Team Play Visualizations of NA LCS Spring Split 2018

I’ve recently been starting to mine through a bunch of data on the 2018 Spring Split for the NA LCS, and trying to find good ways to visualize differences between teams and overall trends that lead to stronger performances. One of the trends that I’ve been able to look at is how a team racks up their assists throughout games during an entire season.  The look at assists rather than kills definitely favors teams that have more team-fights or multi-person skirmishes, and may be a better metric than kills for a team’s synergy and ability to play together (an increasingly important part of pro play). I will be looking at kill distributions in the near future (hopefully), and it might also prove insightful to look at how assist and kill breakdowns differ. Below, I’ve included each team’s assist histogram displaying their assists from the entire season binned in groups of five minutes of play:

Looking at the histograms for all the teams in the league, I’ve provided some thoughts on each team’s distribution as well as a few thoughts on overall trends. There is definitely more to unpack here than I provide with my short analyses (which range in content), and in the coming weeks I’ll be taking a deeper dive on some of the more interesting teams (in conjunction with some ideas I talk about here. Feel free to reach out with questions, comments and feedback, it is very useful and exciting to engage with readers! But without further ado, here is a brief look at the league and its teams.

  • Mean number of assists (per team): 470.4 || Median: 464

  • Looking at the similarities and differences between the top and bottom teams, it doesn’t appear right off the bat that there is a significant difference in the way the best and worst teams play overall as a team. There does (not surprisingly) appear to be a correlation between number of assists and wins. However, there are certainly teams who performed well with a radically different number of assists throughout the season.

  • The large differences in teams’ play styles indicate that different teams across the league may thrive and fail in different types of metas that play to their different strengths and weaknesses

  • It would be awesome to compare these charts to those of the top teams from the LCK and LPL to see if the best teams in the world are playing differently than the NA LCS teams, and if there is the same variation in play style abroad.

  • 100 Thieves ended up finishing the season in first place with a very average number of assists. To me, this indicates that there must be some measure for the quality of assists or kills that better influences victory rather than pure number. Interestingly, 100 Thieves has the most kills after 45 minutes which might signal an overall reliance on, and skill in, late-game team fights and macro. 100 Thieves may struggle in a more early-game meta, and may have been more evenly matched with opponents than their record suggests. Between 20 and 40 minutes, 100 Thieves assist frequency does not change significantly which is not typical of the league. This may indicate a unique play style that doesn’t emphasize a strong building mid-game aggression.

Total assists - 478 || T-1st PlaceTotal assists – 478 || T-1st Place

Total assists - 618 || T-1st Place

Total assists – 618 || T-1st Place

  • Echo Fox had the most assists by far, with 80 more than the next team (CLG), and nearly 300 more than Optic Gaming. In this regard, it shouldn’t be surprising that Echo Fox did incredibly well. With only 12 solo kills throughout the season (still the most of any team), Echo Fox did have strong synergy among its starters. Although much attention was brought to Dardoch’s early influence, Echo Fox didn’t have more early-game assists than most other teams. Similar to Team Liquid, Echo Fox seems to succeed most during 25-35 minutes and has a dip just before in “productivity” between 20-25 minutes, an interesting note. However, unlike Liquid, Echo Fox seems to push into the mid-late game rather than losing aggression from 10-25 minutes.

  • Clutch Gaming has surprisingly few assists for a team that finished in the top five. They have one of the most parabolic histograms, that differs significantly from TSM, a team with equal success. They seem to have a mid-game focus, and although they were successful, the low number of assists for the team despite having many games above 40 minutes indicates potential issues with team fighting and coordination. However, they did tie for 3rd place, so they obviously played very well through their carries without having a lot of assists, which may indicate a tendency to skirmish late-game rather than all-out team fight. More investigation would certainly illuminate this.

