| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Chicago T-Rex | USPHL-Premier | 17 | 10 | 10 | 20 | 1.177 | 0.1327 | 0.1356 | 0.4002 | 0.4088 |
| 2022-23 | Bay State Bobcats | NA3HL | 19 | 7 | 11 | 18 | 0.947 | 0.1048 | 0.1017 | 0.3001 | 0.2913 |
| 2023-24 | — | NCDC | 52 | 25 | 24 | 49 | 0.942 | 0.2178 | 0.2027 | 0.7619 | 0.7090 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Plymouth State | D3 | LittleEast | SO | 1 | 0 | 0 | 0 | 0.000 |
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.