| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Drayton Valley Thunder | AJHL | 60 | 14 | 21 | 35 | 0.583 | 0.1935 | 0.1955 | 0.5406 | 0.5461 |
| 2022-23 | Oklahoma Warriors | NAHL | 60 | 24 | 40 | 64 | 1.067 | 0.4226 | 0.4153 | 1.1199 | 1.1005 |
| 2023-24 | Oklahoma Warriors | NAHL | 56 | 22 | 33 | 55 | 0.982 | 0.3891 | 0.3638 | 1.0311 | 0.9640 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Union | D1 | ECAC | SO | 33 | 3 | 7 | 10 | 0.303 |
| 2024-25 | Union | D1 | ECAC | — | 35 | 3 | 3 | 6 | 0.171 |
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.