| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Muskegon Lumberjacks | USHL | 39 | 3 | 6 | 9 | 0.231 | 0.1419 | 0.1478 | 0.6800 | 0.7083 |
| 2022-23 | Cranbrook Bucks | BCHL | 54 | 15 | 26 | 41 | 0.759 | 0.2828 | 0.2861 | 1.1064 | 1.1195 |
| 2023-24 | Tri-City Storm | USHL | 15 | 0 | 3 | 3 | 0.200 | 0.1229 | 0.1155 | 0.5892 | 0.5538 |
| 2024-25 | Brooks Bandits | BCHL | 41 | 19 | 27 | 46 | 1.122 | 0.4179 | 0.3827 | 1.6349 | 1.4970 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Maine | D1 | HockeyEast | FR | 7 | 0 | 2 | 2 | 0.286 |
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.