| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2008-09 | Cornwall Colts | CCHL | 4 | 0 | 1 | 1 | 0.250 | 0.0542 | 0.0617 | 0.1915 | 0.2181 |
| 2009-10 | Cornwall Colts | CCHL | 62 | 19 | 39 | 58 | 0.935 | 0.2029 | 0.2217 | 0.7166 | 0.7830 |
| 2010-11 | Cornwall Colts | CCHL | 50 | 30 | 57 | 87 | 1.740 | 0.3774 | 0.3937 | 1.3328 | 1.3904 |
| 2011-12 | Cornwall Colts | CCHL | 25 | 22 | 40 | 62 | 2.480 | 0.5379 | 0.5336 | 1.8997 | 1.8844 |
| 2017-18 | Örebro HK | SHL | 48 | 8 | 10 | 18 | 0.375 | 0.9375 | 0.9931 | 4.8902 | 5.1802 |
| 2018-19 | Örebro HK | SHL | 51 | 6 | 4 | 10 | 0.196 | 0.4902 | 0.4949 | 2.5572 | 2.5818 |
| 2019-20 | Ässät | Liiga | 52 | 13 | 19 | 32 | 0.615 | 1.5385 | 1.5385 | 5.2889 | 5.2889 |
| 2020-21 | Schwenninger Wild Wings | DEL | 38 | 12 | 16 | 28 | 0.737 | 1.8420 | 1.8420 | 6.2453 | 6.2453 |
| 2021-22 | Schwenninger Wild Wings | DEL | 41 | 10 | 21 | 31 | 0.756 | 1.8902 | 1.8257 | 6.4089 | 6.1902 |
| 2022-23 | Schwenninger Wild Wings | DEL | 56 | 16 | 28 | 44 | 0.786 | 1.9642 | 1.8394 | 6.6598 | 6.2368 |
| 2023-24 | Schwenninger Wild Wings | DEL | 44 | 7 | 20 | 27 | 0.614 | 1.5340 | 1.3578 | 5.2011 | 4.6037 |
| 2024-25 | Schwenninger Wild Wings | DEL | 47 | 13 | 25 | 38 | 0.808 | 2.0213 | 1.6963 | 6.8531 | 5.7512 |
| 2025-26 | Schwenninger Wild Wings | DEL | 50 | 11 | 19 | 30 | 0.600 | 1.5000 | 1.3291 | 5.0858 | 4.5063 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2015-16 | Colgate | D1 | ECAC | SR | 37 | 13 | 21 | 34 | 0.919 |
| 2014-15 | Colgate | D1 | ECAC | JR | 23 | 7 | 13 | 20 | 0.870 |
| 2013-14 | Colgate | D1 | ECAC | SO | 37 | 14 | 16 | 30 | 0.811 |
| 2012-13 | Colgate | D1 | ECAC | FR | 36 | 13 | 18 | 31 | 0.861 |
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.