| 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 | 0.0843 | 0.0951 | 0.4292 | 0.4843 |
| 2012-13 | Waterloo Black Hawks | USHL | 5 | 1 | 0 | 1 | 0.200 | 0.1180 | 0.1269 | 0.6007 | 0.6458 |
| 2013-14 | — | USHL | 50 | 21 | 28 | 49 | 0.980 | 0.5781 | 0.5945 | 2.9433 | 3.0266 |
| 2014-15 | — | USHL | 56 | 17 | 36 | 53 | 0.946 | 0.5583 | 0.5466 | 2.8424 | 2.7830 |
| 2021-22 | Nürnberg Ice Tigers | DEL | 49 | 25 | 18 | 43 | 0.878 | 2.1940 | 2.4357 | 7.4405 | 8.2603 |
| 2022-23 | Nürnberg Ice Tigers | DEL | 53 | 12 | 22 | 34 | 0.641 | 1.6037 | 1.7332 | 5.4388 | 5.8779 |
| 2023-24 | Straubing Tigers | DEL | 50 | 11 | 14 | 25 | 0.500 | 1.2500 | 1.2868 | 4.2391 | 4.3639 |
| 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.