| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2011-12 | Waterloo Black Hawks | USHL | 7 | 0 | 1 | 1 | 0.143 | 0.0878 | 0.0991 | 0.4210 | 0.4750 |
| 2012-13 | Waterloo Black Hawks | USHL | 5 | 1 | 0 | 1 | 0.200 | 0.1229 | 0.1321 | 0.5892 | 0.6334 |
| 2013-14 | — | USHL | 50 | 21 | 28 | 49 | 0.980 | 0.6024 | 0.6194 | 2.8873 | 2.9690 |
| 2014-15 | — | USHL | 56 | 17 | 36 | 53 | 0.946 | 0.5818 | 0.5696 | 2.7883 | 2.7300 |
| 2021-22 | Nürnberg Ice Tigers | DEL | 49 | 25 | 18 | 43 | 0.878 | 0.9597 | 1.0654 | — | — |
| 2022-23 | Nürnberg Ice Tigers | DEL | 53 | 12 | 22 | 34 | 0.641 | 0.7015 | 0.7581 | — | — |
| 2023-24 | Straubing Tigers | DEL | 50 | 11 | 14 | 25 | 0.500 | 0.5468 | 0.5629 | — | — |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2018-19 | Minnesota | D1 | BigTen | SR | 38 | 12 | 29 | 41 | 1.079 |
| 2017-18 | Minnesota | D1 | BigTen | JR | 36 | 12 | 13 | 25 | 0.694 |
| 2016-17 | Minnesota | D1 | BigTen | SO | 38 | 20 | 33 | 53 | 1.395 |
| 2015-16 | Minnesota | D1 | BigTen | FR | 37 | 12 | 18 | 30 | 0.811 |
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.