Total assists - 420 || T-3rd Place

Total assists – 420 || T-3rd Place

Total assists - 506 || T-3rd PlaceTotal assists – 506 || T-3rd Place
  • Cloud9 has one of the more interesting assist distributions of the top five teams. During the Spring Split, Smoothie was lauded for his early game roams, and the mid-jungle synergy seemed strong. This shows in the high number of assists from 5-15 minutes (typically laning phase). Besides this focus on the 5-15 minute range, C9 seems to have strong mid- and late-games. With a roster that has played multiple seasons together, the above-average number of assists and solid team-fighting ability are not too much of a surprise. With somewhat of a boom-and-bust season, I’d be interested to see if their play style changed from the first half to the second half of the season.

  • Team Solomid exhibits one of the most interesting, and to me, clear-cut strategies of playing for the late game (with a tail from exceptionally long games). The only team with a similar number of assists after 30 minutes is Cloud9, but they don’t exhibit the same sort of crescendo to mid/late-game team fights around 30-35 minutes. As with 100 Thieves, this seems like a risky play style, heavily reliant on team-fighting skill and less reliant on generating early advantages to snowball through the early-game. Even with a late-game focus, TSM has an average number of assists and if they encounter an early-game meta, they may struggle more than other teams.

Total assists - 482 || T-3rd PlaceTotal assists – 482 || T-3rd Place
Total assists - 450 || T-3rd PlaceTotal assists – 450 || T-3rd Place
  • Team Liquid has an assist distribution that peaks at the end of the early-game and then peaks again at the end of the mid-game. They have the fewest assists after 40 minutes, which means that they win and lose quickly. They seem to rely on their ability to outplay opponents at the tail end of the early-game and laning phase with superior team play that may include early team fights and skirmishes with fewer team members. For a team that has such skilled laners, this seems to be a good strategy— quickly leveraging of their early advantages and power spikes. When they cannot beat opponents through this early dominance, they seem to stall a bit and vie for mid-game team fights rather than stalling for full-on late game fights.

  • Counter Logic Gaming finished the season in 7th place, but with nearly 70 more assists than the average team. They have a fairly strong mid-late game focus that most closely resembles 100 Thieves’ distribution. With a squad that has played together for a few splits (minus Aphromoo now), the high number of assists is not necessarily surprising, and this may show that CLG’s spring placement was abnormally low for their play, or that other factors such as individual play led to their high number of losses. It’s impossible to know by looking at this one graph, so CLG is definitely a prime candidate for further investigation.

Total assists - 538 || 7th PlaceTotal assists – 538 || 7th Place

Total assists - 446 || 8th PlaceTotal assists – 446 || 8th Place

  • FlyQuest has a large focus on 20-35 minutes, where their aggression does not change a significant amount. This lack of change in assists over time is another trend that we see with Golden Guardians’ mid-game, and maybe this is some signal for a lack of decisiveness that may come with a lower placement. It could also just be a result of the team trying to stall an early deficit to late game! The stark drop of assists after 35 minutes is similar to Team Liquid, which indicates an overall aggressiveness that may not be backed up by the strong individual and team play that Liquid has. Flyquest is a team that went through significant changes throughout the season, so it would be interesting to see their change over time with Keane vs. Fly, and even Stunt vs. JayJ.

  • Optic Gaming: Analysts and commentators may have mentioned it throughout the split, but this chart shows to me that Optic probably maybe should have finished in last place for the split. With the fewest assists throughout the season, Optic does have a signal that shows an emphasis on mid-game and late-game team fights that might lead to the longer game times you can see (similar in part to TSM). Optic seems to have a mid-game focus without great team play that appears to lead to longer game times— for a team that went through roster changes and inconsistent play, this strategy did not prove fruitful for the team, and might not bode well for summer split (but I hope they do well!).

Total assists - 354 || 9th PlaceTotal assists – 354 || 9th Place

Total assists - 412 || 10th PlaceTotal assists – 412 || 10th Place

  • Golden Guardians finished last during the season, but are interesting because of their early-game coordination. They have more assists between 10-15 minutes than any other team besides Liquid, which is an odd trait for a last-place team to have. Their overall assist frequency and numbers also most closely resemble Clutch Gaming, who finished 7 places higher in the standings. Whether this indicates that Golden Guardians should have finished higher or Clutch should have finished lower is a question of looking at the data in different ways, or at different data. Golden Guardians is another prime target for further analysis, especially since they have found increased success during the summer split.