| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | Blackfalds Bulldogs | AJHL | 30 | 6 | 14 | 20 | 0.667 | 0.2212 | 0.2230 | 0.6179 | 0.6230 |
| 2023-24 | Blackfalds Bulldogs | AJHL | 44 | 1 | 17 | 18 | 0.409 | 0.1357 | 0.1304 | 0.3792 | 0.3644 |
| 2024-25 | Coquitlam Express | BCHL | 47 | 2 | 27 | 29 | 0.617 | 0.2298 | 0.2098 | 0.8990 | 0.8206 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Sacred Heart | D1 | AHA | FR | 6 | 0 | 1 | 1 | 0.167 |
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.