| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Culver Military Academy | USHS-W | 49 | 12 | 13 | 25 | 0.510 | 0.1534 | 0.1534 | — | — |
| 2022-23 | Culver Military Academy | USHS-W | 53 | 14 | 12 | 26 | 0.491 | 0.1475 | 0.1475 | — | — |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Bowdoin | D3 | NESCAC | — | 16 | 0 | 0 | 0 | 0.000 |
| 2024-25 | Bowdoin | D3 | NESCAC | — | 24 | 1 | 3 | 4 | 0.167 |
| 2023-24 | Bowdoin | D3 | NESCAC | — | 24 | 0 | 1 | 1 | 0.042 |
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.