| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2005-06 | Indiana Ice | USHL | 52 | 1 | 7 | 8 | 0.154 | 0.0907 | 0.1034 | 0.4604 | 0.5248 |
| 2006-07 | Indiana Ice | USHL | 53 | 4 | 9 | 13 | 0.245 | 0.1447 | 0.1575 | 0.7344 | 0.7994 |
| 2007-08 | Indiana Ice | USHL | 58 | 8 | 13 | 21 | 0.362 | 0.2136 | 0.2216 | 1.0841 | 1.1245 |
| 2009-10 | Indiana Ice | USHL | 58 | 14 | 27 | 41 | 0.707 | 0.4170 | 0.3872 | 2.1163 | 1.9650 |
| 2013-14 | Tappara | Liiga | 54 | 11 | 21 | 32 | 0.593 | 1.4815 | 1.7045 | 5.0906 | 5.8568 |
| 2014-15 | Dinamo Minsk | KHL | 60 | 11 | 26 | 37 | 0.617 | 1.5417 | 1.7266 | 8.4918 | 9.5101 |
| 2015-16 | Dinamo Minsk | KHL | 40 | 6 | 25 | 31 | 0.775 | 1.9375 | 2.0392 | 10.6716 | 11.2318 |
| 2016-17 | Växjö Lakers HC | SHL | 20 | 4 | 10 | 14 | 0.700 | 1.7500 | 1.6426 | 9.1321 | 8.5716 |
| 2017-18 | Traktor Chelyabinsk | KHL | 56 | 11 | 19 | 30 | 0.536 | 1.3392 | 1.2963 | 7.3765 | 7.1402 |
| 2018-19 | Traktor Chelyabinsk | KHL | 62 | 7 | 17 | 24 | 0.387 | 0.9677 | 0.8939 | 5.3303 | 4.9236 |
| 2019-20 | Traktor Chelyabinsk | KHL | 36 | 11 | 14 | 25 | 0.694 | 1.7360 | 1.7360 | 9.5617 | 9.5617 |
| 2020-21 | Traktor Chelyabinsk | KHL | 51 | 13 | 22 | 35 | 0.686 | 1.7158 | 1.7158 | 9.4502 | 9.4502 |
| 2021-22 | Traktor Chelyabinsk | KHL | 49 | 6 | 36 | 42 | 0.857 | 2.1427 | 1.6273 | 11.8021 | 8.9631 |
| 2022-23 | Kölner Haie | DEL | 56 | 19 | 26 | 45 | 0.804 | 2.0090 | 1.5747 | 6.8128 | 5.3401 |
| 2023-24 | Kölner Haie | DEL | 34 | 4 | 20 | 24 | 0.706 | 1.7647 | 1.2926 | 5.9845 | 4.3836 |
| 2024-25 | Kölner Haie | DEL | 13 | 1 | 5 | 6 | 0.462 | 1.1538 | 0.7921 | 3.9126 | 2.6862 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2012-13 | RPI | D1 | ECAC | SR | 35 | 12 | 19 | 31 | 0.886 |
| 2011-12 | RPI | D1 | ECAC | JR | 39 | 7 | 15 | 22 | 0.564 |
| 2010-11 | RPI | D1 | ECAC | SO | 38 | 8 | 28 | 36 | 0.947 |
| 2008-09 | Bowling Green | D1 | CCHA | FR | 37 | 6 | 10 | 16 | 0.432 |
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.