| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | New England Wolves | EHL | 24 | 7 | 14 | 21 | 0.875 | 0.1878 | 0.1921 | 0.4285 | 0.4383 |
| 2023-24 | Boston Jr. Rangers | EHL | 45 | 17 | 26 | 43 | 0.956 | 0.2051 | 0.1994 | 0.4680 | 0.4551 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2024-25 | Saint Mary's | D3 | MIAC | FR | 13 | 0 | 2 | 2 | 0.154 |
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.