| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2015-16 | Omaha Lancers | USHL | 57 | 6 | 8 | 14 | 0.246 | 0.1449 | 0.1376 | 0.7376 | 0.7005 |
| 2016-17 | Islanders Hockey Club | USPHL-Premier-Classic | 45 | 20 | 54 | 74 | 1.644 | 0.4616 | 0.4387 | 1.3520 | 1.2850 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2019-20 | Arizona State | D1 | NCHC | SO | 35 | 3 | 11 | 14 | 0.400 |
| 2018-19 | Arizona State | D1 | NCHC | SO | 31 | 4 | 9 | 13 | 0.419 |
| 2017-18 | Arizona State | D1 | NCHC | — | 0 | 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.