| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2008-09 | — | OHL | 59 | 8 | 17 | 25 | 0.424 | 0.2451 | 0.2695 | 1.0887 | 1.1971 |
| 2009-10 | Oshawa Generals | OHL | 64 | 41 | 25 | 66 | 1.031 | 0.5965 | 0.6273 | 2.6497 | 2.7864 |
| 2010-11 | Oshawa Generals | OHL | 66 | 54 | 45 | 99 | 1.500 | 0.8678 | 0.8695 | 3.8543 | 3.8619 |
| 2011-12 | Oshawa Generals | OHL | 55 | 34 | 33 | 67 | 1.218 | 0.7047 | 0.6701 | 3.1302 | 2.9763 |
| 2018-19 | Traktor Chelyabinsk | KHL | 35 | 9 | 10 | 19 | 0.543 | 1.3573 | 1.4202 | 7.4805 | 7.8272 |
| 2019-20 | Traktor Chelyabinsk | KHL | 20 | 2 | 1 | 3 | 0.150 | 0.3750 | 0.3750 | 2.0668 | 2.0668 |
| 2020-21 | KooKoo | Liiga | 32 | 10 | 13 | 23 | 0.719 | 1.7970 | 1.7970 | 6.1789 | 6.1789 |
| 2021-22 | Barys Astana | KHL | 9 | 0 | 1 | 1 | 0.111 | 0.2777 | 0.2450 | 1.5308 | 1.3503 |
| 2024-25 | Iserlohn Roosters | DEL | 14 | 6 | 7 | 13 | 0.929 | 2.3215 | 1.8787 | 7.8729 | 6.3712 |
| 2025-26 | Iserlohn Roosters | DEL | 51 | 21 | 14 | 35 | 0.686 | 1.7158 | 1.4688 | 5.8186 | 4.9811 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2019-20 | SUNY Plattsburgh | D1 | SUNYAC | FR | 24 | 0 | 7 | 7 | 0.292 |
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.