GIS Software for Non-GIS Applications

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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.

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GIS Software for Non-GIS Applications

  1. 1. GIS Ireland 2010<br />GIS Software for <br />Non-GIS Applications <br />Case Study: Save lots of time predicting Football Results with FME!<br />vs.<br />Brendan Cunningham<br />
  2. 2. Introduction<br />Overview : <br />What am I actually speaking about?!?!<br />Imagination meets GIS meets FME<br />Case Study :<br />FME versus The Bookmaker!<br />The FME Workspace<br />Publishing My Results<br />
  3. 3. Range of ETL Software Available<br />
  4. 4. FME, My Weapon of Choice<br />FME (SAFE Software) :<br />Can read/write 250+ Formats<br />Many are database/spreadsheet<br />www.safe.com<br />SAFE Software Management Systems :<br />CRM and Support Ticketing System<br />FME was used to migrate between from old ticketing systems to new systems<br />No GIS Component in these projects!<br />
  5. 5. Meet Michael Habarta…<br />FME Guru, based in Germany<br />http://www.fmepedia.com/index.php/User:Mhabarta<br />He has used FME for a variety of alternative applications:<br />Creating Polyphonic Ringtones<br />Updating an MP3 player Audiobook of The Bible<br />Understanding Pythagorus<br />Understanding Stonehenge<br />
  6. 6. 8-side Polygon – All Corners join to each other<br />
  7. 7. 48-side Polygon – All Corners join to each other<br />
  8. 8. 8-side Polygon – All Corners join to each other<br />Has this ever been used in an “everyday” application…<br />
  9. 9. Overlay 8-side Polygon on Stonehenge… Weird!<br />
  10. 10. Lego Building in FME!!!<br />Created by Dmitri Bagh, SAFE Software<br />http://www.fmepedia.com/index.php/Lego_House_Example<br />
  11. 11. Sudoku Generator in FME!!!<br />Created by Dmitri Bagh, SAFE Software<br />http://www.fmepedia.com/index.php/SudokuGenerator<br />
  12. 12. Case Study<br />Predicting Football Results with FME!<br />vs.<br />
  13. 13. Typical Weekend <br />Fixture List<br />Case Study<br />77 Games across 9 divisions<br />
  14. 14. Typical Weekend <br />Fixture List<br />Case Study<br />77 Games across 9 divisions<br />Another 50+ matches across other European Leagues<br />
  15. 15. Typical Weekend <br />Fixture List<br />Case Study<br />77 Games across 9 divisions<br />Another 50+ matches across other European Leagues<br />Takes approx. 3 hours to analyze UK fixtures based on multiple statistical criteria<br />
  16. 16. Typical Weekend <br />Fixture List<br />Case Study<br />77 Games across 9 divisions<br />Another 50+ matches across other European Leagues<br />Takes approx. 3 hours to analyze UK fixtures based on multiple statistical criteria<br />Another 2-3 hours to analyze European matches<br />
  17. 17. Statistical Criteria:<br />Case Study<br />Compare League Positions<br />Home vs. Away<br />Current Form – Last 5 league games<br />Non-Statistical Criteria:<br />Club Turmoil!<br />Injuries<br />Transfers In/Out<br />Rivalry & Derbies<br />
  18. 18. How can FME help out?<br />Great statistical functions in FME<br />Possible for FME to read <br />Historical Football Results (CSV/XLS)<br />Future Football Fixtures (CSV/XLS)<br />Analyze the relationship of teams who are playing each other<br />The aim is to reduce the 5-6 hours research down to 5-6 minutes using FME and some good football data…<br />
  19. 19. Meet www.Football-Data.co.uk!!!<br />
  20. 20. Fixture Data is downloaded in CSV/XLS Formats<br />Includes League, Date, Teams and the best Odds!<br />
  21. 21. Results Data is downloaded for 22 leagues across Europe<br />Includes League, Date, Teams, Goals, Referee, Shots, etc<br />
  22. 22. Project History<br />FME Prototype built in March 2010<br />Basically compared league positions<br />Invested €20 for 10 weeks of season<br />Result: €75 profit during this time<br />Excellent form guide and trends available (August-March results)<br />2010-2011 Football Season be difficult in early stages<br />No trends or previous results to go on<br />Erratic League (Blackpool in The Top Four!?!)<br />
  23. 23. The season so far…<br />
  24. 24. The season so far…<br />More Criteria Used<br />Create a League Table<br />Recent Form (Previous 6 Matches)<br />Best Odds available<br />Can Location / GI Data help anywhere?!?<br />In 99% of cases there is a spatial element to data<br />Early Form so far (Sept.- Oct. 2010)<br />Invested €30<br />Currently down €5.50<br />Famous last words… “Its early days…”<br />
