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football top 3 teams league prediction

Hi everybody!

I'm working on my thesis and want to discover how predictable the final top three teams are in a football league (for example The English Premier League).

I am new to rapidminer and am not quite sure what to do. My data set consists of the league ranking per week over a period of 10 years. I would like to discover the accuracy percentage of the top 3 teams and next to analyze which team attributes may influence it (for example average weight of players in a team)

Anybody some advice?

thanks in advance for any help

Regards, Frederique

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MartinLiebig

Hi,

it's easy, take german Bundesliga. Bayern München always wins .

And seriously: You need to build a team profile. Like what is the average market value, average age etc. Based on this you can start to predict. Building the profile is key here.

Best,

Martin

f_nyst

Haha!! ;-)

Thanks for your reply! If I have the team profile, do you have suggestions on which operator to run on it? Naive Bayes?

And I also want see when I provide the league ranking over the 38 rounds to be played (in the English Premier League for example) after how many rounds a correct prediction comes out. In the example below, in which round can an operator predict the top three (or bottom three) of round 38.

Thanks so much in advance for any help

Rank

round 01

Round 02

Round 03

Round 04

Round 05

Round 06

Round 07

Round 08

Round 09

Round 10

Round 11

Round 12

Round 13

Round 14

Round 15

Round 16

Round 17

Round 18

Round 19

Round 20

Round 21

Round 22

Round 23

Round 24

Round 25

Round 26

Round 27

Round 28

Round 29

Round 30

Round 31

Round 32

Round 33

Round 34

Round 35

Round 36

Round 37

Round 38

Chelsea

Manchester United

Blackpool

Arsenal

Manchester United

Manchester City

Arsenal

Manchester United

Arsenal

Manchester United

Chelsea

Arsenal

Chelsea

Manchester United

Arsenal

Manchester United

Arsenal

Manchester United

Arsenal

Manchester United

Arsenal

Chelsea

Manchester City

Chelsea

Manchester City

Chelsea

Manchester City

Chelsea

Arsenal

Manchester City

MartinLiebig

Hi,

i guess you would build a process predicting the if a team is likely to be #1 or in #1-3 (not sure what's works best). Afterward you score a season and take the top3 in terms of likelihood.

Since this is a classification problem you can take a lot of algorithms. Naive Bayes is one of them and a good start but i guess you need stronger algorithms for decent results. Eg. Random Forest, SVM, Deep Learning.

Cheers,

Martin

f_nyst

Thanks for your help!!

One more question, hopefully the last one ;-)

For these analyses I obviously need a target attribute. So far I thought is should be the attribute "ranking" (i.e. rank 1 to 20, the first column in the example above), however it should predict the ranking after the last match. Should therefore the target attribute be "round 38" in the example of the English Premier League?

Best regards,

Frederique