| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2014-15 | New York Bobcats | EHL | 44 | 13 | 21 | 34 | 0.773 | 0.1130 | 0.1086 | 0.3789 | 0.3643 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2018-19 | Western New England | D3 | CNE | SR | 15 | 0 | 2 | 2 | 0.133 |
| 2017-18 | Western New England | D3 | CNE | JR | 26 | 5 | 10 | 15 | 0.577 |
| 2016-17 | Western New England | D3 | CNE | SO | 16 | 2 | 2 | 4 | 0.250 |
| 2015-16 | Western New England | D3 | CNE | FR | 21 | 3 | 1 | 4 | 0.191 |
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.