| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2014-15 | — | AJHL | 28 | 5 | 4 | 9 | 0.321 | 0.1066 | 0.1101 | 0.2979 | 0.3077 |
| 2015-16 | Calgary Mustangs | AJHL | 50 | 14 | 21 | 35 | 0.700 | 0.2323 | 0.2292 | 0.6488 | 0.6400 |
| 2016-17 | — | AJHL | 46 | 11 | 13 | 24 | 0.522 | 0.1731 | 0.1623 | 0.4835 | 0.4534 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2020-21 | Marian | D1 | — | SR | 2 | 0 | 0 | 0 | 0.000 |
| 2020-21 | Marian | D3 | NCHA | SR | 2 | 0 | 0 | 0 | 0.000 |
| 2019-20 | Marian | D1 | — | JR | 17 | 4 | 4 | 8 | 0.471 |
| 2019-20 | Marian | D3 | NCHA | JR | 17 | 4 | 4 | 8 | 0.471 |
| 2018-19 | Marian | D1 | — | SO | 16 | 2 | 2 | 4 | 0.250 |
| 2018-19 | Marian | D3 | NCHA | SO | 16 | 2 | 2 | 4 | 0.250 |
| 2017-18 | Marian | D3 | NCHA | FR | 7 | 0 | 0 | 0 | 0.000 |
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.