Why Is League of Legends LP So Inflated?
An Apex Ranked System Analysis
What Is LP Actually Supposed to Measure?
League of Legends' ranked system was designed to do one thing: separate players by skill. LP represents a reliable signal of where you stand relative to other players, and at apex ranks, that signal has been going over a difficult period with a lot of frustration being expressed by players, especially in regions with very high player counts such as EUW.
The gap between the best and second-best players has grown larger than what matchmaking can bridge fairly, and larger than what the LP system can accurately represent. Everything visible, from negative LP gains to inflated cutoffs and volume grinding replacing skill as the primary differentiator, are issues that can be connected to the mismatch between the system's resolution and the population it's trying to measure.
This analysis looks at what's causing that mismatch, how Riot is currently responding, and potential paths toward addressing the root problem.
Note: This analysis begun and was based on information from April - May 2026. I tried to include some of the updates and measures Riot took since, like the Apex Ranked & MMR reset, as well as the removal of the soft cap.
Defining the Standard
Before identifying what's broken, it helps to define what a healthy version of the system looks like. A well-functioning apex ranked system should satisfy four properties simultaneously:
Accuracy
LP reliably reflects skill. Two players at the same LP should be very close in ability. Gains and losses should be proportional to performance, not proximity to an arbitrary cap.
Fairness
The rules of climbing should be equal for everyone in the same tier. A 55% winrate at 1500 LP should produce roughly the same LP gains as a 55% winrate at 1900 LP. The math shouldn't punish you for where you started or what your MMR history looks like.
Responsiveness
The system should detect and reflect a player's true skill level within a reasonable number of games. A sluggish system punishes skilled players by making them grind through games they've already demonstrated they should win.
Legitimacy
Once a player has played enough games for the system to assess their skill accurately, additional volume should not meaningfully move their LP beyond what their skill justifies. Rank should reflect how well you play, not how often you play.
The risk of building too conservative a system is that accurate rating requires an unreasonable volume investment, at which point responsiveness itself becomes a legitimacy problem.
Volume needed to reach the system's confidence threshold is legitimate. Volume beyond that threshold continuing to move LP is not, since at that point rank reflects availability rather than skill.
What's Actually Breaking It
Eleven variables contribute to the current breakdown, spanning structural design decisions, population-level shifts, and systemic interactions between the two. I picked four of the most significant ones to cover here, but you can find the full breakdown in the Miro board.
Variables influencing rank signal integrity
The soft cap was a stability mechanism that worked fine in isolation. It begins misfiring when the skill gap at apex widens enough that matchmaking struggles to build fair games at the top. At that point it compresses gains for the players already most affected by matchmaking's limitations, producing the +10/-30 outcomes that made the distortion impossible to ignore. It doesn't cause inflation directly, but it amplifies the fairness and accuracy breakdown that inflation makes visible.
Combined with the soft cap, top players can reach a point where they lose more than twice what they gain per win. At a 55% winrate a player could still be losing LP net over time. The system ends up telling someone who wins more than they lose that they don't belong at their rank. A 55% winrate means you're better than your opponents on average, so the system should be moving you upward. Instead it moves you downward.
This soft cap was removed later on, which dealt with this issue but introduced a new one: LP gains at the top increase with an unprecedented rate, with players reaching 4.7k LP (as of September 2026 EUW). These ever increasing numbers, also increase the entry threshold to Challenger (2320LP as of September 15 2026 EUW), and it reaches a point where new Master and Grandmaster players can feel overwhelmed and demotivated due to the sheer amount of games needed to reach this number.
Every season starts with a soft MMR reset pulling everyone toward average. High elo players then climb back through ranks far below their true level, winning at enormous rates, which rockets their MMR back up rapidly. By the time they reach apex, their MMR has already overshot their LP significantly. The reset mechanism designed to keep the ladder fresh is one of the main things responsible for creating the divergence that breaks apex matchmaking at the start of every season.
This is the most important systemic interaction in the analysis. The soft cap worked well when matchmaking could still produce fair games at apex. When the skill gap widened and matchmaking started struggling, the system began misfiring by compressing LP gains in games that were already unfair to begin with. Neither variable is necessarily bad in isolation. Together they produced the negative LP gain situation that sparked the entire conversation.
When the visible LP gap between the bottom of Master and Challenger grows too large, the psychological barrier of the climb can eclipse the actual skill barrier. Seeing an inflated 2500 LP cutoff feels unreachable and inherently demoralising to new Master players. While the Grandmaster rank was originally introduced to make this gap feel more granular, it was only a temporary fix. We've reached that inflection point again, and indefinitely inserting new tiers isn't a sustainable long-term solution.
What Riot Is Getting Right, And Where The Gap Is
What they correctly identified
- The soft cap was producing asymmetric outcomes that felt deeply unfair to top players performing well.
