| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2015-16 | Boston Jr. Rangers | EHL | 29 | 19 | 14 | 33 | 1.138 | 0.2629 | 0.2835 | 0.5568 | 0.6005 |
| 2016-17 | Shreveport Mudbugs | NAHL | 32 | 15 | 24 | 39 | 1.219 | 0.4478 | 0.4538 | 1.2864 | 1.3037 |
| 2017-18 | Youngstown Phantoms | USHL | 10 | 1 | 2 | 3 | 0.300 | 0.1770 | 0.1651 | 0.9010 | 0.8405 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | Alaska Fairbanks | D1 | WCHA | — | 4 | 0 | 0 | 0 | 0.000 |
| 2021-22 | Alaska Fairbanks | D1 | WCHA | — | 24 | 3 | 3 | 6 | 0.250 |
| 2019-20 | Alaska Fairbanks | D1 | WCHA | — | 27 | 1 | 6 | 7 | 0.259 |
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.