| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2015-16 | Dauphin Kings | MJHL | 8 | 2 | 1 | 3 | 0.375 | 0.1020 | 0.1172 | 0.2363 | 0.2716 |
| 2016-17 | Dauphin Kings | MJHL | 42 | 13 | 19 | 32 | 0.762 | 0.2072 | 0.2280 | 0.4801 | 0.5284 |
| 2017-18 | — | MJHL | 51 | 26 | 22 | 48 | 0.941 | 0.2559 | 0.2692 | 0.5931 | 0.6239 |
| 2018-19 | Dubuque Fighting Saints | USHL | 61 | 22 | 28 | 50 | 0.820 | 0.5039 | 0.4912 | 2.4150 | 2.3541 |
| 2019-20 | Dubuque Fighting Saints | USHL | 47 | 34 | 21 | 55 | 1.170 | 0.7193 | 0.7193 | 3.4476 | 3.4476 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2023-24 | North Dakota | D1 | NCHC | SR | 40 | 18 | 16 | 34 | 0.850 |
| 2022-23 | North Dakota | D1 | NCHC | JR | 39 | 20 | 17 | 37 | 0.949 |
| 2021-22 | North Dakota | D1 | NCHC | SO | 34 | 15 | 22 | 37 | 1.088 |
| 2020-21 | North Dakota | D1 | NCHC | FR | 29 | 11 | 10 | 21 | 0.724 |
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.