Plays – Gaming Master https://gaming.vmondeika.com Get daily gaming updates with us Fri, 12 Jun 2026 06:05:15 +0000 en-US hourly 1 https://wordpress.org/?v=7.0.2 Unorthodox plays and scary team coordination: Team WE will likely qualify for MSI https://gaming.vmondeika.com/unorthodox-plays-and-scary-team-coordination-team-we-will-likely-qualify-for-msi/ https://gaming.vmondeika.com/unorthodox-plays-and-scary-team-coordination-team-we-will-likely-qualify-for-msi/#respond Fri, 12 Jun 2026 06:05:15 +0000 https://gaming.vmondeika.com/unorthodox-plays-and-scary-team-coordination-team-we-will-likely-qualify-for-msi/ Team WE on stage
Image Credit: Team WE Weibo

If there is any team you should be rooting for right now in League of Legends esports, it should be Team WE. This mid-pack team pulled off not one, but two of the greatest upsets of the season and are now one series away from qualifying for the Mid-Season Invitational.

While everyone loves an underdog story, Team WE’s success feels different. Once considered one of the faces of Chinese esports, the team is far from its glorious days. Could this be the start of a new chapter? And are they one of the most dangerous teams to face in the world, right now? 

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A Tough Start to the 2026 Season

At the start of the season, Team WE had formed a roster that didn’t really stand out from the pack. It kept its top side trio of Dai “Cube” Yi, Wang “Monki” Meng-Qi, and Kim “Karis” Hong-jo and brought in a new bot lane with Korean ADC Moon “About” Hyeong-seok and Chen “yaoyao” Si-Yuan, following the departure of Kim “Taeyoon” Tae-yoon and Zhao “Vampire” Zhe-can.

The first split of the 2026 season went by without many surprises, with Team WE constantly in the mid-pack. Their top-eight finish, however, allowed them to be placed with the big boys in Group Ascend for the second split.

While playing with strong teams can help weaker teams improve, Team WE struggled to find its footing in the LPL Split 2 regular season, winning only 1 of 14 matches. 

lpl split 2 regular season
Image Credit: LPL Weibo

Even though the addition of support Shi “Erha” Xu-Ye didn’t yield much in results initially, Team WE was slowly improving and building all the necessary elements bit by bit, just in time for when it mattered the most.

This is proven by the team’s game record: after losing the first 8 series with 0-2 records, Team WE began winning games and taking maps from most teams, including JD Gaming. 

Despite a few wins, the team still finished last in Group Ascend, forcing them to play LNG Esports in the play-ins stage.

The Play-Ins Survival Series and the Upsets in Playoffs

Team WE’s rise in form came exactly during this series. After being pushed to five games, Team WE came back from a 5,000-gold deficit through their teamfighting and kept their playoff hopes alive. The issue was that BLG picked WE in their first round: the best team in the league was facing the bottom team of Group Ascend.

Against all odds, Team WE took BLG down with a 3-1 record. The series wasn’t clean, but the victory wasn’t just down to pure luck or BLG having a bad day: Team WE fought back from losing positions and outplayed what was considered the best team in the world through stronger coordination and cohesion.

Team WE proved to everyone that the victory was not a fluke, proceeding to dismantle the #4 seed Anyone’s Legend with another clean 3-0. 

What Makes Team WE So Strong?

The scariest part of Team WE right now is their cohesion as a five-man unit. They have proven to be more coordinated than any other team in the league, with all five players making the same decision.

And at the heart of that cohesive decision-making is jungler Monki.

The guy has established himself as the main voice and shotcaller of the squad while also matching the best junglers in terms of individual performance. When Monki calls for a play, everyone on the team will follow his directives, even if they might not be perfect. 

Team WE Monki
Image Credit: Team WE Weibo

Dplus Kia head coach Kim “cvMax” Dae-ho had explained this concept in the past: “If all five members come down to make the same decision in any given circumstance, they can turn a wrong answer right.”

By removing the need to question whether a play is correct in the moment, Team WE can always be the first to move, putting pressure on opponents to fight back. This is what happened in the series against both BiliBili Gaming (BLG) and Anyone’s Legend (AL). In particular, BLG was often caught off guard in teamfight scenarios despite having the gold lead. 

