| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2014-15 | Calgary Mustangs | AJHL | 1 | 0 | 0 | 0 | 0.000 | — | — | — | — |
| 2015-16 | Calgary Mustangs | AJHL | 54 | 10 | 10 | 20 | 0.370 | 0.1229 | 0.1289 | 0.3433 | 0.3601 |
| 2016-17 | Calgary Mustangs | AJHL | 46 | 18 | 8 | 26 | 0.565 | 0.1875 | 0.1875 | 0.5238 | 0.5239 |
| 2017-18 | Calgary Mustangs | AJHL | 57 | 20 | 13 | 33 | 0.579 | 0.1921 | 0.1813 | 0.5365 | 0.5064 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Marian | D3 | NCHA | SR | 14 | 0 | 2 | 2 | 0.143 |
| 2020-21 | Marian | D1 | — | JR | 13 | 0 | 0 | 0 | 0.000 |
| 2020-21 | Marian | D3 | NCHA | JR | 13 | 0 | 0 | 0 | 0.000 |
| 2019-20 | Marian | D1 | — | SO | 26 | 5 | 2 | 7 | 0.269 |
| 2019-20 | Marian | D3 | NCHA | SO | 26 | 5 | 2 | 7 | 0.269 |
| 2018-19 | Marian | D1 | — | FR | 26 | 7 | 1 | 8 | 0.308 |
| 2018-19 | Marian | D3 | NCHA | FR | 26 | 7 | 1 | 8 | 0.308 |
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.