| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2016-17 | Johnstown Tomahawks | NAHL | 50 | 9 | 8 | 17 | 0.340 | 0.1262 | 0.1293 | 0.3600 | 0.3688 |
| 2017-18 | Johnstown Tomahawks | NAHL | 60 | 18 | 19 | 37 | 0.617 | 0.2290 | 0.2233 | 0.6530 | 0.6367 |
| 2018-19 | Muskegon Lumberjacks | USHL | 5 | 1 | 1 | 2 | 0.400 | 0.2547 | 0.2273 | 1.1987 | 1.0697 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2023-24 | Salve Regina | D3 | CNE | — | 26 | 5 | 8 | 13 | 0.500 |
| 2022-23 | Salve Regina | D3 | CNE | — | 25 | 16 | 12 | 28 | 1.120 |
| 2019-20 | SUNY Plattsburgh | D3 | — | FR | 22 | 4 | 5 | 9 | 0.409 |
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.