| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2013-14 | Corpus Christi IceRays | NAHL | 13 | 1 | 0 | 1 | 0.077 | 0.0286 | 0.0304 | 0.0814 | 0.0867 |
| 2014-15 | — | NA3HL | 43 | 13 | 19 | 32 | 0.744 | 0.0897 | 0.0901 | 0.2351 | 0.2361 |
| 2015-16 | New Ulm Steel | NA3HL | 45 | 33 | 30 | 63 | 1.400 | 0.1687 | 0.1612 | 0.4423 | 0.4227 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2016-17 | Wisconsin-Stout | D3 | BigTen | FR | 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.