Tag Archives: Huhi

Academy Standouts: 2020 Spring Week 4

Academy Standouts highlights the players who performed best in the most recent week of NA Academy play.

Previous Academy Standouts:

If you want to track your favourite team’s Academy performance throughout each split, you can also check out the Academy stats pages, starting with 2020 Spring regular season player stats and team stats.

Ablazeolive, Mid, Golden Guardians

Ablazeolive is back for his third Standouts feature slot in four weeks, and this time his team had the results to show for it, taking down CLG Academy and then pulling an upset on DIG Academy. With powerful control play, Ablazeolive has been making a very strong case for himself as one the best Mids in Academy this year.

Ablazeolive Stats, 2020 Spring Week 4
Numbers in parentheses are rank within own position.

  KDA KP GXD10 DPM DMG%
W4 23.0 88.5% +168 542 34.8%
Total 3.6 85.4% +222 593 34.1%

Continue reading Academy Standouts: 2020 Spring Week 4

Improving CSD – A better way to measure effectiveness in lane

The Creep Score Difference statistic is commonly used to evaluate a player’s laning phase; however, it’s far from a perfect stat. One of the main problems I have with the stat is that it doesn’t account for the champion matchup, which may give each player advantages or disadvantages before the game even starts.

To account for the strength of matchups in CSD, I have created a matchup-adjusted CSD stat which is calculated by taking the actual CSD and subtracting the matchup’s average CSD from it.

Adjusted CSD = CSD – Matchup CSD

Since this formula uses matchup averages for CSD, it is important to set some limitations on what can be used as the matchup average. I’ve set the sample size limit for each matchup to 5 games: if a matchup has been played 5 games or more, then the average CSD over those games will be used, but if the matchup has been played for fewer than 5 games then the matchup CSD will be registered as 0, meaning that the adjusted CSD will equal the actual CSD.

One issue that arises from implementing a minimum number of games for a matchup is that there may not be enough data on a lot of the matchups. While I only want to use pro play for the matchup CSD value, I also need to ensure that I can get a value for almost all matchups. To do this in the calculations that follow, I’ve decided to use data from the CBLoL, LCK, LCS, LEC and LMS. All of the data used from these leagues is from games played on the same patches (9.01, 9.02, 9.03, 9.04, 9.05) during the Spring Split 2019 regular season.

To illustrate, the size of the adjustments that can be made using this approach, the tables below show the 5 matchups for each role that have the largest average CSD at 10 minutes with a minimum of 5 games played. Continue reading Improving CSD – A better way to measure effectiveness in lane