| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2014-15 | Sherwood Park Crusaders | AJHL | 52 | 5 | 17 | 22 | 0.423 | 0.1419 | 0.1521 | 0.3915 | 0.4195 |
| 2015-16 | — | AJHL | 54 | 9 | 22 | 31 | 0.574 | 0.1926 | 0.1974 | 0.5313 | 0.5447 |
| 2016-17 | Okotoks Oilers | AJHL | 60 | 26 | 31 | 57 | 0.950 | 0.3186 | 0.3111 | 0.8791 | 0.8584 |
| 2017-18 | Okotoks Oilers | AJHL | 52 | 32 | 37 | 69 | 1.327 | 0.4450 | 0.4094 | 1.2279 | 1.1298 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | Minnesota Duluth | D1 | NCHC | — | 37 | 2 | 5 | 7 | 0.189 |
| 2021-22 | Minnesota Duluth | D1 | NCHC | — | 38 | 10 | 3 | 13 | 0.342 |
| 2020-21 | Minnesota Duluth | D1 | NCHC | JR | 28 | 3 | 7 | 10 | 0.357 |
| 2019-20 | Minnesota Duluth | D1 | NCHC | SO | 31 | 8 | 8 | 16 | 0.516 |
| 2018-19 | Minnesota Duluth | D1 | NCHC | FR | 38 | 7 | 5 | 12 | 0.316 |
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.