Category Archives: Stats Theory

Jungler slash lines improve measurement of early-game effectiveness

TL;DR Because of changes to the jungle as part of Season 7, I am proposing a new way of measuring junglers’ early-game effectiveness.

Key Findings

Changes to the jungle for the 2017 season have created some loss of meaning in one of the oldest statistics used for professional play: CS Difference at X minutes. The addition of more small creeps in the raptor and krug camps has created wider variance in the value of a single creep score (CS), leading to inflated CS gaps for junglers without any real difference in the gold or experience gaps being generated.

These changes have some implications for how we should report on junglers’ early-game head-to-heads. Continue reading Jungler slash lines improve measurement of early-game effectiveness

EGR and MLR: New Team Ratings

Today I’m launching a pair of new statistics that measure teams’ performances in the “early game” and the “mid/late game”. These stats use complex modeling to assign an “early-game rating” (EGR) and a “mid/late rating” (MLR) to each team, which lets us quickly compare teams’ performances using single, straightforward numbers. The higher a team’s EGR, the better they have performed in the early game. The higher their MLR, the better they have done in the mid and late game. It’s that simple!

These stats will start showing up on the OraclesElixir.com team stats tables soon.

Keep reading to learn about how EGR and MLR are produced and what they represent, or skip halfway down for lists of team ratings along with some discussion and interpretation. Continue reading EGR and MLR: New Team Ratings