icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2011-12 | Springfield Jr. Blues | NAHL | 42 | 1 | 7 | 8 | 0.191 | 0.0707 | 0.0787 | 0.2017 | 0.2246 |
| 2012-13 | Janesville Jets | NAHL | 44 | 11 | 22 | 33 | 0.750 | 0.2785 | 0.2961 | 0.9988 | 1.0233 |
| 2016-17 | HK Sochi | KHL | 33 | 0 | 3 | 3 | 0.091 | — | — | — | — |
| 2017-18 | HK Sochi | KHL | 22 | 1 | 1 | 2 | 0.091 | — | — | — | — |
| 2018-19 | — | KHL | 11 | 0 | 1 | 1 | 0.091 | — | — | — | — |
| 2019-20 | Spartak Moskva | KHL | 10 | 0 | 0 | 0 | 0.000 | — | — | — | — |
| 2020-21 | Shanghai Dragons | KHL | 36 | 1 | 6 | 7 | 0.194 | — | — | — | — |
| 2021-22 | Amur Khabarovsk | KHL | 39 | 4 | 5 | 9 | 0.231 | — | — | — | — |
| 2022-23 | Amur Khabarovsk | KHL | 48 | 2 | 7 | 9 | 0.188 | — | — | — | — |
| 2023-24 | Vityaz Moscow Region | KHL | 59 | 7 | 12 | 19 | 0.322 | — | — | — | — |
| 2024-25 | Vityaz Moscow Region | KHL | 41 | 1 | 7 | 8 | 0.195 | — | — | — | — |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2015-16 | Bemidji State | D1 | WCHA | JR | 39 | 3 | 6 | 9 | 0.231 |
| 2014-15 | Bemidji State | D1 | WCHA | SO | 38 | 3 | 7 | 10 | 0.263 |
| 2013-14 | Bemidji State | D1 | WCHA | FR | 38 | 3 | 10 | 13 | 0.342 |
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.