Top laner Cube himself shared in an interview that he’s now more prone to listening to Monki’s plays: “I just do whatever he tells me to do.”

According to Chinese esports analyst Lan Bao Shi (蓝宝石), Monki also has another strong tendency in his gameplay that has worked out in the recent victories: his willingness to change tempo. In a meta where most junglers tend to full clear before making plays, Monki often tries to disrupt the orthodox jungle clears through unexpected gank timers and pathings.

While it’s a high-risk strategy that can cause him to fall behind in gold and experience, Monki won out on many of those plays and built substantial leads for his team. 

The Current Meta Is Helping Hide WE’s Weaknesses

That does not mean WE is flawless. The team still has some clear weaknesses; it’s just that the meta is helping hide some of them.

For example, top laner Cube has been thriving in recent weeks now that the meta has shifted towards a more weakside environment. At the start of the split, when it was still about lane dominance, he struggled to keep up with the best top laners.

Now, he’s able to absorb that pressure and consistently show up in the fights with enough resources.

Bot laner About also had initial struggles in adapting earlier this season. It’s not a coincidence that Team WE’s rise also aligned with About’s improved performance. All esports teams need to rely on their ADC in the late-game teamfights, so the Korean marksman must keep his form moving forward.

Additionally, Monki could also be targeted by other teams moving forward, knowing how vital his pathings are for the squad. 

And Team WE Can Actually Make it to MSI

Could Team WE make it to the Mid-Season Invitational? To put it simply, the chances are real. Not only did Team WE prove they can take down the top teams, but their gameplay is solid as well. 

team WE on stage
Image Credit: Team WE Weibo

The upper bracket final series against Top Esports will not only be crucial for determining which LPL team will be the first locked for MSI, but will also shed light on whether Team WE can be exploited for its weaknesses.

If Top Esports (TES) manages to win, it will become golden material for Team WE’s future opponents to review and study. If they can’t, then this Team WE roster can be a frightening opponent for MSI.

Regardless of how it goes, Monki and his teammates will have the momentum on their side. Caedrel said it best: “This team just feels like they’re on a run. They’ve got something behind them. They’ve got momentum. They’ve got belief. All the players are bought into this idea, this style they’ve adopted… It’s like lightning in a bottle.”

The question is: Will Team WE continue to evolve, or will the other LPL teams catch up first? The answer will directly dictate whether they are going to be a top dog for the rest of the season.

The post Unorthodox plays and scary team coordination: Team WE will likely qualify for MSI appeared first on Esports Insider.

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Google built an AI that can see football plays before they happen https://gaming.vmondeika.com/google-built-an-ai-that-can-see-football-plays-before-they-happen/ https://gaming.vmondeika.com/google-built-an-ai-that-can-see-football-plays-before-they-happen/#respond Fri, 12 Jun 2026 00:37:10 +0000 https://gaming.vmondeika.com/google-built-an-ai-that-can-see-football-plays-before-they-happen/ [ad_1]

Football managers spend countless hours analyzing corners, free kicks, and player positioning in search of tiny competitive advantages. Google DeepMind believes artificial intelligence can make that process significantly faster, and its latest project, TacticAI, is designed to do exactly that. TacticAI is a football-specific AI assistant capable of modeling player movement, forecasting future play dynamics, and even recommending tactical adjustments for corner kicks. One of its standout abilities is predicting player trajectories up to eight seconds into the future using only broadcast-style visual data.

TacticAI was built with Liverpool FC and validated by football experts

Unlike general AI models, TacticAI focuses specifically on football tactics. Using geometric deep learning, the system analyzes the positions and interactions of players during corner kicks before generating predictions about what could happen next and suggesting alternative player arrangements that may improve outcomes.

Perhaps more importantly, the model wasn’t just tested in a lab. Google says its usefulness was evaluated through a qualitative study with football experts at Liverpool FC, who compared the AI’s recommendations against real match scenarios. According to the published research, experts preferred TacticAI’s suggested tactical setups 90 percent of the time over the original match configurations, highlighting the system’s practical value rather than just its statistical performance.

