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Amanda Chaffin Ph. D. Student Games + Learning Lab

Using Player Data to Drive Intelligent Auto-Balancing of Teams in Video Games or Heuristic assignment of teams in multiplayer games. Amanda Chaffin Ph. D. Student Games + Learning Lab. Superbowl XLVI. New York Giants (NFC) 21. New England Patriots (AFC) 17.

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Amanda Chaffin Ph. D. Student Games + Learning Lab

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  1. Using Player Data to Drive Intelligent Auto-Balancing of Teams in Video Games orHeuristic assignment of teams in multiplayer games Amanda Chaffin Ph. D. Student Games + Learning Lab

  2. Superbowl XLVI New York Giants (NFC) 21 New England Patriots (AFC) 17 Nielsen Rating 45 with 111.3 million viewers

  3. San Francisco 49ers (NFC) 55 Denver Broncos (AFC) 10 Superbowl XXIV Nielsen rating 39 (74 million viewers and lowest Superbowl Rating since 1968)

  4. Lopsidedness • Not just in sports – voter turnout much higher in close elections • Lopsided classrooms lead to misery • Half the class is graduate level computer scientists • The other half cannot program • Frustrating, to the extreme! • Video games, in particular, FPS (First Person Shooters)

  5. RageQuit! • Term coined back in IRC days • Quickly moved to video games (and became an official term with developers) • Quake 2 • Unreal Tournament • According to a recent (unofficial) survey by Valve Coorporation, players RageQuit due to • Skill imbalance • Team disharmony • To help combat the issue, autobalance was born

  6. Current Autobalance Approach • In game lobby, create teams by number, not by skills (3v4, 6v6, etc) • In game, autobalance if: • Players drop out (original implementation • Score is very unbalanced (added later) • Autobalance typically takes best 1 or 2 players from winning team and switches with 1 or 2 players from loosing team

  7. Players HATE autobalance (not the idea, the current implementation) • Battlefield: notorious for switching best players with best players (what was the point) • TF2: Will switch players, regardless of score, skill or even role in the middle of a round • Section 8: Prejudice: biases towards keeping friends together, means random players have less chance • Call of Duty 3 – autobalance buggy, does not work properly, does not work on ranked servers at all

  8. Typical Definition of Good Players • Measured by a kill/death (k/d) ratio • Can be lifetime • Most often, just that map • Problems with the approach • Can be skewed easily • Play only against less skilled players • Play only against greater skilled players • Only addresses individual kill skill and not teamwork

  9. Redefining “Good” Players • Or, more to the point, expanding what defines a good player • Takes into account • K/D ratio • Team work • Shooting accuracy • Sound tactical decisions • Situational awareness • Attempting to determine what “role” the player fits best

  10. Left 4 Dead: Running Example • Cooperative horror survival FPS • Created by Turtle Rock Studios • Purchased and produced by Valve Corporation • 4 game modes • VS mode • 2 teams (up to 4 players per team) • Take turns on each level as survivor and special infected • Survivor goal: get the team to the saferoom • Special Infected goal: stop the survivors

  11. L4D: Weighting Player Skill • From Steam data, build player profiles and abilities according to skill • Leads to categorization • Leader • Tactician • Teamwork • Shooting Skills • General Gameplay Skills • VS Skills

  12. Intelligent Auto Balance Rules • Each player rated for each categorical set • Teams divided into equal (or close to) distribution of players • For each category • Top two players on opposing teams • Rest divided evenly between teams

  13. Situational Awareness

  14. Questions • ?

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