| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2007-08 | Omaha Lancers | USHL | 38 | 5 | 11 | 16 | 0.421 | 0.2484 | 0.2539 | 1.2406 | 1.2680 |
| 2008-09 | Omaha Lancers | USHL | 60 | 17 | 30 | 47 | 0.783 | 0.4621 | 0.4516 | 2.3078 | 2.2555 |
| 2009-10 | Omaha Lancers | USHL | 57 | 35 | 47 | 82 | 1.439 | 0.8486 | 0.7750 | 4.2384 | 3.8710 |
| 2017-18 | Augsburger Panther | DEL | 52 | 16 | 26 | 42 | 0.808 | 2.0192 | 2.1571 | — | — |
| 2018-19 | Augsburger Panther | DEL | 50 | 22 | 27 | 49 | 0.980 | 2.4500 | 2.3949 | — | — |
| 2019-20 | Neftekhimik Nizhnekamsk | KHL | 60 | 15 | 19 | 34 | 0.567 | 1.4167 | 1.4167 | — | — |
| 2020-21 | Dinamo Riga | KHL | 16 | 0 | 5 | 5 | 0.312 | 0.7812 | 0.7812 | — | — |
| 2021-22 | Eisbären Berlin | DEL | 54 | 28 | 31 | 59 | 1.093 | 2.7315 | 2.1798 | — | — |
| 2022-23 | Eisbären Berlin | DEL | 56 | 16 | 35 | 51 | 0.911 | 2.2767 | 1.7500 | — | — |
| 2023-24 | Grizzlys Wolfsburg | DEL | 32 | 11 | 17 | 28 | 0.875 | 2.1875 | 1.5692 | — | — |
| 2024-25 | Grizzlys Wolfsburg | DEL | 52 | 18 | 31 | 49 | 0.942 | 2.3558 | 1.5817 | — | — |
| 2025-26 | Grizzlys Wolfsburg | DEL | 51 | 15 | 30 | 45 | 0.882 | 2.2060 | 1.5844 | — | — |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2013-14 | Vermont | D1 | HockeyEast | SR | 35 | 1 | 6 | 7 | 0.200 |
| 2012-13 | Nebraska Omaha | D1 | CCHA-orig | — | 37 | 16 | 18 | 34 | 0.919 |
| 2012-13 | Vermont | D1 | HockeyEast | JR | 34 | 6 | 10 | 16 | 0.471 |
| 2011-12 | Nebraska Omaha | D1 | CCHA-orig | — | 38 | 17 | 23 | 40 | 1.053 |
| 2011-12 | Vermont | D1 | HockeyEast | SO | 31 | 5 | 5 | 10 | 0.323 |
| 2010-11 | Nebraska Omaha | D1 | CCHA-orig | — | 39 | 14 | 11 | 25 | 0.641 |
| 2010-11 | Vermont | D1 | HockeyEast | FR | 34 | 3 | 8 | 11 | 0.324 |
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.