The benchmarking results are equally impressive. TacticAI outperformed existing baseline models in predicting both the likely receiver of a corner kick and whether a shot would occur afterward, while also generating realistic alternative player layouts that closely resembled genuine professional match situations.

This could be much bigger than football

The research is already moving beyond the lab. Google DeepMind has now announced a partnership with Brazilian football club Palmeiras, making it the first team to meaningfully build on TacticAI to simulate on-field scenarios and predict open-play dynamics up to eight seconds in advance. If successful, it could mark the beginning of AI becoming a genuine tactical assistant on the sidelines, not just another analytics tool running in the background.

We’re teaming up @Palmeiras, the first football club to meaningfully build upon TacticAI: our AI system that can help simulate field scenarios and predict open play dynamics up to 8 seconds in advance. ⚽ pic.twitter.com/M3Krejk9Er

— Google DeepMind (@GoogleDeepMind) June 11, 2026

What’s more, is that the underlying technology has applications far beyond sports. Similar predictive models could one day assist autonomous robots, traffic systems, logistics planning, or any environment where understanding and forecasting coordinated movement is critical. And perhaps that’s the most fascinating part of TacticAI. On the surface, it looks like an AI built to help coaches win football matches. Underneath, it may be quietly laying the groundwork for machines that understand and anticipate complex real-world interactions before they unfold.

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Google DeepMind’s TacticAI can predict football plays 8 seconds before they happen. Palmeiras is using it first. https://gaming.vmondeika.com/google-deepminds-tacticai-can-predict-football-plays-8-seconds-before-they-happen-palmeiras-is-using-it-first/ https://gaming.vmondeika.com/google-deepminds-tacticai-can-predict-football-plays-8-seconds-before-they-happen-palmeiras-is-using-it-first/#respond Thu, 11 Jun 2026 23:18:44 +0000 https://gaming.vmondeika.com/google-deepminds-tacticai-can-predict-football-plays-8-seconds-before-they-happen-palmeiras-is-using-it-first/ [ad_1]

TL;DR

Google’s TacticAI predicts football plays 8 seconds ahead. Liverpool experts preferred its tactics 90% of the time. Palmeiras is the first club using it in live play.

Google DeepMind built an AI that can predict football plays before they happen. TacticAI uses geometric deep learning to model player movement, forecast dynamics up to eight seconds into the future, and recommend tactical adjustments, all from broadcast-style visual data. Brazilian club Palmeiras is the first to use it for live open-play analysis.

The system was originally developed with Liverpool FC and validated through a qualitative study with the club’s football experts. They compared TacticAI’s recommended tactical setups against real match configurations. The experts preferred the AI’s suggestions 90% of the time. The published research, in Nature Communications, showed TacticAI also outperformed existing models in predicting corner kick receivers and whether a shot would follow.

The Palmeiras partnership, announced at Google’s Brasil event on June 10, marks a significant step. TacticAI was previously limited to set-piece analysis, specifically corner kicks. Palmeiras is the first club to use it for open-play dynamics. The club’s data science team uses a drag-and-drop interface to virtually reposition players and observe how changes affect the collective behaviour of both their team and the opponent.

That means a coach can ask: what happens if we push the left back five metres higher? TacticAI simulates the downstream effect on the entire defensive structure. It quantifies tactical options that were previously gut feeling. Google also partnered with Brazil’s football confederation CBF to use AI in World Cup preparation.

The underlying technology has applications well beyond sport. Predicting coordinated movement from visual data is the same problem autonomous robots, traffic systems, and logistics planners need to solve. TacticAI’s geometric deep learning approach, which treats players as nodes in a dynamic graph and models their spatial relationships, is architecturally closer to physical AI systems than to a standard language model.

Football has been slower than other sports to adopt AI-driven tactics. Baseball has Statcast. Basketball has Second Spectrum. Football’s continuous, 22-player dynamics make it harder to model. TacticAI’s 90% expert preference rate suggests the gap is closing, and the growing role of AI in professional sport is moving from analytics in the background to tactical recommendations on the sideline.

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