| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2004-05 | U.S. National U17 Team | NTDP-U18 | 14 | 6 | 5 | 11 | 0.786 | 0.5840 | 0.5924 | 2.9318 | 2.9739 |
| 2005-06 | U.S. National U18 Team | NTDP-U18 | 43 | 11 | 12 | 23 | 0.535 | 0.3976 | 0.3839 | 1.9959 | 1.9272 |
| 2012-13 | HV71 | SHL | 52 | 14 | 25 | 39 | 0.750 | 1.8750 | 2.0369 | 9.7865 | 10.6316 |
| 2013-14 | Växjö Lakers HC | SHL | 55 | 13 | 25 | 38 | 0.691 | 1.7272 | 1.7513 | 9.0153 | 9.1412 |
| 2014-15 | Växjö Lakers HC | SHL | 51 | 6 | 12 | 18 | 0.353 | 0.8822 | 0.8525 | 4.6049 | 4.4498 |
| 2015-16 | Linköping HC | SHL | 33 | 14 | 15 | 29 | 0.879 | 2.1970 | 1.9969 | 11.4671 | 10.4225 |
| 2016-17 | Malmö Redhawks | SHL | 41 | 15 | 12 | 27 | 0.658 | 1.6462 | 1.3996 | 8.5925 | 7.3056 |
| 2017-18 | Malmö Redhawks | SHL | 37 | 9 | 22 | 31 | 0.838 | 2.0945 | 1.7137 | 10.9321 | 8.9446 |
| 2018-19 | Frölunda HC | SHL | 38 | 9 | 12 | 21 | 0.553 | 1.3815 | 1.0617 | 7.2107 | 5.5417 |
| 2019-20 | Frölunda HC | SHL | 36 | 10 | 15 | 25 | 0.694 | 1.7360 | 1.7360 | 9.0609 | 9.0609 |
| 2020-21 | Djurgårdens IF | SHL | 35 | 11 | 17 | 28 | 0.800 | 2.0000 | 2.0000 | 10.4389 | 10.4389 |
| 2021-22 | Djurgårdens IF | SHL | 50 | 11 | 15 | 26 | 0.520 | 1.3000 | 0.8384 | 6.7853 | 4.3759 |
| 2022-23 | Grizzlys Wolfsburg | DEL | 21 | 5 | 7 | 12 | 0.571 | 1.4285 | 0.9934 | 4.8444 | 3.3687 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2009-10 | Denver | D1 | NCHC | SR | 41 | 21 | 29 | 50 | 1.220 |
| 2008-09 | Denver | D1 | NCHC | JR | 38 | 15 | 22 | 37 | 0.974 |
| 2007-08 | Denver | D1 | NCHC | SO | 37 | 14 | 14 | 28 | 0.757 |
| 2006-07 | Denver | D1 | NCHC | FR | 40 | 10 | 26 | 36 | 0.900 |
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.