| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2011-12 | Janesville Jets | NAHL | 50 | 1 | 1 | 2 | 0.040 | 0.0147 | 0.0165 | 0.0422 | 0.0473 |
| 2012-13 | Waterloo Black Hawks | USHL | 50 | 1 | 7 | 8 | 0.160 | 0.0944 | 0.0975 | 0.4805 | 0.4960 |
| 2013-14 | Waterloo Black Hawks | USHL | 59 | 7 | 14 | 21 | 0.356 | 0.2099 | 0.2069 | 1.0689 | 1.0535 |
| 2014-15 | Waterloo Black Hawks | USHL | 59 | 3 | 14 | 17 | 0.288 | 0.1700 | 0.1592 | 0.8653 | 0.8103 |
| 2021-22 | Iserlohn Roosters | DEL | 32 | 1 | 6 | 7 | 0.219 | 0.5470 | 0.5839 | 1.8550 | 1.9801 |
| 2022-23 | Düsseldorfer EG | DEL | 56 | 6 | 15 | 21 | 0.375 | 0.9375 | 0.9732 | 3.1793 | 3.3002 |
| 2023-24 | Düsseldorfer EG | DEL | 49 | 4 | 18 | 22 | 0.449 | 1.1225 | 1.1076 | 3.8067 | 3.7562 |
| 2024-25 | Düsseldorfer EG | DEL | 48 | 2 | 14 | 16 | 0.333 | 0.8332 | 0.7839 | 2.8258 | 2.6585 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2018-19 | Cornell | D1 | ECAC | SR | 36 | 3 | 9 | 12 | 0.333 |
| 2017-18 | Cornell | D1 | ECAC | JR | 32 | 5 | 7 | 12 | 0.375 |
| 2016-17 | Cornell | D1 | ECAC | SO | 35 | 1 | 9 | 10 | 0.286 |
| 2015-16 | Cornell | D1 | ECAC | FR | 34 | 3 | 12 | 15 | 0.441 |
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.