| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2014-15 | — | AJHL | 2 | 0 | 0 | 0 | 0.000 | — | — | — | — |
| 2015-16 | — | AJHL | 54 | 6 | 21 | 27 | 0.500 | 0.1677 | 0.1855 | 0.4627 | 0.5119 |
| 2016-17 | — | AJHL | 53 | 8 | 29 | 37 | 0.698 | 0.2341 | 0.2476 | 0.6460 | 0.6832 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2019-20 | Denver | D1 | NCHC | JR | 36 | 10 | 22 | 32 | 0.889 |
| 2018-19 | Denver | D1 | NCHC | SO | 39 | 6 | 21 | 27 | 0.692 |
| 2017-18 | Denver | D1 | NCHC | FR | 41 | 2 | 28 | 30 | 0.732 |
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.