| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2014-15 | Aberdeen Wings | NAHL | 51 | 0 | 3 | 3 | 0.059 | 0.0216 | 0.0223 | 0.0621 | 0.0642 |
| 2015-16 | Aberdeen Wings | NAHL | 60 | 1 | 11 | 12 | 0.200 | 0.0735 | 0.0727 | 0.2111 | 0.2089 |
| 2016-17 | — | NAHL | 32 | 2 | 5 | 7 | 0.219 | 0.0804 | 0.0752 | 0.2309 | 0.2159 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | Ferris State | D1 | CCHA | — | 22 | 2 | 3 | 5 | 0.227 |
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.