| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2012-13 | Green Bay Gamblers | USHL | 8 | 0 | 0 | 0 | 0.000 | — | — | — | — |
| 2013-14 | — | USHL | 52 | 6 | 15 | 21 | 0.404 | 0.2382 | 0.2511 | 1.2128 | 1.2785 |
| 2014-15 | Chicago Steel | USHL | 57 | 27 | 33 | 60 | 1.053 | 0.6209 | 0.6240 | 3.1614 | 3.1772 |
| 2019-20 | MoDo Hockey | Allsvenskan | 52 | 10 | 24 | 34 | 0.654 | 1.6345 | 1.6345 | 6.1339 | 6.1339 |
| 2020-21 | IK Oskarshamn | SHL | 51 | 13 | 21 | 34 | 0.667 | 1.6667 | 1.6667 | 8.6995 | 8.6995 |
| 2021-22 | IK Oskarshamn | SHL | 49 | 15 | 27 | 42 | 0.857 | 2.1427 | 2.2630 | 11.1840 | 11.8120 |
| 2025-26 | Rögle BK | SHL | 52 | 12 | 26 | 38 | 0.731 | 1.8270 | 1.8270 | 9.5359 | 9.5359 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2018-19 | Nebraska Omaha | D1 | NCHC | SR | 36 | 10 | 24 | 34 | 0.944 |
| 2017-18 | Nebraska Omaha | D1 | NCHC | JR | 33 | 6 | 14 | 20 | 0.606 |
| 2016-17 | Nebraska Omaha | D1 | NCHC | SO | 34 | 11 | 13 | 24 | 0.706 |
| 2015-16 | Nebraska Omaha | D1 | NCHC | FR | 34 | 8 | 9 | 17 | 0.500 |
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.