Category Archives: Stats Theory

NA, EU, and LCK Gold Difference Charts

The graphs below chart gold differences over time in LCS teams’ last six games (weeks 6 through 8 of the 2015 Summer Split) and in LCK teams’ last two weeks (weeks 8 and 9 of the 2015 Summer Split).

Note: The timelines only run to 50 minutes, even if a game went longer.

NA LCS

EU LCS

LCK

Pick My Next Stat Exploration

Let me know what stats you’re most interested in seeing next. See below for more detailed descriptions of the options I’ve given, or make a suggestion!

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Team Kill Efficiency
This stat measures the average number of objectives a team takes per kill, where an objective is a Tower, Dragon, Baron Nashor, or Inhibitor.

In-depth Conditional Win Rates
I will explore the win rates associated with some very specific game scenarios. For example, how often does a team win when taking the first Dragon in the first five minutes of the game? What are the win rates in 4-minute Tower trades for the teams that kill Bot vs. Top Tower? What are the win rates for players with Flash on D vs Flash on F? Win rates would be provided overall and separately by NA and EU LCS, LCK, and LMS.

Capitalization on Baron buffs
This stat would measure the average number of Towers + Inhibitors teams have been able to take during the 3-minute window after taking a Baron kill. Note: I only have this data for NA and EU LCS at this point, but will have it for other leagues in the future.

Bloodletting: Kill Pace and Target Selection in MSI and Regional Playoffs

The 2015 Mid-Season Invitational was an absolute bloodbath, with 62% more kills per minute than the LCK playoffs and a way faster pace than anyone could have expected, based on how each region’s playoffs played out.

The chart above compares the average Combined Kills per Minute (CKPM) from each major region’s playoffs and the entire Mid-Season Invitational tournament. (The LPL unfortunately can’t be included because the league does not release its match histories publicly.) As an added bonus, I’ve broken out average target selection for each region.

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