| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2012-13 | Texas Tornado | NAHL | 39 | 1 | 8 | 9 | 0.231 | 0.0848 | 0.0894 | 0.2436 | 0.2567 |
| 2013-14 | Lone Star Brahmas | NAHL | 52 | 6 | 14 | 20 | 0.385 | 0.1413 | 0.1418 | 0.4059 | 0.4074 |
| 2014-15 | Lone Star Brahmas | NAHL | 54 | 10 | 24 | 34 | 0.630 | 0.2313 | 0.2200 | 0.6645 | 0.6321 |
| 2020-21 | Avangard Omsk | KHL | 13 | 0 | 3 | 3 | 0.231 | 0.5770 | 0.5770 | 3.1801 | 3.1801 |
| 2021-22 | Omskie Krylia | VHL | 5 | 0 | 1 | 1 | 0.200 | 0.3407 | 0.2878 | 1.4580 | 1.2315 |
| 2022-23 | Sibir Novosibirsk | KHL | 34 | 1 | 2 | 3 | 0.088 | 0.2205 | 0.2020 | 1.2153 | 1.1134 |
| 2023-24 | Admiral Vladivostok | KHL | 66 | 6 | 14 | 20 | 0.303 | 0.7575 | 0.6516 | 4.1749 | 3.5915 |
| 2024-25 | Avangard Omsk | KHL | 58 | 2 | 2 | 4 | 0.069 | 0.1725 | 0.1433 | 0.9507 | 0.7898 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2018-19 | Bentley | D1 | AHA | — | 37 | 5 | 8 | 13 | 0.351 |
| 2017-18 | Bentley | D1 | AHA | — | 31 | 1 | 9 | 10 | 0.323 |
| 2016-17 | Bentley | D1 | AHA | — | 31 | 7 | 9 | 16 | 0.516 |
| 2015-16 | Bentley | D1 | AHA | — | 30 | 1 | 3 | 4 | 0.133 |
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.