Prologue : Manuel for Final Four Analysis

Here we are, at the greatest stage of the European Basketball again. We are four games away from the end of the Euroleague's 2012-13 Season. Before the beginning of the greatest tradition of European Basketball (my subjective opinion), we've made series of unique analysis. But,before sharing them we prepared a manuel to make it easier to understand stats we used in final four analysis. Actually, we mentioned most of them in previous posts. Yet, it would be annoying to go back number of older posts to remember older stats,I believe. So, we decided to create this post.

Play

Play is a stat that we frequently use. We first talk about Play in T-Con Post. We use Play as an alternative for Possession. Basically, Play shows an offense which takes place between start of a shot clock and start of an next shot clock. Every move which resets shot clock time is considered as a Play. We give up using Possession,because Play fits better in our formulas since it includes every offense even the ones after an offensive rebound.

T-Con


T-Con is a tool that we used to measure players' tangible contributions in the game. It includes lots of data and formula and we showed how to calculate T-Con in a previous post. I will mention its general characteristics. First of all, I came up with T-Con since I've never believed in PIR. In T-Con, we evaluate every possible scenario and outcomes of these scenarios for every move a player makes. One of the greatest features of T-Con is it takes both team's and opponent's performances into consideration while evaluating a player's performance. For instance, players penalized for their missed shots by considering their team mates' shooting performance. If a player's team mates have a good field goal percentage, he would be penalized more than a player who has better field goal percentage than rest of his team.

T-Con has also some gaps like team success. Yet, since we are making analysis for four F4 teams and it would be logical to assumed that they have similar success rates, this problem doesn't effect us of now. But, we will integrate team success into T-Con later on of course.


Play Making Abilities

It is another long analysis. You can find stats that used to calculate Play Making Abilities in Who Runs the Show Better post. It basically measures play making abilities of team's point guards.

Rebound Rate

Rebound Rate for team's is not one of our stats. You can find it  in any other site. It shows how many percent of the rebounds in defensive or offensive rebound pool a team grabbed. We adjusted this formula to players by using minutes they played and plays they involved. It would be much healthier to calculate that numbers by using real numbers instead of adjustment. Yet, as I've said before, it is a gigantic problem
to reach some advanced numbers for Euroleague games sadly.

Shooting Stats

I've used some extra stats while measuring shooting abilities. One of them was Opponent's Strength. It shows, how opponents defends shots. Finding these numbers was crucial to measure hardness of shots and evaluate shooting performance. Another stat that I needed to use was Volume of the Shots. Since, great shooters tend to reach great numbers by using lots of shoots, number of shot attempts is very important for such evaluation. So, I've formed up the shooting function of the Euroleague Season 2012-13 Season by using shot attempt numbers. After that, I've form up probability density function for this system. Thanks to that, I've managed to integrate Volume of the Shots to the shooting evaluation.

Play Oriented Winning %

It's a whole new stat that we used in the Final Four Analysis for the first time. It shows which team has bigger chance to win the game according to pace of the game. There would be another post to introduce this stat extensively. Now, I'll just talk about main principles of it.

First of all, I've analyzed all games of the F4 teams in terms of number of plays and points made. Then, by using this particular data set, I've created  Winning Function for each team. After, I've started to compare every team with each other. I've determined winning zones for each team by number of plays they made by using these comparisons. For example, more defensive teams prefer making lesser plays and force their opponents to do the same. So, in a low pace game (in which lesser number of play occured), defensive teams has bigger advantage. On the other hand, if number of play tends to increase, then winning chance of a defensive teams decreases while more offense oriented teams' increases. Hence, this functions show how should any of these four teams adjust pace of the game to increase their winning percentage.