Using Player Data to Drive Intelligent Auto-Balancing of

Teams in Video Games or

Heuristic assignment of teams in multiplayer games

Amanda ChaffinPh. D. Student

Games + Learning Lab

8/24/2010 ~ 2

Superbowl XLVI

New York Giants (NFC)

21

New England Patriots (AFC)

17

1 2 3 4 Total

NYG 9 0 6 6 21

NE 0 10 7 0 17

Nielsen Rating 45 with 111.3 million viewers

8/24/2010 ~ 3

Superbowl XXIV

San Francisco 49ers (NFC)

55

Denver Broncos (AFC)

101 2 3 4 Total

SF 13 14 14 14 55

DEN 3 0 7 0 10

Nielsen rating 39 (74 million viewers and lowest Superbowl Rating since 1968)

8/24/2010 ~ 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)

8/24/2010 ~ 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

8/24/2010 ~ 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

8/24/2010 ~ 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

8/24/2010 ~ 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

8/24/2010 ~ 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

8/24/2010 ~ 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

8/24/2010 ~ 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

8/24/2010 ~ 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

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• Situational Awareness

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Questions

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