Data Analysis for Game Development

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Presentation transcript:

Data Analysis for Game Development Administrative IMGD 2905

Outline Background Admin Stuff Motivation Objectives

Professor Background (Who am I?) Mark Claypool (professor, “Mark”) Professor Computer Science Interactive Media and Game Development Research interests Multimedia performance Congestion control (protocols, AQM) Wireless networking Network games Current gamin’ Overwatch League of Legends Oxenfree Data analysis!

Student Background (Who are you?) Year? Major? IMGD Art or Tech Other Background? Statistics Probability Tools? Python Excel Platform of Choice? Windows Linux Mac

Syllabus Stuff http://www.cs.wpi.edu/~imgd2905/d18 Class: M, T, Th, Fr 10-10:50am Office hours (FL B24): Mo 12-1pm, Tu 2-3pm, Th 9-10am, Fr 12-1pm Or by appointment Email claypool@cs.wpi.edu (me) imgd2905-all@cs.wpi.edu (class + me)

“Even You Can Learn Statistics and Analytics” Text Book D.M. Levine and D.F. Stephan “Even You Can Learn Statistics and Analytics” 3rd ed. Pearson, 2015 Unfortunate name, but good content  depth to provide foundation for analytics Good examples, but not game-centric

Class Topics Data analysis tools and pipeline Statistics Visualizing and presenting data Probability Hypothesis testing Regression Apply topics to game data! Commercial and custom New and old

Course Structure Prerequisites Grading College algebra No programming, stats, probability expected No game analytics experience required Grading Exams (30%) Projects (55%) Presentation (10%) Participation (5%) On the Instruct Assist Website: https://ia.wpi.edu/imgd2905/ Authenticate with WPI login and password

Exams 2 exams, 30% of grade total Mid-term, Final (non-cumulative) Closed-note, Closed-paper, Closed-friend Generally, on material in class, but may have some parts from project  Test mastery of concepts that may not be evident from project reports

Projects 5 projects, 55% of grade total Last project slightly larger Do game analysis on actual game data! Use game analytics pipeline Typical flow for game (and other) analytics Common tools used for analytics Multiple instances of analysis Apply, become skilled with methods of synthesis, interpretation, presentation “Lather, rinse, repeat” Project 1 – today!

Presentation Presentation Peer-critique Everyone 1 presentation In-class, maximum 4 minutes long Leave time for critique Content drawn from projects When? 1 person per class Assigned at random Stay tuned for schedule Feedback to become better presenters! Everyone will provide for every presenter Short, written form Presenter will review Turn in short, written reflection Reflection due 1 week after presentation 10% of grade

Participation Showing up to class matters Come to class! Being engaged in class matters Put down your phone/laptop! Ask questions, answer questions 5% of your grade But much bigger indirect effect!

Slides On the class Web page PowerPoint and PDF Caution! Don’t rely upon slides alone! Use them as supplementary material (come to class)

Timeline Tentative timeline for dates for exams and projects In order to help you plan http://www.cs.wpi.edu/~imgd2905/d18/timeline.html Will notify if update

Why This Class?

Why This Class? Goals Objectives Gain proficiency using modern tools for data acquisition and analysis Understand basic probability and statistics as it applies to data analysis Develop skills for presenting game data analysis both orally and in written form Use spreadsheet to analyze and visualize game data Use scripting language to extract and clean data recorded from game Apply summary statistics to game data Compute probability distributions for game data Write reports with graphs and tables illustrating analysis of game data Present game dataset report using appropriate visual aids

Why This Class? – Other WPI IMGD requirements Gotta take Math/Quantitative Science Statistics and Probability useful for game design and development Game Analytics similar to other forms of analytics (e.g., Data Science) Fun! Game analysis increasingly important (jobs!)

Jobs Game Play Data Analyst, Sony Interactive Entertainment Duties Advise, define implement gameplay data to ensure understanding of player experience Provide insights that impact game design and improve quality Create and maintain player segmentation that allows understanding of engagement and spending Mine data sets and develop dashboard for live service teams, game developers Devise and implement A/B experiments to test acquisition, engagement Present finding and provide recommendations Requirements BS/BA degree Stats, Math, Econ, CS or related Experience with SQL Experience with data visualization packages Experience with statistical software Experience with Amazon cloud services Have created and presented visualizations and insights to various business groups Passion for video games preferred

Jobs Analyst, Riot Games Duties Requirements Aggregate and analyze petabytes of game data from various sources Prep data for deeper analysis and/or reporting Organize collected data into reliable intel that informs Rioters to improve player experience Work with decision-makers to understand goals, identify opportunities, and inform decisions across company Create awesome Requirements BS/BA degree Stats, Math, Econ, CS or related Graduate degree preferred Business savvy Technically adept SQL, Python Excel, PowerPoint Communicator Reports clear, and concise Presentations to variety of audiences