League of Legends

EU Masters Power Ranking post Day3 – 2019 Spring

LeagueofLegends11 - EU Masters Power Ranking post Day3 - 2019 Spring


How it works in general – I compare EUM teams based on the level of the teams against they win or lose every playday. Each team has a score similar to a elo. The full explanation is at the end of the post.

How Starting score works for EUM – In cooperation with Clockwoork and Megalodontus who write on LoLEsports about the EU Masters teams, I realized the starting PR based on:

  1. Clockwoork - EU Masters Power Ranking post Day3 - 2019 SpringClockwoork & Megalodontus Ranking
  2. ERL Score: every team got a score based on the rank it finished the regular season compared to how many participants every ERL has
  3. Bonus on previous EUM editions final rank.

Feedback or ideas for some new kind of graph or stat are appreciated.

Power Ranking after Day3

New – Updated graph with chart ranked from left to right by the current highest score, with an indication next to each team's name showing their movement in the rank.

Teams with a * have 1 more game played

Power Ranking by Groups

  1. Group C: average score 928,39
  2. Group B: average score 924,21
  3. Group A: average score 921,02
  4. Group D: average score 918,64

47130qver0t21 - EU Masters Power Ranking post Day3 - 2019 Spring


Best Win Score (plus percentage increase on starting score)

  1. Ventus Esports: +123 score | +3.95%
  2. Fnatic Rising: +100 score | +21.14%
  3. Splyce Vipers: +90 score | +3.59%

4d9qk9ncs0t21 - EU Masters Power Ranking post Day3 - 2019 Spring

Teams with a * have 1 more played game

Predictions on Day4 (based on Power Ranking score)

fusievabr0t21 - EU Masters Power Ranking post Day3 - 2019 Spring


To Note – Some scores sometimes aren't the exact sum of their addends cause of rounding not showed in the graphs.

Every feedback to improve this power ranking and how it should be shown will be appreciated.


More info on how it works

I divided the teams of the EUM into a starting ranking based on:

  • I normalized the average score in a range from a minimum of 750 points for the lowest score to a maximum of a 1.000 score for the highest one.
  • The ranking is updated on each match.
  • The formula is exponential.

This is an analytical power ranking because it expresses the value of the teams through a score. The score changes during the tournament according to the match results between the teams: it is not based on the victories and the defeats itself but on how these come through, like in other traditional sports. This power ranking is based on the level of the teams against which you win or lose in that week. Winning against a lower level team scores less than winning against a superior team. Likewise, losing against a lower level team will lose more points than losing against a superior team.

The sum is not zero cause the losing team loses half of the amount of the winning one.

I will also introduce the best team of the week or the roster that will achieve the most points differential compared to the previous week, and the worst: Best Performing Teams of the Week and Worst Performing Teams of the Week. Last, but not least, the team that it has obtained the best positive score in a single match: Biggest Score Wins of the Week. There won’t be the Worst Defeat of the week because it clearly is the team who lost to the Best Win one. I will also add the best Group.

Source: Original link

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