| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2003-04 | USNTDP Juniors | NAHL | 42 | 10 | 12 | 22 | 0.524 | 0.1924 | 0.2158 | 0.5529 | 0.6201 |
| 2004-05 | U.S. National U18 Team | NTDP-U18 | 23 | 4 | 11 | 15 | 0.652 | 0.4848 | 0.4700 | 2.4336 | 2.3593 |
| 2014-15 | Metallurg Novokuznetsk | KHL | 60 | 15 | 15 | 30 | 0.500 | 1.2500 | 1.2332 | 6.8894 | 6.7968 |
| 2015-16 | — | KHL | 53 | 18 | 11 | 29 | 0.547 | 1.3680 | 1.2575 | 7.5397 | 6.9304 |
| 2016-17 | Spartak Moskva | KHL | 57 | 22 | 14 | 36 | 0.632 | 1.5790 | 1.3854 | 8.7026 | 7.6356 |
| 2017-18 | Spartak Moskva | KHL | 53 | 15 | 15 | 30 | 0.566 | 1.4150 | 1.1810 | 7.7987 | 6.5089 |
| 2018-19 | Traktor Chelyabinsk | KHL | 59 | 11 | 16 | 27 | 0.458 | 1.1440 | 0.9042 | 6.3051 | 4.9832 |
| 2019-20 | Örebro HK | SHL | 52 | 19 | 18 | 37 | 0.712 | 1.7788 | 1.7788 | 9.2841 | 9.2841 |
| 2020-21 | — | SHL | 24 | 3 | 5 | 8 | 0.333 | 0.8332 | 0.8332 | 4.3491 | 4.3491 |
| 2021-22 | Nürnberg Ice Tigers | DEL | 46 | 15 | 18 | 33 | 0.717 | 1.7935 | 1.2194 | 6.0823 | 4.1352 |
| 2022-23 | Nürnberg Ice Tigers | DEL | 32 | 14 | 4 | 18 | 0.562 | 1.4062 | 0.9147 | 4.7690 | 3.1022 |
| 2023-24 | Nürnberg Ice Tigers | DEL | 52 | 17 | 13 | 30 | 0.577 | 1.4423 | 0.8642 | 4.8911 | 2.9307 |
| 2024-25 | Nürnberg Ice Tigers | DEL | 52 | 12 | 15 | 27 | 0.519 | 1.2980 | 0.7181 | 4.4019 | 2.4354 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2008-09 | Minnesota | D1 | BigTen | JR | 36 | 24 | 22 | 46 | 1.278 |
| 2007-08 | Minnesota | D1 | BigTen | JR | 2 | 1 | 1 | 2 | 1.000 |
| 2006-07 | Minnesota | D1 | BigTen | SO | 41 | 12 | 12 | 24 | 0.585 |
| 2005-06 | Minnesota | D1 | BigTen | FR | 41 | 10 | 15 | 25 | 0.610 |
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.