| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2017-18 | Amarillo Wranglers | NAHL | 43 | 3 | 2 | 5 | 0.116 | 0.0427 | 0.0434 | 0.1228 | 0.1247 |
| 2018-19 | Amarillo Wranglers | NAHL | 17 | 3 | 1 | 4 | 0.235 | 0.0864 | 0.0839 | 0.2484 | 0.2412 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2019-20 | Bethel | D1 | MIAC | FR | 14 | 2 | 1 | 3 | 0.214 |
| 2019-20 | Bethel | D3 | MIAC | — | 14 | 2 | 1 | 3 | 0.214 |
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.