- Legacy account advantages, while creating an uneven playing field, serve an important purpose in discouraging smurfing.
- Matchmaking at apex is structurally constrained by pool size — perfect role parity, skill matching, and fast queues simultaneously is not possible with 300 Challengers.
- The widening skill gap between the best and the rest is a long-term structural challenge that won't resolve on its own.
General observation
Riot is making changes that are individually rational and show real understanding of the problems. However, the overall approach is partly reactive. Many proposed solutions address the most visible symptoms at the time rather than working toward a unified long-term vision of what the apex ecosystem should look like in 3 to 5 years.
Without a clearly defined destination for what apex ranked should feel like at its best, each fix risks creating the conditions for a new problem.
Directions Worth Exploring
As I am not a Riot developer with access to their systems, data, or internal constraints, the proposals below are directions that invite discussion rather than definitive solutions.
One of the reasons this analysis took longer to complete was because Riot conducted an MMR hard reset for apex tiers partway through. I waited to observe its effects before writing this section. The reset did meaningful work — it weeded out players who didn't deserve their LP and gave deserving players a faster path back to their rank.
However with the soft cap still removed, top players are once again approaching record LP numbers, and the tier gap is widening. As of 1st June 2026 on EUW, the top Challenger player sits at approximately 3.3k LP (4.7k @ 15 Sep) with the cutoff at 1.7k (2.3k @ 15 Sep). The reset was a necessary intervention. Without additional measures it doesn't address the deeper variables identified above.
Tiered Confidence Reset System
Target: MMR carryover, legacy account advantages, seasonal resetsInstead of a blanket soft reset that treats all apex players equally, reset treatment should be proportional to how consistently a player has proven they belong at their rank across multiple seasons. All apex players start back at Emerald-Diamond and climb through to their respective tier without anyone skipping the worthiness check entirely.
The speed at which they move through irrelevant ranks should be tiered based on proven history, and the critical mechanic is an MMR readjustment point: when a player gets close to their previously proven rank, their MMR resets to a neutral baseline for that tier rather than continuing to overshoot. Multi-season veterans, defined as maintaining the rank for the majority of the season at a meaningful peak LP across multiple seasons, receive a boost that carries slightly further into the tier itself, reflecting accumulated proof of belonging there.
Variables targeted: Seasonal resets, MMR/LP decoupling, legacy account advantages, volume as strategy
Stabilised Gain/Loss Bands With Performance Variance
Target: Asymmetric LP delta, soft cap removal side effects, volume as strategyRather than either a hard soft cap or completely unbounded gains, each apex tier would have a target gain/loss range instead of fixed numbers. For example, Master sitting around +18 to +22 / -18 to -22, tightening slightly through GM and Chall. Within those bands, the exact number fluctuates based on matchmaking quality: well-balanced games produce gains and losses at the higher end, difficult-to-balance games reduce both proportionally.
Gains and losses move together rather than independently, eliminating the asymmetric delta problem without introducing a hard cap. Once a player has played enough games to converge to their true rating within the tier, the band narrows further, preventing volume from continuing to move LP significantly beyond the confidence threshold.
Variables targeted: Asymmetric LP delta, soft cap side effects, volume as strategy, MMR/LP decoupling (partially)
Dynamic Slot Scaling With Regional Population
Target: Fixed slot counts, autofill pressure, fairness across regionsRather than fixed GM and Challenger slot counts per region, slots could scale dynamically with regional ranked population, maintaining a consistent percentage threshold rather than a fixed number. The goal is preserving the ratio that made these ranks prestigious when they were designed, rather than letting that ratio erode silently as populations grow.
As noted in a previous step, when Challenger was introduced and its 300 slots were the chosen number, the amount of people who played was less than now, therefore adjusting this based on the population number, makes logical sense. It can always be slightly constrained rather than a 1:1 analogy, to preserve a more prestigious feeling.
Variables targeted: Fixed slot counts, autofill pressure, fairness across regions, legitimacy
The three proposals above aren't presented as a complete solution. They're an attempt to point at a deeper layer within the problem that the current approach hasn't fully reached yet. Individually, each one addresses a specific root cause variable from the analysis, and together, they try to answer the question defined at the very start: how do you build a system that can actually separate players by skill at apex, when the skill distribution has outgrown what the system was originally designed to measure?
None of these are simple to implement, and all of them carry tradeoffs that would need iteration and care, with access to data and systems that only Riot has. Designing and implementing changes for a live system with millions of players is a fundamentally different challenge than analysing it from the outside.
What an outside perspective can offer is a different set of questions. Instead of asking "how do we fix the LP number", we should ask what is LP supposed to measure, and is the system still measuring it? Instead of asking "how do we make the climb feel less grindy", we should look at what the system is rewarding, and whether that is the same thing we want it to reward. Whether these specific proposals have merit is a conversation worth having, and the framing they come from feels like a strong starting point.