Is Marvel Rivals Matchmaking Rigged? Unveiling The Truth
Is the matchmaking system in Marvel Rivals designed to keep you playing longer, even at the expense of fair competition? Recent allegations and player experiences suggest that the game's "Engagement Optimized Matchmaking" (EOMM) system might prioritize player retention over providing a truly balanced and enjoyable experience.
The world of online gaming, particularly competitive multiplayer titles, thrives on the promise of fair play and engaging experiences. Central to this promise is the matchmaking system, the invisible hand that pairs players based on skill, geographical location, and other relevant factors. When the matchmaking system falters, the entire foundation of the game can crumble, leading to frustration, imbalance, and ultimately, a decline in player engagement. Marvel Rivals, the hero-based shooter developed by NetEase Games, has found itself at the center of just such a controversy, with players questioning the integrity and fairness of its matchmaking algorithm.
The concerns surrounding Marvel Rivals' matchmaking system, which have bubbled to the surface since the game's release, revolve around the alleged use of "Engagement Optimized Matchmaking" (EOMM). Unlike Skill-Based Matchmaking (SBMM), which primarily focuses on matching players of similar skill levels, EOMM incorporates a wider array of factors, including player engagement metrics. This means the system potentially adjusts matchmaking to keep players in a "flow state" a state where they remain engaged and continue playing for extended periods. Critics argue that this approach can lead to several undesirable consequences.
One of the most vocal proponents of this viewpoint is the popular gaming streamer, Nickmercs, who has publicly claimed that Marvel Rivals manipulates matchmaking to balance wins and losses, thereby keeping players invested in the game. The implication is that the game deliberately creates scenarios, through the quality of teammates or opponents, that either reward or punish player performance, with the ultimate goal of maximizing playtime. This has led to accusations that the system is "rigged," designed to keep players hooked rather than provide a consistently fair and competitive environment.
To understand the nuances of this debate, let's delve into the core concepts and controversies surrounding Marvel Rivals' matchmaking system. We'll examine the various factors that might be considered, the potential benefits and drawbacks of EOMM, and the evidence players are citing to support their claims. Furthermore, we'll consider how NetEase Games' own research, including their paper "Optmatch (2020)", might shed light on the inner workings of this complex system.
Before we delve into the specifics of Marvel Rivals, it is important to clarify the distinction between the different types of matchmaking systems. Skill-Based Matchmaking (SBMM) is designed to pair players of similar skill levels. This is the most common and generally accepted approach to matchmaking in competitive games. The goal is to create balanced matches where players have a fair chance of winning. However, it is not always fun, as a player can be matched with highly skilled players and lose constantly.
Engagement Optimized Matchmaking (EOMM), on the other hand, takes a more holistic approach. While skill is still a factor, EOMM considers various other metrics, such as playtime, win/loss ratios, in-game purchases, and even the amount of time a player spends in the games menus. The core goal of EOMM is to optimize player engagement, which, in the context of a free-to-play game, translates to maximizing revenue. This is achieved by keeping players playing for longer durations.
The alleged implementation of EOMM in Marvel Rivals has raised significant concerns. Players believe the system manipulates matches to create a sense of progression and reward, regardless of the players skill level. For example, a player on a losing streak might be matched with less-skilled opponents or receive higher-skilled teammates to artificially boost their win rate. Conversely, a player on a winning streak might be matched against tougher opponents or receive weaker teammates to prevent them from dominating the game.
While SBMM aims for fair matches, EOMM prioritizes player retention. This can lead to an inconsistent experience for players. Matches can feel either too easy or too difficult. The variability in the game experience can lead to players feeling that the game is rigged, further damaging the game's image.
Another key aspect of the debate involves the use of bots. Several players have reported encountering bot matches, particularly after experiencing a series of losses. These matches, populated by AI-controlled opponents, might be designed to provide an easier experience, helping players to recover from a losing streak and maintain their engagement. The presence of bots, while potentially beneficial in the short term, can undermine the authenticity of the competitive experience, making victories feel less meaningful. This could be considered a psychological manipulation of players.
