| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | Dubuque Fighting Saints | USHL | 6 | 0 | 1 | 1 | 0.167 | 0.1025 | 0.1060 | 0.4911 | 0.5080 |
| 2023-24 | Dubuque Fighting Saints | USHL | 53 | 4 | 5 | 9 | 0.170 | 0.1044 | 0.1028 | 0.5003 | 0.4927 |
| 2024-25 | Dubuque Fighting Saints | USHL | 62 | 1 | 11 | 12 | 0.194 | 0.1189 | 0.1110 | 0.5701 | 0.5323 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Colgate | D1 | ECAC | JR | 36 | 0 | 7 | 7 | 0.194 |
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.