UOL vs H2K - Analysis of Farming

Many things may affect directly or indirectly in your game. And also we can analyse that every digital data while we are able to reach its source. Of course analysis can make differences according to players' condition. I am going to touch on "Analysis of Farming" in this text. It is useful and applying often.

Firstly I'll share to you my sources (for this match):
LoLesports and Reddit.

You can click these links and be able to reach match details.

Farming is so important for champions and as a matter of course teams. Because all champions (except supports) gains basis gold from farming. Certainly champions gains gold from kills, assists, baron etc. but farming is more stable income.

This table is an example for analysis of farming. In general I enter data into the left side of table, and my special formulas automatically calculates results on the right side.

You can see H2K and UOL's farms per match on the left side - and next to them at ratio tab their percentage increase and decrease. Herein we use 100% as base. If a player get higher than 100% , it means the player has above average. If a player lesser than 100%, so he has below average as against to his opponent.

While you are comparing teams, look at RATIOS - not MINION COUNT!

The reason of this sometimes minion counts can be tricky, if the difference is too little between two players. That's why percantel ratios are more determinative.

The results section shows us each roles' minion count. At the middle of this section (mean tab) amount to necessary minion count per minute. Between player's tab, if any of them is lesser than the mean, that means he farmed less than he had to. Herein we use colouring technique for comparing players. 

Green colour: This player have an advantage over his opponent

Red colour: This player who is fall behind his enemy

Yellow colour: It is not necessary to compare - the difference is too little or they are support players

Sometimes it is hard to imagine results just look at numbers. In such a case we can use a chart which called "radar". Thus it is much easier to realize results. In fact, there are so many numbers in the graph - for instance minion counts, minion counts mean etc. - but i prefer to remove because that will be more technical language.

Analysis processes are taking a long time and complicated as you can see. In this analysis, we use just one relative value which is farming. Indeed analyses have much more than one value and accordingly different consequences.

Thank you for reading!