Using Efficiency Ratings in Greater Detail

In past posts we have discussed the concepts of OER (Offensive Efficiency Rating) and DER (Defensive Efficiency Rating) that have been around for at least 50 years. For the very few uninitiated, for OER one divides the number of points scored by the number of possessions for any time period- say a team scores 80 points in an 80 possession game, obviously that game’s OER is 1.00. In that same game, your opponent scored 70 points on 80 possessions. Your DER (and their OER) would be .88. Goals can vary from level to level and program to program but in general, anything over 1.00 is a good OER and anything under 1.00 is a good DER. Points per possession obviously takes tempo into account so that we’re comparing apples to apples, so to speak.

For those who have used these concepts, the most obvious benefit is helping players understand the value of a possession and that they are indeed finite. Another common benefit is referencing a segment during a game where the offense might have gone 6 or 7 possessions in a row without a score, as an example, or 5 or 6 possessions in a row giving up points. Generally, players know when the team isn’t playing well but a graphic illustration can pinpoint the exact situation and bring it into focus with greater clarity.

For a long time, the basic principles of OER and DER seemed very advanced. That is, until the explosion of analytics and metrics came upon the game. Of course, the NBA has led the way because of the high financial stakes incumbent upon winning at that level. Not all teams participate to the same degree but everyone at that level is invested and no one is going backward.

As the NBA has been at the forefront of the revolution, many programs at the college level have followed because of the inherent pressures to win at that level. Tournament participation and TV revenues are relatively just as important at the college level as they are at the NBA level-not to mention the effect winning big has on the future freshmen applications. Three quick examples follow. When George Mason went to the Final Four in 2006, two years later their freshman applications were up 30%, but the real eye openers were after Butler’s Final Four appearance in 2010 and Wichita’s St.’s appearance in 2013, freshman applications were up 41% and 81% respectively.

While coaches at the high school level aren’t faced with necessarily the same pressures, anyone who watches high school basketball on a regular basis knows that winning isn’t considerably less important on that level. It’s in everyone’s best interests to keep searching for competitive edges and analytics (metrics) is proving to be the most promising resource.

So, how can using the concepts of OER and DER in more detail help give a program an additional competitive edge? The answer is quite simply by keeping track of OER and DER in every phase of the game by category. It starts with the person who is assigned to chart OER/DER in game or post game. That person needs to be familiar with the system and should be able to “tag” a possession in various ways. For instance, if the head coach calls a specific play or defense to be utilized, the charter “tags” that play or defense on the chart. Similarly, if the the opposing coach uses a specific play or defense, that can also be tagged on the DER chart. Obviously, this in-game approach is most ideal because then the head coach can receive in-game data which can be used for in-game decisions. For those programs who can’t utilize a knowledgeable charter who can make the correct tags in-game, one will have to rely on a post-game OER/DER charting session. This, of course, serves as valuable data in and of itself.

Whether the charter is tagging in-game or post-game, the most obvious and useful types of tags would include:

  • TRANSITION: These offensive and defensive possessions should certainly be isolated from other possessions because they tell a completely different story for the coaching staff than half-court possessions. For purposes of this article, let’s tag transition possessions with a “T”.
  • HALF-COURT MAN: These possessions would be tagged HM. If the possession started as a transition possession, it would first be tagged T and if there was no score off the break, it would also be tagged HM.
  • HALF-COURT ZONE: These would be tagged HZ whether the possession started as transition or not.
  • PLAY, ACTION, DEFENSE OR CALL: Whenever possible the action which creates the shot should be tagged so that in game and post-game analysis can be developed. This category would be the most difficult to tag because of the variety of different actions offenses can utilize. A few examples would be SR24 (high screen roll-24 with ball), DD5 (Dribble drive #5), PP 5-24 (Penetrate and Pitch #5 for #24).
  • REBOUND: Tagged R if the possession was extended by an offensive rebound.
  • FOUL: Tagged F if the possession was extended by a foul for which free throws weren’t taken.
  • BASELINE (or SIDELINE) OUT-OF-BOUNDS: Tagged OB or SB to track OER or DER for just such plays.
  • FULL COURT PRESS OFFENSE (or DEFENSE): Tagged FP for any possession which begins with full court pressure.
  • HALF COURT PRESS OFFENSE (or DEFENSE): Tagged HP for any possession which begins with half court pressure.

It should be apparent by now that a possession can be tagged several different ways. For example, a possession can start as transition, turn into half court man, include a rebound, then a foul. If a FG is scored after the foul, the points are assigned to HM, R and F but not T because the FG wasn’t scored in transition. It should also be apparent that a lot of work is involved but the end result is that the head coach has at his disposal numerous specialized OER’s and DER’s in addition to the game OER and DER.

Keep in mind several factors:

If one charter is utilized, it may take both in-game and post-game views to calculate all the final data.
Two charters could be used and one could only track #4 above (Play, Action, Defense or Call).
Based on the OER/DER breakdowns by category, a coaching staff receives very graphic information on the effectiveness of specific areas. For instance, my team’s overall OER might be 1.00 but only .89 vs zones and .96 vs full court pressure etc. This type of data needs to be known so that a coach is addressing weaknesses as early as possible. These stats help to eliminate guesswork.
All coaches use the eye test to make decisions and have instinctive “hunches” based on experience. Detailed OER/DER analysis and other metrics lends credence to the eye and makes hunches more calculated, thereby possibly adding competitive edges.

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