icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2017-18 | Sibir Novosibirsk | KHL | 25 | 0 | 0 | 0 | 0.000 | — | — | — | — |
| 2018-19 | Sibir Novosibirsk | KHL | 49 | 1 | 4 | 5 | 0.102 | 0.2550 | 0.3516 | 1.4052 | 1.9378 |
| 2019-20 | Sibir Novosibirsk | KHL | 59 | 4 | 5 | 9 | 0.152 | 0.3812 | 0.3812 | 2.1008 | 2.1008 |
| 2020-21 | Sibir Novosibirsk | KHL | 44 | 1 | 4 | 5 | 0.114 | 0.2840 | 0.2840 | 1.5650 | 1.5650 |
| 2021-22 | Sibir Novosibirsk | KHL | 46 | 3 | 7 | 10 | 0.217 | 0.5435 | 0.6602 | 2.9949 | 3.6380 |
| 2022-23 | Sibir Novosibirsk | KHL | 67 | 5 | 9 | 14 | 0.209 | 0.5225 | 0.5928 | 2.8792 | 3.2665 |
| 2023-24 | Sibir Novosibirsk | KHL | 68 | 5 | 4 | 9 | 0.132 | 0.3310 | 0.3570 | 1.8239 | 1.9673 |
| 2024-25 | Sibir Novosibirsk | KHL | 58 | 3 | 8 | 11 | 0.190 | 0.4743 | 0.4976 | 2.6133 | 2.7415 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Miami | D1 | NCHC | — | 36 | 8 | 12 | 20 | 0.556 |
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.