Welcome! So far we’ve looked at what wins on 2 and 3 game slates, today we are going to look at 5+ game slates. We’ll come back to 4 game slates later, but for now we’re skipping them for 5+ gamers

Before I jump in, let me outline my criteria. I counted all slates from the end of the summer player break (August 26th) until the last Tier One tournament ended in December. The data includes any tournaments in Europe (including CIS) and North America, and does not include tournaments that were Asia/Oceanic or South America only, as there are often huge favorites and/or weird pricing in those and I didn’t want to skew the data (when SA teams are part of a bigger slate they were included). When I say SA I mean teams that currently play there, Furia and MiBR and classified as NA teams since that’s where they are now based out of.

I used tournaments that had total prize pools of $10,000+ and a buy-in of under $20 (the only tournaments over $10k on a given day were the big $10/12 and then sometimes the $222 or $180, the high dollar value tournaments are not included since they have so few participants).

What I looked at was what lineup constructions won slates/finished in the top 1% of slates compared to how often they were used overall. That latter piece is important because without it you may be led to believe that a certain lineup construction was better than another when in reality it wasn’t. To illustrate what I mean, if I told you (these are not actual numbers) that on 2 game slates a 3/3 lineup construction and a 3/2/1 lineup construction each won 50% of tournaments, which one would you say is better or are they equal? It’s a trick question, because you need to know how many total lineups there are of each. If 90% of the field is running 3/3 and 10% is running 3/2/1 (again, not actual numbers, just to be clear) but they each win half the time, the 3/2/1 construction would clearly be superior. Hopefully that makes sense.

The constructions I looked at are 3/3, 3/2/1, and 2/2. What 3/3 means is 3 players from 2 different teams. By default this means they are from different games and therefore cannot be a gamestack. 3/2/1 means 3 players from Team A, 2 from Team B, and 1 from Team C. There can be game stacking here, Team A and B can be from the same game, Team A and C can be from the same game, or Team B and C can be from the same game. 2/2 means 2 players from Team A, 2 from Team B (Team A and B could theoretically be opponents), and then either 2 from team C or 1 from Team C and 1 from Team D. Of course there are other lineup constructions possible, particularly on larger slates, but they’re not as common so I’ve grouped them all together as “Other”.

There’s a quick TLDR at the end again if you don’t want to sift through all the data and just want to see the takeaways. Let’s jump in.

 

5+ Game Slate Lineup Construction

We only have a 16 game sample size here, far and away the smallest of all the different slate sizes. On top of that, we have twelve 5 game slates, three 6 game slates and one 8 game slate, which complicates things even a little further. That said, let’s take a look and see what we can learn. The lineup construction was as follows:

Lineup Style 3/3 3/2/1 2/2 Other
Percent Used 4.32% 23.09% 42.22% 30.38%

As you would kind of expect, people 3 stack significantly less (note that a 3-1-1 falls into “Other”) as slates get larger. This is unsurprising, as theoretically the best player from each game is likely to be make the optimal lineup. However, the win rates dictate that getting that optimal lineup may not be so easy:

Lineup Style 3/3 3/2/1 2/2 Other
Percent Used 4.32% 23.09% 42.22% 30.38%
1st Place Finishes 6.25% 37.50% 43.75% 12.50%
Wins Minus Used 1.93% 14.41% 1.53% -17.88%

As we see, the larger stacks still end up winning more often than they are used, and not stacking as much (Other) wins far less. Why would this be the case?

My hypothesis, and I unfortunately don’t have data to back this up because we never have huge tournaments, is that because even the biggest GPP’s in CS:GO aren’t actually that big, the field is never big enough to where you need to be perfectly optimal on these big slates. On a 6 game slate, let’s say you pick one player from each game. This is an over simplification, but let’s say your 6 players each have a 60% chance to win their game, and an 80% chance to put up a “good” or better score if their team wins. Once you do the math out (.6 * . 8)^6 you end up with about a 1.2% chance of having all of your players win and put up a “good” or better game. Of course, players can have good games in losses and I simplified the odds, but the point is that you get a very low chance of your lineup all hitting. And keep in mind that even when it hits you’re still competing against all the other lineups that hit. Meanwhile, lets say you played a 3/2/1. Playing players on the same team obviously decreases the chances they all have a great game, but let’s say Player A has an 80% chance, Player B has a 70% chance and Player C has a 60% chance of having a “good” or better game if their team wins. That means if you run a 3/2/1 you have about a 3% chance of all your players having a “good” or better game based on the math I just laid out. You have almost 3 times the likelihood of having your whole lineup hit. This is a long way of saying, winning usually equates to good scores in CS:GO, but upside per team is capped. However, tournaments are small enough that the trade off of slightly limiting your upside for an increased chance of your lineup hitting is worth it.

The top 1% data essentially confirms what the above, here it is:

Lineup Style 3/3 3/2/1 2/2 Other
Percent Used 4.32% 23.09% 42.22% 30.38%
Top 1% of Lineups 7.59% 33.26% 38.62% 20.54%
Wins Minus Used 3.27% 10.17% -3.60% -9.84%

There are small shifts in the percentages, Other doesn’t look quite as bad compared to 2/2, but 3/2/1 is still underutilized. It is worth noting that this data is of course skewed towards 5 game slates, but it still pretty clearly shows that 3 stacks are king, until tournaments are huge at least. This data also helps alleviate the small sample size concerns a little bit, as the rates Top 1% rates are relatively similar to the winning lineup rates.

Lineup Building Takeaways

Once again 3/2/1 lineups are underutilized compared to how often they win. In the past I’ve typically built 2/2/2 or 2/2/1/1 on big slates, but I’ll definitely mix in some 3/2/1 after seeing this data. I won’t break out the data as it’s an insignificant amount of lineups, but the 3/2/1 are never opponents in the winning lineups. I don’t have an easy way to capture this data, but it stands to reason that playing opponents gets worse as slate size goes up, as they are inherently negatively correlated.

Summary

While you, and the field based on lineup construction, might assume that bigger slates mean moving away from 3 stacks, because the tournaments themselves are fairly small, you typically don’t actually need to find that completely perfect lineup to win. The field seems to try to do that though, as more and more players veer towards 2/2 or Other constructions, leaving 3/2/1 and even 3/3 lineups underutilized relative to how often they’re winning. I’ll be shifting some of my lineups on bigger slates to 3/2/1 based on this data.

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