League of Legends, like many competitive games, relies on sophisticated systems to gauge player skill, and for the entirety of the game's history, ELO dictated how we maneuver around the ranks and climb our way up the ladder. This makes insight into how the Elo system works in League crucial to optimizing our approach to the game and understanding the significance of the upcoming TrueSkill 2.
Contrary to popular belief, ELO isn’t made by Riot and isn’t solely reserved for League. It is actually a rating system conceptualized in 1960 to better organize professional chess tournaments and rank players based on their performance. Its inventor, Arpad Elo, who was a mathematician and a chess player himself, sought after a method of making the game more accessible for newcomers while ensuring the integrity of high-level play, and so the Elo system was born.
Let’s explore briefly how it operates:
Each player is assigned a number to represent their skill level. Each new coming player begins their journey with the same Elo rating and wins or loses points based on his Elo and his opponent’s Elo.
To put it simply; if you win against an opponent of a higher rating (where you’re less likely to win), you’ll gain more points than what you’d gain after a victory over a lower-rated player. And since these points are deducted from the opponent’s score, if you lose against a weaker opponent you’ll lose more points than what a defeat against a higher-rated opponent would net you.
This way you’re rewarded for beating the odds conquering tougher players and funneling all of your efforts into every game as your rating is updated after each match and any loss would cost you your precious points (we’ll examine the technical aspects of this system later in the article).
Seeing the success of this system and its impact on professional chess, many fields jumped aboard and adopted it as their standard, from football leagues to AI models, and especially multiplayer games.
Since ELO was modeled around chess, which is a 1v1 game, Riot had to tweak a couple of knobs to ensure this system functions as intended to regulate competitive play in a multiplayer setting.
To adapt it to the 5v5 nature of League, ELO needed to be more than just a metric of skill but also a tool to organize matchmaking and structuralize the ranked ladder. Your Elo gain/loss is now determined by averaging out the collective elo of the enemy team and rating you based on that, as well as only matching you with players of similar skill levels whose Elo rating isn’t distant from yours.
While the rating system Riot uses is clearly inspired by ELO from chess, “ELO” isn’t a term coined by Riot Games (There is no record of them referring to the rating system used in League as “Elo”). The official term is MMR or MatchMaking Rating which is ALSO a number representing your skill level that changes after each match and functions pretty much exactly like ELO does.
In reality, the word “ELO” is widely used by the League community *(and Riot itself)* not to quantify a player’s skill level, but to denote a rough estimate of the player’s skill being more synonymous with RANK than individual skill; We demonstrate this using expressions like High Elo or Elo Hell to point out a range of ranks sharing similar traits and a comparable player experience (for example High Elo represents ranks from Masters and above who are characterized by high competitiveness and unmatched skill by the rest of the playerbase).
Technically speaking, Riot ditched the Elo system in season 3 in favor of the League system we’re currently using*.* In practice, however, it’s a mere reskin, using Ranks and Tiers and LP instead of publicly displaying your MMR rating; Your MMR is still what determines your gains and losses so it all ultimately functions the same under the hood.
Now how about we open this hood and find out how this system plays its magic and matches you with the same 2/10/3 Yasuo 4 games in a row, here’s the
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simplified Elo mathematical breakdown:
Ra: Your MMR ;Rb: The enemy team’s average MMR
“note that the value 400 is characteristic to chess, the true value used by Riot is undisclosed”
Pa is a value between 0 and 1 to determine how likely you are to conquer a team with an *“Rb” *****average rating; This value is crucial to calculating how much LP you’ll win or lose.
R’a: Your new rating;
Sa here represents the outcome of the game (Sa=1 if you won, otherwise it’s 0).
K here represents the magnitude of change in rating; In other terms, if K is high, you’ll win and lose a lot of LP after each game, if it’s low your LP fluctuations will be subtle. K always starts as a high number for your first ranked games and decreases the more you play; This is why you rank up and down too fast during placements and find it harder to promote later down the line!
While this system is functional enough in rating players, it only takes into account one thing: Whether you won or lost, and in a game as complex as League that single metric is insufficient to determine a player’s skill level which is the whole point of the Elo system. This implementation of Elo has ultimately been the bane of the League community for ages as it introduced systematic roadblocks that made Ranked play an insufferable cesspool of frustration. The biggest criticism regarding this system is that your individual performance has little to no impact on how you’re rewarded or punished: Your LP is hostage to your team’s performance regardless of how you played (So you just lost the game despite being 17/5/8 with an afk botlane? Too bad, here’s -34 LP to treat yourself).
Another detriment of Elo is that it creates situations ironically called Elo Hell where your rating has dropped due to continuous losses (regardless of whether you’ve played well yourself or not), and when you’ve played enough games that your K value is so low that victories don’t give significant rewards, forcing you to be stuck in the lower tiers with no way out (other than boosting perhaps).
There is more to skill than just winning and losing, and the current system has no regard for any of them. Luckily for us Riot Games officially announced a couple of months ago that it will introduce TrueSkill 2 to substitute the current prehistoric League system. It will function similarly to Valorant’s ranked system (which takes into account metrics regarding your in-game performance) where you’ll be rewarded for carrying your team to victory and spared some points if you lost in spite of doing your best.
The reason Riot was so hesitant to implement such a system in League was fear that players would discover what metrics favor the system and try to maximize them instead of winning the game (for example; players would avoid High-risk High reward plays to preserve their KDA, or waste Gold on wards to inflate vision score…). Looks like the success of Valorant’s ranked system gave them reassurance to move forward with this plan, but we’ll still have to wait for it to judge by ourselves.
Even though the entire ranked system is being altered in around 6 months, it’s still necessary to gain some insight on how to use ELO’s weaknesses to your advantage and rank up faster in the two remaining splits to get a headstart with a higher MMR (or its new equivalent) next season:
The best course of action now is to focus on honing these skills to gain a headstart wherever TrueSkill 2 hits the rift, and what better way to thoroughly master League’s mechanics than by practicing on a smurf account? At UnrankedSmurfs, we offer hand-leveled ranked and unranked accounts, providing a convenient solution for acquiring high-quality League of Legends smurf accounts all in one place.
Despite its widespread use in numerous fields, the Elo rating system has demonstrated over the 15-year history of League of Legends that it is ill-suited for the game's highly complex nature. However, with the impending introduction of TrueSkill 2 , which promises more individualized ratings and a fairer ranking system, we can only hope it remains unexploitable and fulfills its promises, potentially resolving the major issues that have plagued League of Legends for so long.
