| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Northern Cyclones | USPHL-Premier | 35 | 10 | 14 | 24 | 0.686 | 0.2260 | 0.2420 | 0.2333 | 0.2498 |
| 2022-23 | Winkler Flyers | MJHL | 57 | 22 | 24 | 46 | 0.807 | 0.2194 | 0.2235 | 0.5086 | 0.5182 |
| 2023-24 | Winkler Flyers | MJHL | 52 | 21 | 23 | 44 | 0.846 | 0.2301 | 0.2224 | 0.5333 | 0.5154 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Stonehill | D1 | AHA | SO | 20 | 1 | 3 | 4 | 0.200 |
| 2024-25 | Stonehill | D1 | AHA | — | 20 | 3 | 5 | 8 | 0.400 |
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.