If we take some of the battleground stats from the armoury and use them as “performance indicators”, we can get a measure of class performance, as well as individual performance. There are some problems with this, as we’ll see in a minute, but the results are interesting nevertheless.

The performance indicators I like best are killing blows per game and deaths per game, since these give some indication of the performance of the character or class, as opposed to the performance of the team. (Of course they are not completely independent variables. For example an effective team may try to protect the squishies and the healers who should then have a lower death rate.)

Here we take a sample of level 19 WSG players with more than 100 games played.  We can chart these two indicators to give a view of the effectiveness of each class. In this graph I use the inverse of deaths-per-game, so that the sense of each axis is the same. Basically – the further away from the origin the better, along both the x- and y-axes.

This is what we get:


Class performance, 19 WSG.

There are a few interesting things here. The first is that there a clear grouping of classes in the top lefthand corner (around priests) whose role is not primarily individual combat. Priests heal, Druids CC, heal and do the bear flag run thing. What surprises me is to see Paladins so close to this group. Does anybody know why that might be? What do pallies do in WSG at 19?

Out along the bottom right, you see the attack classes – they die a lot more than the druid/priest/pally set, but they do a lot more damage too. The most unexpected thing here is the power of the much-maligned warlock. Although they are the squishiest class (closest to the origin on the y-axis is bad, remember) they can certainly dish it out – more than rogues. The stand-out class is the hunter – significantly more a damage dealer than the rogue, for basically the same death rate. I suspect that a lot of players don’t know that, since the rogue seems to be the most popular choice amongst the serious WSG player at level 19.

The division between attack classes and “support classes” (perhaps an unfair term since running the flag is a bit more than “support”) helps explain the observation I made in the last post – that there is not a high correlation between killing blows and deaths. Several classes are doing something other than killing.

Before we leave this subject, I want to show that these averages are interesting and informative, but they must be taken with the proverbial grain of salt. Averages tend to be influenced by outliers, and to abstract from the fact that the better players (or the richer twinkers perhaps…) can get a good performance from most classes. If we take three classes that are close to each other on the above chart – mages, warlocks and warriors – and plot the individual values used to form the averages, then we get a different picture:


Character performance.

You can see that a lot of players have similar performance and the averages tend to be skewed in one direction or another by smaller groups of outliers. On the other hand, the averages do provide some real insight since you can see that mages have no strong killers at all and that must reflect something about the class as well as something about the player.


Warsong Gulch chart porn

March 20, 2009

I’ve been having a bit of fun with the battleground stats data from the Armoury. There are plenty of good strategy guides on the net for each battleground, but it’s interesting to see how well the strategy is reflected in the data. A good chart really is worth a thousand words…

Warsong Gulch is our example here. You probably know that there are a number of traps in what seems like a simple game. Trap number one is to be on a team where everyone wants to run to the middle of the field and have a big punch-up while the flag carriers run by unchallenged.

The following charts are for level 19 characters who have played at least 100 games, so we’re not talking about noobs here. But you can still see all the nuances of the game in the data.

For a start, teamwork and focus on the flags rather than on scoring kills is vital to winning. So, if we chart games won to killing blows struck by individuals, we don’t find a strong correlation. You can help to win by doing other things than killing – CC-ing, running interference, guarding the flag rooms.

Killing blows vs games won.

Killing blows vs games won.

Being able to drop the opponent does have one important role:  getting the flag back when the other side is running with it. We can chart flags-returned to killing blows, and we get a stronger correlation:

Flags returned vs killing blows

Flags returned vs killing blows

But again, capturing the flag from the other side is about skills other than fighting and the data proves that. In fact, this is my favourite chart since the whole ding an sich of the game is in there. The best characters at capturing the flag are generally those with lower killing blow scores. They’re too busy running and hiding to be killing. So you get a gentle negative correlation as the chart shows:

Flags captured vs killing blows.

Flags captured vs killing blows.

The purpose of this exercise is to see if these indicators can be used to pick out twinks from the data. I’m confident that they can. So, the next chart shows deaths per game vs games won, and suggests what we all know – that the character with the best gear and enchants stays upright for longer. They spend less time running back from the spawn point and more time on-target.


Deaths per game vs games won.

Dead toons don’t win games – it’s not rocket science.

One interesting point is that there is a poor correlation between deaths per game and killing blows per game, which surprises me. I would have thought that twinked characters both killed more and died less. Perhaps there is a kamikaze style of player that kills a lot and dies a lot, and a more um… tactical… toon that can dish it out without getting too much in return.

Deaths per game vs kills per game.

Deaths per game vs kills per game.

One final point – if you look carefully at the last chart, you will see the bane of the armoury data miner – the annoying little outlier that makes all our averages skew away from the median. That character circled on the bottom right of the chart is one lean mean killin’ machine, a real leader of the pack. Here’s his armoury profile – check him out. He’s a twink, no surprise there, but he doesn’t seem out of the general range of twink stats. To me, he is a reminder that skill does play a part in the game too. Mind you, he played nearly 900 games to get that good.