AHQ: Trial By Vision

In this article I will be looking at AHQ’s vision control over several different time periods in the early game. Everyone knows Westdoor as the man that roams whether it is his Twisted Fate, Lissandra, or his used to be Fizz. In order to effectively roam though you need vision or else you are blindly walking through fog of war and showing your location. I am curious how AHQ prioritize their vision and how their play style affects their vision control.

The data I will show will be on the ward differences for specific sub-regions of the map. The key I will use for determining the weakness and strength of the vision is below:

Strong Positive/Negative: -0.5 or less, 0.5 or greater

Medium Positive/Negative: Between -0.15 to -0.4999, 0.15 to 0.4999

Weak Positive/Negative: Between -0.1499 to 0.1499

River Control

Overall Data

Overall Data

Top River Ward Difference: 0.071

Bot River Ward Difference: 0.163

What you see above is the ward difference for AHQ on the different time periods I tested and the overall average of these time periods. The first values I will look at are the overall which are displayed below Overall Data title. The top river ward difference is a bit weak. Essentially it means AHQ aren’t providing much vision towards top while also the opposition is taking resources to invest in top river control. One of the factors is Ziv’s champion pool. He has played essentially three champions: Gnar, Ekko, and Gangplank. Ekko and Gangplank are very independent champions who don’t need as much focus allowing your team to invest more resources on the opposite side of the map. As a side note, Flash Wolves put more focus on top vision control in their games against AHQ. The top river control data will be more influenced by this and thus AHQ will have a lower top river ward difference.

For bot river control AHQ holds a small advantage over their opponents. As most should know at this point, patch 6.15 increased bot priority since lanes are always standard. Some of this data is also skewed towards bot because AHQ played five games against Flash Wolves in the semifinals. FW’s bot lane is rather weak. It makes for a great target for AHQ who have one of the strongest duo lanes in LMS.

The early time periods for AHQ are light to even control. AHQ does not snowball lanes quickly. A large number of their games they are running Gragas into high tempo junglers like Rek’sai which requires AHQ’s lanes to play safer. You can see the top river control actually take a dip at 5:40 game time which is not unexpected based on what I said. However, as the game progresses the bot river control increases. Mountain likes to wait on his bot lane ganks until he can find chances to secure bot tier-1 off his gank. This number spikes the highest at 13:40 where AHQ typically get bot tier-1. By 15:40 they will have usually swapped their duo towards top side to take the other side lane tier-1. Again, the data helps support this trend of how they allocate their vision control in the rivers.

How Westdoor’s Picks Affect River Control

Global Mids: Taliyah and Twisted Fate

Global Mids

Top River Ward Difference: 0.190

Bot River Ward Difference: 0.167

The first thing you will notice is how sporadic the data is. Westdoor played three Taliyah games and three Twisted Fate games. The way he performs on these two champions are quite different. Westdoor’s Twisted Fate is typically losing in lane. He is down in CS, he is getting out pressured, and in the three games he played it he couldn’t find consistent Destiny uses. This hurts AHQ’s vision control of the river and since there are only six total games of data it can skew the results a bit.

Meanwhile Westdoor’s Taliyah is the opposite. It produces a lot of pressure since Taliyah on 6.15 has total wave priority. She controls the behavior and shape of the wave while also having the passive to roam throughout the map to place wards. You could say you have two champions on the opposite spectrum. What they do have in common is a global ultimate. Global ultimates can quickly turn vision upside down. A successful usage means you acquired a kill or objective. The success then snowballs to stronger control of that area. If a team has consistent strong control of a river or even both when playing global mids then they can quickly take over the game. AHQ are not there yet though so the teams in Group C do not have to worry as much if Westdoor gets Twisted Fate.

Non-Global Mids

Top River Ward Difference: -0.18

Bot River Ward Difference: 0.161

When AHQ play non-global mid laners their control of bot lane rises. Westdoor played Malzahar four times, Lissandra twice, and Kassadin twice. Malzahar should enable stronger vision in one river since he can be a lane bully. Lissandra can win or lose depending on who she faces while the Kassadin should straight up lower vision control, which he did. The thing is these champions aren’t the main causes of the rise in bot lane priority. It’s the support champions AHQ are taking. Four of these games Albis was on Tahm Kench and three he was on Braum. These are two of the best melee supports currently and can help you grab hold of pressure in the bot lane.

There is also another reason, Mountain’s increased ganks mid when Westdoor is on non-global mids. If he can secure pressure mid and AHQ’s bot lane is winning independently then obtaining vision control of bot river is relatively easy. Ziv is still left on his own in these cases. The only reason you see the top river control spike at the end is again due to AHQ swapping their duo topside after taking bot tier-1.

