| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2014-15 | — | NAHL | 36 | 1 | 5 | 6 | 0.167 | 0.0619 | 0.0630 | 0.1765 | 0.1796 |
| 2015-16 | St. Cloud Norsemen | NAHL | 18 | 2 | 5 | 7 | 0.389 | 0.1444 | 0.1406 | 0.4118 | 0.4008 |
| 2016-17 | Connecticut Jr. Rangers | USPHL-Premier-Classic | 42 | 12 | 34 | 46 | 1.095 | 0.3289 | 0.3091 | 0.9021 | 0.8478 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2017-18 | New England | D3 | — | FR | 28 | 7 | 20 | 27 | 0.964 |
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.