| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2016-17 | — | USHL | 49 | 6 | 8 | 14 | 0.286 | 0.1685 | 0.1748 | 0.8581 | 0.8901 |
| 2017-18 | — | USHL | 60 | 23 | 19 | 42 | 0.700 | 0.4129 | 0.4078 | 2.1024 | 2.0764 |
| 2018-19 | — | USHL | 59 | 24 | 23 | 47 | 0.797 | 0.4699 | 0.4398 | 2.3925 | 2.2395 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2020-21 | Colorado College | D1 | NCHC | — | 22 | 5 | 8 | 13 | 0.591 |
| 2019-20 | Colorado College | D1 | NCHC | — | 34 | 5 | 8 | 13 | 0.382 |
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.