| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Ogden Mustangs | USPHL-Premier | 46 | 16 | 27 | 43 | 0.935 | 0.1054 | 0.1102 | 0.3180 | 0.3325 |
| 2022-23 | Ogden Mustangs | USPHL-Premier | 50 | 35 | 47 | 82 | 1.640 | 0.1850 | 0.1844 | 0.5579 | 0.5559 |
| 2023-24 | Ogden Mustangs | NCDC | 49 | 17 | 37 | 54 | 1.102 | 0.2547 | 0.2431 | 0.8911 | 0.8506 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Suffolk | D3 | CNE | — | 26 | 5 | 14 | 19 | 0.731 |
| 2024-25 | Nichols | D3 | CNE | — | 23 | 2 | 8 | 10 | 0.435 |
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.