One Tricking vs Hero Maining In High Elo Overwatch: An Empirical Analysis

Given that the patch that is expected to murder mercy has dropped and that this season the ‘Performance Based SR’ has been removed in high ELO, I thought it would be a good time to throw my two cents into the over-saturated market of one-tricking discussion. I can’t provide a long manifesto about my personal beliefs on what people deserve when they buy a game — but I hope to provide some much needed data-driven perspective on the issue.

The topic of one-tricking has been discussed to death by everyone from pros to bronze heroes, and even Papa Jeff has weighed in on the topic several times. I have myself experienced the same frustration as Effect when I queue into Route: 66 offense with a player on my team with 100% of their hours on Symmetra. Because events like these are so memorable, it is easy to overestimate the percentage of your games that include onetricks. One quick disclaimer before I begin — if you are someone playing at lower ELO the results of this analysis might not apply to you — please consider this before commenting “LUL I HAVE 2 HANZO MAINS IN EVERY GAME I PLAY IN PLAT.” So, without further I am bad at words, here is my attempt at a more objective look at the concept of Hero-Maining and One Tricking.

Let’s start with some basic facts. In 1,062 accounts I examined playing in GM or higher on the NA ladder in Season 8, the average percent of time played on the accounts main was 42.8%. Put more simply, the average player played a little under half of their comp time on their mained hero. That average, however, looks pretty different if you look at it hero-by-hero.

The below chart shows some unsurprising trends — Symmetra, Mercy, and Sombra — three of the most mechanically unique heroes exist at the top of the chart. If you think about what drives someone to ‘hard main’ a hero in GM, there are probably two main drivers — 1) Mechanical Uniqueness: a hero with mechanics that do not translate well to other heroes will be more likely to be onetricked, since the player won’t have universal skills in the game. 2) Off-Meta Use: If a hero is not often picked, say Symmetra, then you are more likely to be able to pick her in any game than say Dva, since there are probably other people on your team who want to play Dva.

Symmetra Mains are the most hard-core.

In other words — there needs to be motivation to onetrick a hero (mech uniqueness) and then the ability to onetrick the hero (off-meta pick). These theories generally work for what you see here — the five heroes with average play times above 50% are Sym, Mercy, Lucio, Sombra, and Reaper. Sym, Sombra, and Mercy all fit the mechanical uniqueness (and some fit the off-meta), where Reaper and Lucio are definitely off-meta right now.

I was able to examine how accurate my ‘mechanical uniqueness’ theory was by examining winrate differentials. If Mercy is truly mechanically unique, you would expect that there would be a big drop-off in a Mercy main’s ability to win when forced of his / her main hero.

Based on these numbers it looks like Symmetra mains are the worst at ‘filling’. It also looks like my color scheme got messed up — but I can’t bring myself to recode those now.

The above chart looks at this Winrate differential by hero. Unsurprisingly, Symmetra mains appear to be the worst at filling. Mercy, despite being always lambasted as the ‘hero for people who can’t actually play FPS games’, only has the 6th worst fill win-rate, about even with Hanzo players. To give these numbers some context, the average winrate for players in my dataset on their main was 58.2% and the average winrate for players off their main was 50.5%, with the average Winrate differential being 7.7%.

For the above analyses I considered all players who ‘mained’ a hero. To isolate the issue of one tricks — Out of the dataset of 1,064 players, I selected only players who have at least 80% of their playtime on their most played hero — the results below show the breakdown of the onetricks in GM by hero. Using this definition — I found that of my 1,062 GM players 105, or roughly 10%, of them ‘One-Tricked’ a hero. The specific breakdown of these 105 players can be seen in the chart below — believe it or not Mercy is the most onetricked hero in NA GM ladder.

So what is the impact that these onetricks might have on their games? The below charts examine that question by looking at how well these onetricks do at ‘filling’ when they have to. Not controlling for map or other items, the first chart looks at what the average win rates of one tricks are when they are playing on their main vs when they are filling. You can see here that Tracer onetricks (out of the four heroes displayed) do the worst job at filling when they have to. My advice based on this, if you have a Tracer one trick on your team, let that person play Tracer.

The next chart is a different way at examining the problem — the question it answers is ‘how much worse are onetricks at filling than regular players’? The answer — by hero- is a lot worse. Tracer onetricks fill with a 35 percentage point lower winrate, but regular tracer mains fill with only a 3.5 percentage point lower winrate.

Conclusions & Next Steps

With the caveats that my data is incomplete and only related to GM players in NA — there are a few key takeaways I’d like to mention.

First on the Prevalence: the proportion of onetricks in GM seems very high to me — if 10% of the population are onetricks, and you assume you are not one, then the probability that you have at least one onetrick in your game is 68.6% (I haven’t done math since the GMAT, so maybe someone should check that — 11 slots with 90% chance of not being a onetrick). This number may seem high, but remember the vast majority of these onetricks you encounter will be Mercy or Dva or Zenyatta players, so you might not remember them as vividly as the Sym or Torb players.

Second on the Impact: I said earlier that the average percentage point differential in winrate for players forced off their main in GM was roughly 7.7% — that number changes to 21.6% for one tricks. This lack of flexibility, in a game where creating and adapting specific comps to specific maps and enemy strategies is essential, definitely has a negative impact on the game.

Next Steps: While 1,000 players is a fairly good sample size, there are still issues that cannot be addressed fully with limited data. For example — it would be interesting to know how win-rate differentials compare for mercy mains who swap to other supports vs other roles, or how the average healing/10 varies for people who main mercy vs people who just fill on her. The nice thing about my current dataset is it was all pulled from the same patch (Same patch OWL is being played on), and future data will be mixed based on the old and new meta. Hope you enjoyed reading this — if you think I missed something please let me know!