Valorant devs are asking players to report cheaters more often

Valorant’s anti-cheat leadership, headed by Paul “Arkem” Chamberlain, recently shared comprehensive data about in-game reporting patterns to motivate players toward more consistent reporting behavior. The statistics reveal surprising gaps in current reporting habits that directly affect cheating prevention effectiveness.

While the Vanguard system demonstrates impressive technical capabilities for identifying hackers automatically, Arkem emphasized that community-submitted reports remain the “most powerful tools” available to the anti-cheat team. These player-submitted reports travel directly to specialized analysts who investigate suspicious activities. This player-generated intelligence provides crucial context about actual gaming experiences and highlights areas needing immediate attention from developers.

What happens when you report a player in Valorant?

In a recent developer blog publication, Riot Games detailed the complete lifecycle of a player report, demonstrating how this community-driven mechanism significantly enhances anti-cheat operations beyond automated systems alone.

Within the automated component of Vanguard’s detection framework, the backend infrastructure utilizes report data to determine which accounts warrant “additional scrutiny.” This assessment frequently relies on the volume of reports submitted against specific accounts. When multiple players report the same individual, Vanguard gains increased confidence in its analytical conclusions, enabling swifter account restrictions without requiring human intervention.

For manual investigation procedures, dedicated analysts examine “the most suspicious players” daily, prioritizing those with the highest report frequencies across matches.

“These hands-on investigations allow us to discover cheating methods that automated systems haven’t yet identified. We then incorporate these findings into Vanguard’s development roadmap to enable future automatic detection and banning capabilities. Additionally, we leverage these manual assessments to proactively eliminate highly disruptive players before scheduled review cycles,” Arkem clarified.

The anti-cheat leadership team explained that “ban waves” frequently get strategically timed to prevent cheat developers from understanding whether their software has been detected.

Arkem further noted that manual reporting data assists developers in evaluating Vanguard’s overall performance and effectiveness.

“When we observe increasing report volumes overall, that signals to our development team that players are experiencing concerns about game integrity (independent of individual report accuracy). Similarly, we can gauge Vanguard’s efficiency by comparing the proportion of players reported for cheating against the percentage automatically detected by our systems,” Arkem stated.

The numbers behind Valorant cheating reports

Valorant’s development team decided to analyze reporting behaviors comprehensively, revealing unexpectedly low reporting rates throughout the player community.

Based on Arkem’s analysis, 97% of Valorant participants have never received any player reports. Among the 3% of players who have been reported within Valorant, over 80% received reports from just one individual player. Approximately 90% of reported players received complaints from fewer than three separate accounts.

“Expressed differently,” Arkem commented, “merely 0.6% of players have obtained more than one cheating report and only 0.3% have accumulated three or more reports. However, reporting frequency and actual cheating incidence don’t perfectly align—many reported players demonstrate no cheating behavior, while some confirmed cheaters never get reported before receiving bans.

Presently, only 53% of ultimately banned cheaters were reported prior to their account restrictions. Just 60% of players accumulating 20+ reports eventually get banned following investigation.

“Despite imperfect correlation between reports and actual cheating, community reporting remains exceptionally valuable,” Arkem supplemented.

The anti-cheat team subsequently encouraged Valorant participants to report suspicious activities more frequently. Whenever players observe potentially questionable behavior, the security team recommended utilizing the reporting interface immediately. They characterized these player-submitted reports as the “best intelligence” available for identifying and removing hackers and cheaters from gameplay environments.

Identifying Genuine Suspicious Behavior

Learning to distinguish between skilled gameplay and actual cheating represents the first step toward effective reporting. Watch for players exhibiting impossible reaction times, consistently perfect pre-aiming through walls, or demonstrating knowledge of opponent positions without logical explanation. Genuine cheaters often display inconsistent performance—dominating some rounds while performing poorly in others when their cheats become less effective.

Common Reporting Mistakes to Avoid:

• Reporting players simply because they outperform you
• Submitting reports based solely on death cam footage without additional context
• Reporting entire teams after frustrating matches rather than specific suspicious individuals

Optimal Reporting Timing and Strategy

Submit reports immediately after observing suspicious behavior rather than waiting until match conclusion. Multiple reports from different players against the same individual significantly increase investigation priority. Document specific incidents with timestamps when possible through the in-game reporting system.

Advanced Reporting Techniques:

Experienced players should note unusual patterns across multiple rounds, such as consistently knowing flanking routes or demonstrating impossible tracking through smoke screens.

Understanding the relationship between weapon performance and typical gameplay limits helps identify genuine cheating versus exceptional skill.

Remember that false reports waste valuable analyst resources. When uncertain, consider whether the player’s behavior could be explained by game knowledge, audio cues, or predictable player patterns before submitting reports.

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