The fundamental issue players face is understanding the exact factors that the EOMM system takes into account. Without an official statement from NetEase Games, and because the algorithm is not fully public, it is difficult to ascertain the precise inner workings of the system. The lack of transparency fuels speculation and allows for accusations of manipulation to persist.
The claims and counter-claims are further complicated by the nature of the gaming community itself. Players are naturally prone to confirmation bias, selectively interpreting their experiences to support their pre-existing beliefs. If a player believes the matchmaking is rigged, they are more likely to notice and remember instances that confirm that belief. The opposite is also true.
In contrast to the more rigorous SBMM in the competitive modes, the system takes a more relaxed approach, almost non-existent, in the casual modes like Quick Match, Conquest, or custom games. These modes prioritize quick matches and provide players with an opportunity to enjoy the game's roster of 35 characters, without the pressure of strict skill-based matchmaking.
The controversy surrounding Marvel Rivals' matchmaking is a complex issue with arguments on both sides. The allegations of EOMM and potential bot usage must be weighed against the potential benefits of maintaining player engagement and ensuring a positive gaming experience. Transparency from the developers is essential to dispel the rumors and create trust within the community. Only then can the matchmaking system deliver on its fundamental promise: to provide a fair and enjoyable competitive experience for all players. More research and player observation are vital to gain a deeper understanding of the reality of the Marvel Rivals matchmaking system.
The game's developers have been under fire since release due to allegations that the game's matchmaking is rigged on purpose with the use of the engagement optimized matchmaking (EOMM) system.
Heres what we know about the Marvel Rivals Matchmaking System:
| Feature | Description |
|---|---|
| Core Function | Match players for online multiplayer games. |
| Primary Goal (Alleged) | To maximize player engagement and retention (EOMM). |
| Factors Considered | Skill, playtime, win/loss ratios, in-game purchases, time spent in menus (speculated). |
| Controversy | Allegations of manipulating matches to balance wins/losses; potential use of bots. |
| Casual Modes | SBMM is less strict to prioritize quick matches and fun. |
| Transparency | Lack of official information on the exact factors considered by the algorithm. |
| Player Experience | Inconsistent matches; potential feeling of being "rigged." |
In the context of Marvel Rivals, here's a potential breakdown of how EOMM might manifest:
| Scenario | Potential EOMM Influence |
|---|---|
| Player A has a high win rate and is consistently performing well. | The system might match them against tougher opponents or place them with less skilled teammates to balance their win rate. |
| Player B is on a losing streak and has played for several hours. | The system might match them against easier opponents or place them with higher-skilled teammates to boost their win rate and keep them engaged. |
| Player C has made in-game purchases. | The system might prioritize them in matchmaking to ensure they can continue enjoying the game with the content they have acquired, aiming to keep them engaged longer. |
| Player D is new to the game. | The system might match them against less experienced players to create a positive initial experience and encourage them to continue playing. |
The impact of these potential manipulations is significant. Players might experience inconsistent match quality, making victories feel less earned and losses feel more frustrating. This inconsistency can lead to a perception of the game being "rigged," leading to player dissatisfaction and potentially even abandonment of the game. The developers research stating that fair matches are not always good for player engagement adds fuel to this fire, increasing player's sense of the developers prioritizing their engagement metrics above everything else.
Understanding the intricacies of SBMM is paramount to the discussion. SBMM aims to pair players with others of comparable skill, offering a relatively consistent and fair experience. However, the accuracy of SBMM is dependent on the game's ability to accurately assess player skill. Inaccuracies can lead to mismatches, with highly skilled players facing lower-skilled opponents and vice versa. This can disrupt the balance of matches and detract from the overall fun and experience of the game.
The core of the problem isn't necessarily the use of EOMM itself, but the lack of transparency surrounding its implementation. If NetEase Games were more forthcoming about the factors considered by the algorithm and how they are weighted, players would be better equipped to understand the system and potentially mitigate the feeling of manipulation. A transparent and well-documented system could increase player confidence, even if EOMM is used. It is also important to avoid the losers queue, which can push players away from the game.
One can find the research in the published paper of netease games titled "Optmatch (2020)" and other related material.
Netease Games Research (Example)
