| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | Rock Springs Miners | USPHL-Premier | 5 | 1 | 0 | 1 | 0.200 | 0.0659 | 0.0700 | 0.0680 | 0.0723 |
| 2023-24 | Bridgewater Jr. Bandits | EHL | 43 | 1 | 5 | 6 | 0.140 | 0.0491 | 0.0511 | 0.0684 | 0.0712 |
| 2024-25 | Bridgewater Jr. Bandits | EHL | 44 | 12 | 10 | 22 | 0.500 | 0.1759 | 0.1741 | 0.2452 | 0.2427 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Rivier | D3 | MASCAC | FR | 16 | 0 | 1 | 1 | 0.062 |
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.