Deep Ward Control

The B and R after Top and Bot represent what jungle quadrant I am talking about.

Blue Side

Blue Side Data

Blue Jungle Top Deep Wards: 0.000

Red Jungle Top Deep wards: 0.107

For those curious on why I am filtering this data by side, it gives a stronger tell on how a team both protects their own jungle with deep wards and how they assault an enemy’s jungle with wards. In AHQ’s case, they don’t have strong control over top side typically. They are able to get some deep wards of their own down, but it’s nothing massive.

The reason their deep vision of the enemy’s jungle is even this high is mostly because their opponents put more ward focus in AHQ’s jungle versus their own. I would also say the ward difference for the red jungle is this high is because of Albis’s roams. He occasionally roams from base towards the top half of the map. He helps secure additional vision before heading back bot side.

As an additional note, most of AHQ’s games on blue side were against M17 and HKE. These weaker teams allow AHQ to take the bot tier-1 first as I mentioned earlier. The result is Albis being able to help clear wards and secure deep vision when AHQ swap their duo top side.

Blue Side Data

Blue Jungle Bot Deep Wards: -0.071

Red Jungle Bot Deep wards: 0.000

AHQ’s deep vision control on bot side seems to be a bit lacking at first glance when on bot side. Part of this comes from the way Mountain plays around Nidalee and Rek’sai when on Gragas. He takes an approach to minimize the camp differentials by farming more. However, higher tempo junglers should find more opportunities to invade if they just facing a Gragas trying to farm. I mentioned earlier as well how Mountain delays his ganks bot so him invading bot side doesn’t occur much in the first 10 minutes.

There is another reason here as well. AHQ’s bot lane has a strange tendency to lose focus later on in the laning phase. The first five minutes AHQ’s duo plays rather smart. Whether it be giving up pressure or forcing the third wave to bounce back to them they seem to have a good idea on what to do. However, as the early game progresses they try attacking the bot tier-1 without considering the location of their jungler and the enemy jungler. It leads to messy fights and deaths even. A kill can allow the opposition to move into AHQ’s jungle quadrant to take hold of vision and camps.

The deep negative spikes at the 13:40 mark cause the overall data to misrepresent their true control on top of all of this. AHQ are able to match the deep vision in their bot jungle typically while being able to produce more vision in the enemy jungle. To no surprise this again directly correlates towards their bot river control. It is also makes sense on the basis of where if the enemy team is controlling one quadrant of your jungle then you should be able to control the other side of the enemy’s jungle quadrant. Now does this case always hold, no. Teams can prevent deep vision in both their jungle quadrants while taking control of one of the enemy’s jungle quadrants. There are not enough strong LMS teams currently though for such a team to dominate vision like this against AHQ.

Red Side

Note: AHQ have less red side games than blue side so certain aspects of games can heavily influence results.

Red Side Data

Blue Jungle Top Deep Wards: -0.082

Red Jungle Top Deep wards: 0.041

With a lower number of games some of this data can look a bit spread out. AHQ’s trend shows a constant shift of deep vision control for both their jungle and their opponents. The end result is the teams staying relatively even. Three of these games are against FW. The dip in ward coverage is expected on top side based on the way FW played against AHQ.

Red Side Data

Blue Jungle Bot Deep Wards: 0.381

Red Jungle Bot Deep wards: -0.167

The data for bot side at first glance looks more promising compared to the top side data. Based on the bot side data AHQ are taking hold of vision in the enemy jungle, but also losing vision in their own. I wish I could infer more from this. The problem though is some of these games AHQ’s opponent places a pink ward that just never gets cleared. Every time interval the pink ward survives further alters the data for the control of AHQ’s own jungle. I am more confident in the blue jungle control compared to the red jungle for that reason.

A Little About The System

For those curious this is the first trial run of something like this by me. I always evolve the systems I work on and this one is just an infant. There is so much I can combine with this type of data to make more inferences while also if I had more variety of teams I can look at more unique stylistic comparisons. There were also other filters I could add like comparing how AHQ switched their vision control from playoffs to regionals. However, I didn’t want to take long periods of time to collect a variety of data nor do I wish to reveal that much since I am still working for a team.

I do make sure to watch all the games by the teams I analyze though to understand the context of what I am looking at and be able to refer to these in game specifics to clarify the data’s meaning.

Thanks for reading, if you enjoy my work you can support me here and on twitter Brendan Schilling.

Pictures were taken from the Garena eSports Flickr, https://www.flickr.com/photos/127961400@N06/