Presentation Slides for my presentation at GIS Ireland, October 14th 2010. The title is "GIS Software for Non-GIS Applications". The case study is how to use FME to predict the outcome of football matches across Europe each week.

1. GIS Ireland 2010 GIS Software for Non-GIS Applications Case Study: Save lots of time predicting Football Results with FME! vs. Brendan Cunningham

2. Introduction Overview : What am I actually speaking about?!?! Imagination meets GIS meets FME Case Study : FME versus The Bookmaker! The FME Workspace Publishing My Results

3. Range of ETL Software Available

4. FME, My Weapon of Choice FME (SAFE Software) : Can read/write 250+ Formats Many are database/spreadsheet www.safe.com SAFE Software Management Systems : CRM and Support Ticketing System FME was used to migrate between from old ticketing systems to new systems No GIS Component in these projects!

5. Meet Michael Habarta… FME Guru, based in Germany http://www.fmepedia.com/index.php/User:Mhabarta He has used FME for a variety of alternative applications: Creating Polyphonic Ringtones Updating an MP3 player Audiobook of The Bible Understanding Pythagorus Understanding Stonehenge

6. 8-side Polygon – All Corners join to each other

7. 48-side Polygon – All Corners join to each other

8. 8-side Polygon – All Corners join to each other Has this ever been used in an “everyday” application…

9. Overlay 8-side Polygon on Stonehenge… Weird!

10. Lego Building in FME!!! Created by Dmitri Bagh, SAFE Software http://www.fmepedia.com/index.php/Lego_House_Example

11. Sudoku Generator in FME!!! Created by Dmitri Bagh, SAFE Software http://www.fmepedia.com/index.php/SudokuGenerator

12. Case Study Predicting Football Results with FME! vs.

13. Typical Weekend Fixture List Case Study 77 Games across 9 divisions

14. Typical Weekend Fixture List Case Study 77 Games across 9 divisions Another 50+ matches across other European Leagues

15. Typical Weekend Fixture List Case Study 77 Games across 9 divisions Another 50+ matches across other European Leagues Takes approx. 3 hours to analyze UK fixtures based on multiple statistical criteria

16. Typical Weekend Fixture List Case Study 77 Games across 9 divisions Another 50+ matches across other European Leagues Takes approx. 3 hours to analyze UK fixtures based on multiple statistical criteria Another 2-3 hours to analyze European matches

17. Statistical Criteria: Case Study Compare League Positions Home vs. Away Current Form – Last 5 league games Non-Statistical Criteria: Club Turmoil! Injuries Transfers In/Out Rivalry & Derbies

18. How can FME help out? Great statistical functions in FME Possible for FME to read Historical Football Results (CSV/XLS) Future Football Fixtures (CSV/XLS) Analyze the relationship of teams who are playing each other The aim is to reduce the 5-6 hours research down to 5-6 minutes using FME and some good football data…

19. Meet www.Football-Data.co.uk!!!

20. Fixture Data is downloaded in CSV/XLS Formats Includes League, Date, Teams and the best Odds!

21. Results Data is downloaded for 22 leagues across Europe Includes League, Date, Teams, Goals, Referee, Shots, etc

22. Project History FME Prototype built in March 2010 Basically compared league positions Invested €20 for 10 weeks of season Result: €75 profit during this time Excellent form guide and trends available (August-March results) 2010-2011 Football Season be difficult in early stages No trends or previous results to go on Erratic League (Blackpool in The Top Four!?!)

23. The season so far…

24. The season so far… More Criteria Used Create a League Table Recent Form (Previous 6 Matches) Best Odds available Can Location / GI Data help anywhere?!? In 99% of cases there is a spatial element to data Early Form so far (Sept.- Oct. 2010) Invested €30 Currently down €5.50 Famous last words… “Its early days…”

25. The FME Workspace Firstly, a Python Script is used to go onto the web to automatically download the CSV and XLS data Secondly, a detailed workspace is run to analyze the data Fixtures and Results Thirdly, filter out the “Good options” and output the results as a webpage, an excel spreadsheet and an email

27. Team Goals = Opposition Goals = 1

28. Team Goals < Opposition Goals = 0Add all these up and FME is now storing a league table Use the “Counter” transformer to add 1-20 based on current position

29. FME : Compare who is playing who? Analyse the teams who are playing: Pass through any matches where the league position is very big 20 Teams in Premier League Home Team (2) vs. Away Team (19) – PASS Home Team (8) vs. Away Team (11) – FAIL Set separate thresholds in FME for Home or Away Predicitons: Home Team (4) vs. Away Team (19) – PASS Home Team (19) vs. Away Team (4) – FAIL

30. FME : Analyze Current Form A team may be on a slump (due to injuries, turmoil, suspensions, etc.) Analyze most recent games for better indication of current form Home (8, WWwdw) vs. Away (15, lLLdL) – PASS Home (8, LlwdL) vs. Away (15, WdWdL) – FAIL Use separate thresholds for FME to recognise good/bad current form: Undefeated in last 5 is good and will Pass 2 defeats or more is an automatic Fail

31. FME : Progress Report Statistical Criteria: Compare League Positions Home vs. Away Current Form – Last 5 games PASS PASS PASS Non-Statistical Criteria: Club Turmoil! Injuries Transfers In/Out Rivalry & Derbies Part of Current Form Algorithm Part of Current Form Algorithm Part of Current Form Algorithm FAIL

33. Norwich – Ipswich = 43 miles, big rivals!

36. Publishing the Results www.BrendanCunningham.com Wordpress Blog FME automatically writes valid HTML from the workspace into an Email FME Batch File kicks off every Tuesday and Wednesday and sends me a mail! Copy and Paste into blog, and offer some notes and advice In some cases I won’t go with results The “Blackpool Factor” will be used

37. The Verdict Model hard to use so early in the football season (only 9 matches) The model becomes more reliable as more games are played Not really a “Predictor” More so an “event filter” If certain criteria are met then they are passed though – this is not predicting! A great time saver, potentially make a few quid over time! Don’t give up the day job though…

38. FME : Live Demo Use this week’s fixtures and league tables to run the workspace Data will be downloaded on the fly from www.football-data.co.uk (WiFi permitting!) All Analysis is carried out in FME Results output on C: drive: Text File of Predictions Text File of HTML code for the blog XLS of Best Odds Another Python script is run to email results I manually analyze the results for 5-6 minutes and update the blog from there!

39. Thank You for your Help Michael Habarta(aed-sicad.com) Don Murray (SAFE Software / FME) Dale Lutz (SAFE Software / FME) Mark Ireland (SAFE Software / FME) Klaas Dijkstra Dmitri Bagh(SAFE Software / FME) Joe Buchdahl(football-data.co.uk) IRLOGI, for the chance to present