| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2009-10 | Alberni Valley Bulldogs | BCHL | 51 | 13 | 11 | 24 | 0.471 | 0.1813 | 0.1895 | 0.6849 | 0.7157 |
| 2010-11 | Alberni Valley Bulldogs | BCHL | 60 | 28 | 30 | 58 | 0.967 | 0.3725 | 0.3718 | 1.4068 | 1.4041 |
| 2011-12 | Omaha Lancers | USHL | 60 | 27 | 32 | 59 | 0.983 | 0.5800 | 0.5365 | 2.9532 | 2.7316 |
| 2018-19 | HC Slovan Bratislava | KHL | 45 | 1 | 4 | 5 | 0.111 | 0.2777 | 0.2825 | 1.5308 | 1.5573 |
| 2019-20 | Växjö Lakers HC | SHL | 28 | 7 | 4 | 11 | 0.393 | 0.9823 | 0.9823 | 5.1268 | 5.1268 |
| 2020-21 | Iserlohn Roosters | DEL | 37 | 20 | 24 | 44 | 1.189 | 2.9730 | 2.9730 | 10.0823 | 10.0823 |
| 2021-22 | Iserlohn Roosters | DEL | 50 | 23 | 18 | 41 | 0.820 | 2.0500 | 1.8591 | 6.9521 | 6.3047 |
| 2022-23 | Iserlohn Roosters | DEL | 53 | 12 | 27 | 39 | 0.736 | 1.8395 | 1.6140 | 6.2383 | 5.4737 |
| 2023-24 | ERC Ingolstadt | DEL | 20 | 4 | 6 | 10 | 0.500 | 1.2500 | 1.0327 | 4.2391 | 3.5021 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2014-15 | Penn State | D1 | BigTen | JR | 37 | 22 | 18 | 40 | 1.081 |
| 2013-14 | Penn State | D1 | BigTen | SO | 32 | 9 | 4 | 13 | 0.406 |
| 2012-13 | Penn State | D1 | BigTen | FR | 27 | 14 | 13 | 27 | 1.000 |
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.