  25. 25. The FME Workspace<br />Firstly, a Python Script is used to go onto the web to automatically download the CSV and XLS data<br />Secondly, a detailed workspace is run to analyze the data Fixtures and Results<br />Thirdly, filter out the “Good options” and output the results as a webpage, an excel spreadsheet and an email<br />
  26. 26. FME Workspace : Build a League Table<br />Analyse the historical results for each team and assign correct points:<br /><ul><li>Team Goals > Opposition Goals = 3
  27. 27. Team Goals = Opposition Goals = 1
  28. 28. Team Goals < Opposition Goals = 0</li></ul>Add all these up and FME is now storing a league table<br />Use the “Counter” transformer to add 1-20 based on current position<br />
  29. 29. FME : Compare who is playing who?<br />Analyse the teams who are playing:<br />Pass through any matches where the league position is very big<br />20 Teams in Premier League<br />Home Team (2) vs. Away Team (19) – PASS<br />Home Team (8) vs. Away Team (11) – FAIL<br />Set separate thresholds in FME for Home or Away Predicitons:<br />Home Team (4) vs. Away Team (19) – PASS<br />Home Team (19) vs. Away Team (4) – FAIL<br />
  30. 30. FME : Analyze Current Form<br />A team may be on a slump (due to injuries, turmoil, suspensions, etc.)<br />Analyze most recent games for better indication of current form<br />Home (8, WWwdw) vs. Away (15, lLLdL) – PASS<br />Home (8, LlwdL) vs. Away (15, WdWdL) – FAIL<br />Use separate thresholds for FME to recognise good/bad current form:<br />Undefeated in last 5 is good and will Pass<br />2 defeats or more is an automatic Fail<br />
  31. 31. FME : Progress Report<br />Statistical Criteria:<br />Compare League Positions<br />Home vs. Away<br />Current Form – Last 5 games<br />PASS<br />PASS<br />PASS<br />Non-Statistical Criteria:<br />Club Turmoil!<br />Injuries<br />Transfers In/Out<br />Rivalry & Derbies<br />Part of Current Form Algorithm <br />Part of Current Form Algorithm <br />Part of Current Form Algorithm <br />FAIL<br />
  32. 32. FME : Finally some GIS Integration<br />New Criteria:<br />99% Databases have a spatial component – football fixtures are no different!<br />Different Criteria for London and the rest of England:<br />Any fixture where teams are within 5 miles are deemed to be high chance of a Derby - FAIL<br />Any fixture where teams are within 5-20 miles are deemed to be potential Derby Matches – Further Info Needed<br />Teams 20-50 miles away outside of London are potential Derbies - Further Info Needed<br /><ul><li>Man Utd – Liverpool = 35 miles, big rivals!
  33. 33. Norwich – Ipswich = 43 miles, big rivals!
  34. 34. Newcastle – Middlesbrough = 39 miles, big rivals!</li></li></ul><li>I Googled “KML Football Grounds”<br /><ul><li>Some basic GIS data cleaning was require – done forever!!!
  35. 35. The GIS component is very loose, a work in progress...</li></li></ul><li>FME : Making the Money!<br />Downloaded Data contains Odds from various Bookmakers<br />FME can automatically analyze the Odds data for each bookmaker to check best odds:<br />Ladbrokes could be 15/1<br />PaddyPower could be 18/1<br />WilliamHill could be 14/1<br />
  36. 36. Publishing the Results<br />www.BrendanCunningham.com<br />Wordpress Blog<br />FME automatically writes valid HTML from the workspace into an Email<br />FME Batch File kicks off every Tuesday and Wednesday and sends me a mail!<br />Copy and Paste into blog, and offer some notes and advice<br />In some cases I won’t go with results<br />The “Blackpool Factor” will be used<br />
  37. 37. The Verdict<br />Model hard to use so early in the football season (only 9 matches)<br />The model becomes more reliable as more games are played<br />Not really a “Predictor”<br />More so an “event filter”<br />If certain criteria are met then they are passed though – this is not predicting!<br />A great time saver, potentially make a few quid over time!<br />Don’t give up the day job though…<br />
  38. 38. FME : Live Demo<br />Use this week’s fixtures and league tables to run the workspace<br />Data will be downloaded on the fly from www.football-data.co.uk (WiFi permitting!)<br />All Analysis is carried out in FME<br />Results output on C: drive:<br />Text File of Predictions<br />Text File of HTML code for the blog<br />XLS of Best Odds<br />Another Python script is run to email results<br />I manually analyze the results for 5-6 minutes and update the blog from there!<br />
  39. 39. Thank You for your Help<br />Michael Habarta(aed-sicad.com)<br />Don Murray (SAFE Software / FME)<br />Dale Lutz (SAFE Software / FME)<br />Mark Ireland (SAFE Software / FME)<br />Klaas Dijkstra<br />Dmitri Bagh(SAFE Software / FME)<br />Joe Buchdahl(football-data.co.uk)<br />IRLOGI, for the chance to present<br />

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