All posts tagged Tableau Public

MCFC Analytics – Summary of blog posts #5

We had a great meeting this weekend to discuss how to move our community forward. We discussed some great ideas. As @MCFCGavinFleig pointed out on twitter, the next big announcements and steps forward will be public in late November/early December when the “CityAnalyticsCommunity” will be launched. Until then, keep blogging away with the data.

Here is a summary of the blog posts based on #MCFCAnalytics data.

Analytics posts

@MarkTaylor0 – How passing sequences create chances – the title is self-explanatory. Great post
@JDewitt – Long passing in the Premiership – John looks at the long passing and its correlation to finishing position in the league table. Interesting post. A question that came up when I read this post is, how is correlation to points or goals scored instead of position in the league table?
@TheWestStandO digs deeper into Fernando Torres’ struggles in front of goal last season
@ChrisJLilley defines metrics and rates the attacking midfielders, central midfielders and the defensive midfielders of last season.
@We_R_PL – Comparison of Top scorers in EPL
@Hpstats – A better passing statistic this was posted in the comments of summary #4
Fulham – opposition analysis by me

Visualization posts

@AlexThamks – a neat viz of Assists, chances created & key passes per formation + the best 11 for each formation using Tableau Public
@Tomberthon – a visualization of the advanced data set and how to make sense out of it

Other

@MarchiMax has a refined version #Rstats code for parsing the F-24 XML
@DannyPage has implemented a Ruby on rails code for importing the F-24 XML

Past summaries

Summary #4

by Ravi Ramineni on October 1, 2012 • Permalink

Posted in Barclays Premier League, Bolton Wanderers, English Premier League, Fulham, Manchester City, MCFC Analytics, Opta

Tagged #MCFCAnalytics, #Rstats, EPL 2011-12, football analytics, Fulham, Manchester City, MCFC Analytics, Ruby, Soccer analytics, soccer data visualization, Tableau Public

Posted by Ravi Ramineni on October 1, 2012

https://analysefootball.com/2012/10/01/mcfc-analytics-summary-of-blog-posts-5/

MCFC Analytics – Summary of blog posts #4

It has been about a month since the basic MCFC data set has been released and it is great to see lots of people churning out stuff using both the basic and advanced data sets.

Based on the tweets with #MCFCAnalytics tag, there are quite a few peoples’ projects are in progress. Good luck to all of you. Make sure you share your project/blog links with the hashtag.

Some people are looking for partners and contributors to the projects they are working on. If you are interested, please keep a tab on the #MCFCAnalytics tab and get in touch with folks directly.

Analysis posts

@MarkTaylor0 – Analyzing the passes by comparing them to their expected pass completion rates using passes of James Milner in Bolton Vs. Manchester City from 2011-12 season.
Mark also has post on how Man City and Bolton passed the ball
@Jdewitt – How goals are scored in EPL
@ChrisJLilley – Analyzing center-backs of the premier league
@analysefooty (this blog!)Opposition analysis of Arsenal

Visualization posts

@DanJHarrington – a very interesting visualizations of passes using Vector diagrams in Tableau Public
@MarchiMax – a visualization of where the ball is a few seconds before a shot is taken
@Ongoalsscored – Visualization of the goalscorer’s body parts. Very neat!

If I missed any please post your links in the comments section.

Links to previous summaries

Summary #1

Summary #2

Summary #3

Feel free to tweet me or email me if you want to chat with me on something specific!

10 Comments

by Ravi Ramineni on September 24, 2012 • Permalink

Posted in Arsenal, Barclays Premier League, Bolton Wanderers, Data Visualization, English Premier League, Football Analytics, Manchester City, MCFC Analytics, Opposition Analysis, Opta, Uncategorized

Tagged #MCFCAnalytics, EPL 2011-12, football analytics, MCFC Analytics, Soccer analytics, soccer data visualization, Tableau Public

Posted by Ravi Ramineni on September 24, 2012

https://analysefootball.com/2012/09/24/mcfc-analytics-summary-of-blog-posts-4/

MCFC Analytics – Summary of blog posts # 3

Thanks for the amazing response to Summary of blog posts #1 & Summary of blog posts #2

I also want to thank people who have reached out to me via twitter with links to their blogs & posts.

Goalscorer ‘footedness’ by @DavidAHopkins measures the footedness or the foot favoured by Premier League goalscorers.

How do the more successful clubs keep the ball in EPL by @JDewitt talks about how the top teams in EPL keep possession. Also by John is Successful Passing and Winning

A sneak peek of a very interesting carto by @Kennethfield Charlie Adam’s “passing wheel”

Football Philosophy – Long passes by @Poolq1984 explores the importance of long ball in football.

@We_R_PL has a nice post on how to use the MCFC dataset more efficiently. He also has spreadsheet which has the own goals calculated per team.

@footballfactman has a post on Darron Gibson using a mix of data from MCFC dataset, whoscored and statszone

The always excellent MarkTaylor0 has detailed post Analysing the quality of shots in Bolton – Manchester City game using the advanced dataset.

@ChrisJLilley has 3 posts on his blog using MCFC data

– GK positional analysis

– Premier league game changers Part I & Part II

@DanJHarrington has cranked up a lot of things using the advanced dataset

1. an interactive tableau viz to see touches of each player in Bolton -City on the pitch.

2. Passing visualization using D3.js

3. Dan also has some interesting visualization work in progress. There is a cool video in the link showing ball movement.

Network passing diagrams by @DevinPleuler

Bolton – http://t.co/mcRQ0oHU

Man City – http://t.co/6mtGgJQS

Extracting data from XML

There have been some questions regarding this and some folks have come up with solutions

1. If you have MS Excel 2007 or a later version you can open the file in XML. The only issue with is that XML’s are nested and Excel converts this into a very flat format. So you will see multiple rows for the same events. For example: A successful pass has multiple rows indicating the direction, the x,y coordinates of where it is passed to. Read the data spec thoroughly to understand how the data is formatted in the XML. It will help understand the data much better.

2. Code for R users to extract the F-24 XML by @MarchiMax

3. Code snippets from @JBrisson to extract events from the F-24 XML

4. If you are into programming, most languages have XML parsers. A simple search will get you code snippets to start with.
If I missed any links, please let me know via Twitter or comment on the blog post. Always use #MCFCAnalytics tag in twitter so I can pick them up easily!