| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | Muskegon Lumberjacks | USHL | 46 | 3 | 6 | 9 | 0.196 | 0.1154 | 0.1213 | 0.5766 | 0.6063 |
| 2023-24 | Alberni Valley Bulldogs | BCHL | 48 | 13 | 13 | 26 | 0.542 | 0.2087 | 0.2145 | — | — |
| 2024-25 | Alberni Valley Bulldogs | BCHL | 52 | 22 | 21 | 43 | 0.827 | 0.3186 | 0.3115 | 1.2049 | 1.1779 |
| 2025-26 | Alberni Valley Bulldogs | BCHL | 29 | 17 | 22 | 39 | 1.345 | 0.5182 | 0.4875 | 1.9595 | 1.8434 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Alaska Anchorage | D1 | WCHA | FR | 19 | 3 | 2 | 5 | 0.263 |
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.