| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | — | USHL | 34 | 2 | 3 | 5 | 0.147 | 0.0904 | 0.0955 | 0.4334 | 0.4578 |
| 2022-23 | Aberdeen Wings | NAHL | 57 | 14 | 15 | 29 | 0.509 | 0.2016 | 0.2113 | 0.5342 | 0.5598 |
| 2023-24 | — | BCHL | 47 | 8 | 15 | 23 | 0.489 | 0.1823 | 0.1788 | 0.7131 | 0.6994 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Army | D1 | AHA | SO | 20 | 2 | 0 | 2 | 0.100 |
| 2024-25 | Army | D1 | AHA | — | 34 | 2 | 4 | 6 | 0.176 |
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.