| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Loko Yaroslavl | MHL-RU | 22 | 0 | 6 | 6 | 0.273 | 0.1387 | 0.1547 | 0.7307 | 0.8152 |
| 2022-23 | Waterloo Black Hawks | USHL | 41 | 8 | 6 | 14 | 0.342 | 0.2015 | 0.2147 | 1.0257 | 1.0929 |
| 2023-24 | Sioux Falls Stampede | USHL | 58 | 13 | 15 | 28 | 0.483 | 0.2848 | 0.2893 | 1.4500 | 1.4731 |
| 2024-25 | Sioux Falls Stampede | USHL | 60 | 13 | 25 | 38 | 0.633 | 0.3736 | 0.3605 | 1.9021 | 1.8353 |
| 2025-26 | Loko Yaroslavl | MHL-RU | 33 | 7 | 25 | 32 | 0.970 | 0.4933 | 0.4609 | 2.5983 | 2.4277 |
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.