Articles:Objective Score - Analyzing Which Teams Prioritize Objectives In The NA LCS
|Objective Score - Analyzing Which Teams Prioritize Objectives In The NA LCS|
Statements such as “CLG doesn’t care about objectives” or “C9 are extremely objective focused” have been echoed by LCS casters, friends, and redditors, but there has been very little evidence or statistics to back up these claims. I am not saying these things are not true, but rather quantifying this data will grant us a clearer understanding of what exactly makes these teams different. That being said, it is very hard to quantify how a team treats objectives. This article tracks my previous attempts to quantify objective priority in teams and my proposed solution for a statistical representation of objective prioritization - Objective Score.
Past Attempts: First Blood/Towers/Dragons
However, when collecting these statistics, I realized how inaccurate they can be. Two examples come in mind: two teams trading early towers, or a team scoring first blood from a botched level 1 invade. These don’t translate into how much teams prioritize objectives: in the push situation both teams valued pushing the same, one only got it a few seconds before. In the invade situation, it was just happenstance that they got First Blood. This data was very interesting, but I thought there had to be more statistics out there in order to show how much a team values objectives.
Next Attempt: Comparing Total Dragons and Towers
As I was looking for other options to describe objective priority, I turned to total dragons/towers killed in the Summer Split for these teams. I thought this would be a good measure in regards to how teams emphasized these objectives throughout the game, not just the first kill. However, after tallying the stats thanks to Leaguepedia, the data was extremely underwhelming.
For example, Cloud 9 had 253 tower kills while Velocity had only 122. I knew this wasn’t because C9 prioritized towers twice as much as Velocity, but because C9 won so many more games (thus securing more towers and dragons than losing teams). What I had to do was find some context to these numbers. They couldn’t be compared to each other due to the high disparity from win-loss and game time; instead, they should be compared to the “average team” estimated using win-loss averages scaled based on a team’s game time.
Solution: Comparing total dragon and towers to weighted estimates
In reading the above chart about dragon kills we can start to see who prioritizes them and who doesn’t. TSM and C9 both have a really high priority on dragon, both exceeding their estimates greatly, as well as earning the first dragon in a majority of games (75% and 57% respectively). Within the same dragon chart, we can see that CLG’s dragon priority is very low, and Dig’s and CST’s dragon priority is moderately low. This reaffirms the first dragon data as CLG and Dig have the lowest percents at 25% and 36% respectively. With similar reading of the tower chart we can see that C9, TSM, and Dig are the big pushers while CLG, CST, and VES end up with lower than average towers for their respective win-loss ratios.
Conclusion - “Objective Score”:
Focusing on the relationship between estimated values (based on win-loss and game time) and actual values gathered from games, we can create a “score” that accurately articulates a team’s objective priorities. Subtracting these values (Actual-Estimate) can get a figure I like to call “Objective Score,” which follows this scale:
This objective score can be easily compared on the horizontal graph seen below:
Let me know what you guys think about this article in the comments!