Dear Friends,
Now this is becoming an headache for me. I am posting here but dont know whether I will be able to explain it properly.
I have some data that I posted below which shows player performance in a cricket tournament called State Premier League. First column is the Match number and next columns are names of the players. Instead of putting names, I had put their Jersey number for identification. The first level of the league of 21 matches are over and based on that, I wish to narrow down few performing players for next level. It has been observed that when a group of three or more players play together then they perform well and hence I want to find a group of people who have performed well in two or more matches.
It is easier for me to rank individual players and give them rank but I want to rank a group of players where three or more player together performed well and for that I need to have a comparitive analysis where I compare Match#1 with Match#2 and find out if there are 3 or more common players then move on and compare Match#1 and Match#3 and do this until we reach comparing Match#20 and Match#21. When I compared Match performance manually, I found players with Jersey # 24, 25, 66, 75 appeared twice together in Match # 4 and 8. Similarly, I found three groups of players who were common in other matches.
I have tried several formula based solution with/without arrays with/without helper columns and tried vba too. All my formulas failed and I did not put a good logic to write a vba code coz I could not think of an efficient logic for loops and ifs. Appreciate if someone could help.
Note: Out of 11 players, I have shortlisted 5 performing players for every match. In future, I may even shorlist 6 or more. The first level of the league where 21 matches are played could also change based on tournament planning so that the first level can also be less or more than 21 matches hence I would want to make provision for that too.
Here is the comparitive analysis (it could be more, manually I found only 3 instances)
compare match 4 and match 8, 4 players with jersey # 24 25 66 75 were common
compare match 5 and match 19, 3 players with jersey # 29 52 57 were common
compare match 13 and match 15, 3 players with jersey # 18 29 83 were common
Here is the data
Match# 01 : 82 90 1 68 61
Match# 02 : 9 22 52 88 10
Match# 03 : 47 8 40 34 82
Match# 04 : 75 25 66 35 24
Match# 05 : 29 57 43 52 72
Match# 06 : 89 37 35 20 41
Match# 07 : 3 36 49 9 90
Match# 08 : 66 84 24 25 75
Match# 09 : 3 49 65 4 11
Match# 10 : 35 4 29 67 55
Match# 11 : 40 92 51 9 42
Match# 12 : 52 75 53 14 66
Match# 13 : 41 34 83 18 29
Match# 14 : 84 39 20 40 86
Match# 15 : 90 1 18 83 29
Match# 16 : 81 36 55 92 13
Match# 17 : 41 69 59 88 70
Match# 18 : 77 12 2 86 93
Match# 19 : 65 57 52 29 38
Match# 20 : 90 60 41 65 48
Match# 21 : 92 59 58 7 45
Eagerly awaiting for some assistance.
Thank you !
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