data analysis & balancing meeting thibault coupart avril 2015
TRANSCRIPT
Data Analysis & BalancingCoupart Thibault - 10/04/2015
PresentationData Analyst / Game Economy Designer
- Master in engineering/town planning- DU in Game / Level Design- Complementary Formation in Hadoop/Programmation skills
- Internship data analyst at Corexpert
- Data analyst at Adictiz
- Current- data analyst at 505 Games
Plan1. Definitions & concepts
2. Case Study 1 - Arcade Game
3. Case Study 2 - City Builder Game
4. Conclusion
Intro
Current mobile game trend (subjective opinion)
?
Definition & concepts
Definition & concepts
A few important words :
- The balancing fundamentally is about “tweaking” existing game variables in order to increase the game experience.
- You always want to have the reward accorded with the difficulty, the investment accorded with the quality, the cost accorded with the power.
- Data analysis helps a lot to spot areas of the balancing that need improvements, whereas a better balancing usually increase the commercial success of the game
- This statement is even more true in the world of Free-to-Play, where it is all about convincing the player that the ing-game purchase worth his real money.
Definition & concepts
A simple way of visualizing the balancing in a free-to-play Economy
Not good (too easy)
Not good (too hard)
Good !
Case Study 1 - Arcade game
Case study 1 - Arcade game
2D casual Games where you need to reach the highest distance possible with your dog ! (tap to fly)
Case Study 1 - Arcade Game
Unlock
Buy
Accelerate Revival Reroll
PLAY
Content
BUY
VIRALIZE
Case Study 1 - Arcade Game
Distribution of players score for each levels of the Game
Case study 1 - Arcade game
Retention by level and fail rate
Case study 1 - Arcade game
Gate 1 where you need to pay 500 coins
Tutorial
Most important retention losses
Retention by level/steps and Retention as percent from previous
Case study 1 - Arcade game
Changing the wheel reward balance is also a part of the balancing.
25% 25
45% 45
5% 100
20% 5
50% 50
5% 100
Original values New values
(expected gain / roll : 31) (expected gain / roll : still 31)
Case study 1 - Arcade game
+4 pts post lvl 3
+8 pts post lvl 7
+3 pts post lvl 12
Case study 1 - Arcade game
Introducing the “bad” roll on the wheelwith the 2.5 release
Average Rerolls used by players
Case study 1 - Arcade game
+5 points retention at Day +1 and after
Case Study 2 - Builder game
Case study 2 - Builder Game
Case study 2 - Builder Game
Percentage from First - Economy Variables
Case study 2 - Builder Game
DPS/ Health of Units unlocked throughout the game
Case study 2 - Builder Game
DPS/ Health of Turrets unlocked throughout the game
Case study 2 - Builder GamePO
WER
PROGRESSION
Defender > Attacker; hard to progress easily at this point in the game; correspond to HQ lvl 2 / 3
Case study 2 - Builder Game
Retention of users according to Campaign Mission with Fail Rate- February 2015
Most important drop
Case study 2 - Builder Game
Researching
Negative side effect - the investment is a deception
Case study 2 - Builder Game
Supplies invested in each units for each users who unlocked the said unit - February 2015
(Total number of Purchases * Unit Price) / Distinct users who bought it at least once)
Underused
Conclusion
Conclusion
- The balancing has became a big topic in the free-to-play economy, and pretty much every gameplay needs a decent balancing now to succeed
- A data analyst will have many benefits by matching balancing data with user data, and the opposite is true : a game designer / balancer will use user data to orient his balancing !
- QUESTIONS
Thanks for your attention!
ContactCoupart Thibault
Mail : [email protected]
Linkedin : https://www.linkedin.com/hp/?dnr=oiFedA9QkZ4bzJnRoqEvqAHABQ43iJ4WcI2W&trk