| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2017-18 | — | USHL | 55 | 7 | 10 | 17 | 0.309 | 0.1823 | 0.1812 | 0.9275 | 0.9221 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | Bowling Green | D1 | CCHA | GR | 36 | 7 | 16 | 23 | 0.639 |
| 2021-22 | Bowling Green | D1 | CCHA | SR | 32 | 10 | 15 | 25 | 0.781 |
| 2020-21 | Bowling Green | D1 | WCHA | JR | 31 | 9 | 14 | 23 | 0.742 |
| 2019-20 | Bowling Green | D1 | WCHA | SO | 38 | 11 | 16 | 27 | 0.711 |
| 2018-19 | Bowling Green | D1 | WCHA | FR | 40 | 5 | 5 | 10 | 0.250 |
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.