | 0.333 | 0.0817 | 0.0867 | 0.2295 | 0.2434 |
| 2022-23 | Smiths Falls Bears | CCHL | 49 | 11 | 10 | 21 | 0.429 | 0.0930 | 0.0947 | 0.3316 | 0.3375 |
| 2023-24 | Utah Outliers | NCDC | 53 | 19 | 42 | 61 | 1.151 | 0.4692 | 0.4616 | 0.9251 | 0.9102 |
| 2024-25 | Utah Outliers | NCDC | 48 | 37 | 17 | 54 | 1.125 | 0.4587 | 0.4309 | 0.9043 | 0.8495 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Gustavus Adolphus | D3 | MIAC | FR | 16 | 2 | 3 | 5 | 0.312 |
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.