How can a person predicted best playing 11 in a match between two teams? This website allows people to bet on cricket and football matches. They ask people to select 11 players and there are point system, so at the end whoever ends with more points gets lots of money. 
Thus, as a statistician, how will you model the data to pick a team which has most probability of having best performing players. 
 A: There are different options available. I am not familiar with cricket, so I will speak about soccer here: 
First, if you do not have external data available but lots of historical data, you could apply a plus-minus rating. This is a (partial) correlation of each players appearance on the pitch with, for example, the goal margin (or shots on goal). We have done that to measure competitive balance as well as inequality in the distribution of playing talent across teams over time. See here for a non-technical description of our paper.
You can secondly also try to get a lot of within-game statistics, which are predictive for success in a team sport (such as pass completion rate or ball-winning ability). You need to somewhat hope that a collection of players which rank high will constitute a high-performing team (because these statistics are not directly one-to-one related to winning as is the goal margin. But you did not define high-performing in your question so winning might not be the most important measure).  
Thirdly, you could also try to gather external assessment of players (e.g. grades by journalists). In Germany for example, the Kicker sports magazine grades grades each matchday all players in Germany's major divisions. We did that in our paper to validate the plus-minus approach. 
There are of course numerous other approaches. 
