| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2012-13 | Chicago Steel | USHL | 60 | 16 | 11 | 27 | 0.450 | 0.2866 | 0.2917 | 1.3485 | 1.3725 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2016-17 | Michigan State | D1 | BigTen | SR | 35 | 3 | 13 | 16 | 0.457 |
| 2015-16 | Michigan State | D1 | BigTen | JR | 37 | 5 | 14 | 19 | 0.513 |
| 2014-15 | Michigan State | D1 | BigTen | SO | 35 | 4 | 7 | 11 | 0.314 |
| 2013-14 | Michigan State | D1 | BigTen | FR | 36 | 2 | 7 | 9 | 0.250 |
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.