FIFA 18 Player Analytics Project 1 IMGD 2905

FIFA 18 Player Analytics Project 1 IMGD 2905

Overview • Set up tools for part of game analytics pipeline • Apply to EA’s FIFA 18 • Pipeline: • Basic queries this project, but will do more advanced for Project 3+ – E. g. , front end involves some scripting in Python • Goal of this (and most) projects time with tools

FIFA 18 • Realistic sports simulation – Contrast: Mario Strikers • User controls 1 player on team of 11 – AI controls others – Control switches to whoever has the ball • Players have attributes, based on real-life athaletes – E. g. , salary, speed • Rosters for all major (and many minor) club teams in world 3

Parts • • Part 0 - Setup Part 1 - Matches Played Part 2 - Champions Played Part 3 - Compare Players Part 4 - Match Data Writeup Submission Grading

Part 0 – Setup • Named “part 0” since don’t write up but foundational for rest of projects! 1. Install spreadsheet 2. Download dataset 3. Try it out http: //web. cs. wpi. edu/~imgd 2905/d 18/projects/proj 1/fifa-18. csv https: //www. kaggle. com/thec 03 u 5/fifa-18 -demo-player-dataset/data

Part 1 – Rating versus Age Analysis • Overall Rating versus Age • Scatter plot • Comma Separated Values (csv) Rating, 90, 88, Age, 22, 25, 26, • Tips – Select some columns – Charts

Part 2 – Rating versus Wage • Overall Rating vs Wage – Another scatter plot • But only 2 teams – Real Madrid – Paris Saint-Germain • Compute averages – Team, Overall • Tips: – Sort by column – Select some rows (e. g. , Real Madrid) – Compute summary stats – Can make separate “sheets”

Part 3 – Age • Analyze Age of all players • Histogram • Tips: – Drawing histogram – F 1 help, too • “How to make a histogram”

Part 4 – Speed by Position • Speed for preferred positions – Striker, Center mid, Center back, Goalie – All • Note, again computing averages • Bar chart • Tips – Filtering data – Again, can make separate “sheets”

Part 5 – Your Choice • Pick other data not yet analyzed • Analyze – Chart – Table – Summary stats • E. g. , other attributes (skill), clustered comparisons (leagues)

Write Up • Short report • Content key, but structure and writing matter • Consider: – Ease of extracting information – Organization – Concise and precise – Clarity – Grammar/English • Graphs/tables: – – – Number and caption Referred to by number Labeled axes Explained trend lines Message • Whatever tool you want (e. g. , Word, markdown) Generate PDF

Hints • Tips from last year http: //web. cs. wpi. edu/~imgd 2905/d 18/projects/proj 1/#hints • For most issues, will not be much penalty (yet) – Learning analytics pipeline is iterative – Will teach and reinforce • But start instilling good habits!

Grading • • • Part 1 (R v Age) Part 2 (R v Wage) Part 3 (Age HG) Part 4 (Speed) Part 5 (Choice) 30% 25% 20% 15% 10% • All visible in report! • (Late – 10% per day)

Rubric • • • 100 -90. The submission clearly exceeds requirements. All parts of the project have been completed or nearly completed. The report is clearly organized and well-written, charts and tables are clearly labeled and described and messages provided about each part of the analysis. 89 -80. The submission meets requirements. The first 3 parts of the project have been completed well, but not parts 4 or 5. The report is organized and wellwritten, charts and tables are labeled and described and messages provided about most of the analysis. 79 -70. The submission barely meets requirements. The first 2 parts of the project have been completed or nearly completed, but not parts 3 or 4. The report is semi-organized and semi-well-written, charts and tables are somewhat labeled and described, but parts may be missing. Messages are not always clearly provided for the analysis. 69 -60. The project fails to meet requirements in some places. The first part of the project has been completed or nearly completed, and maybe some of part 2, but not parts 3, 4 or 5. The report is not well-organized nor well-written, charts and tables are not labeled or may be missing. Messages are not always provided for the analysis. 59 -0. The project does not meet requirements. No part of the project has been completed. The report is not well-organized nor well-written, charts and tables are not labeled and/or are missing. Messages are not consistently provided for the analysis. .