Mistakes Basketball Coaches make when using statistics



All coaches want to win more basketball games, this is an evident fact. So dedicating hours on end, reviewing game footage, running drills to get players prepared for in game scenarios and training them strength-wise so they are fully game ready is a predetermined goal.

While as a coach all the above apply, your team is backed by the community, game in, game out; parents, supporters and fans alike prefer to see results. This is where statistics in the sense of end game results really matter. It’s the one thing that can give you the edge over your opponent when preparing your team to its potential.

Almost all teams these days rely on boxscore results and try to comment based on them, however it’s a fact that more than 85% of coaches internationally rarely fully grasp how statistics in the format of boxscores only point out problems that their team’s face. Out of the 15% of coaches that properly can comment on stats even consider making use of an analytics tool that allow for better decision making and provide insight. Would it surprise anyone that only less than 5% of international coaches actually make use of analytics the way that it is supposed to be. Used for solid decision making and that allow their teams/players to pinpoint focus areas to grow further.

Again, falling back on the fact that stats simply explain whats happened in a game at a very high level; i.e; Player A making three 3pt shots and four 2pt shots as the entire team scored a total of 56 points yet won only by 1 point.

IMG_0715When looked at in terms of analytics, the behavioral insight for your team should potentially be highlighted and a critical point is that any coach, assistant or head coach should be able to see adjustable areas that allow them to express how decision making at a higher level in/post or game can be executed.

A coach that states “the team does better when they play a more moderately slow pace and make use of shot clocks that allow full possessions to be executed, our entire lineup/player rotation does way better…” Once again falling on the fact that a very small percentage of coaches really express these kind of insights is proof of how statistics when reverted to analytics really help out their organization.

Since the beginning of Advance Pro Basketball I have come across teams I have seen as potential clients make use of the incorrect players during wrong possessions while playing, this creates stagnant efficiency and takes a coaches game plan the wrong way and while a coach can diagnose all the mistakes it takes away from the solution efforts.


Making use of possession and playing at a pace that will allow for optimal possessions to be executed are by far a point that we thrive on at Advance Pro Basketball. It not an easy thing to have our clients or potential customers commit to this concept but those that do really get that neglecting this means losing games even before they are played. Teams that understand the best options to execute the best half court offense or best small ball plays; when to pressure the defense or counter strike appropriately have a 37% improved chance of winning games by the end of the first quarter of a game.


Turnovers are one of the pesky areas of the game that have been more and more criticized by everyone from fans all the way to the highest level of coaching and playing. Ever hear that a player or a team has to be much better at “keeping the ball safe” or “commit less turnovers” these are all very general in comparison to the different types of turnovers that come about. Good coaches no matter they use of analytics can visually see how types of turnovers cause problems but when it comes to addressing them find it tricky to explain.

Explaining to a team that they have “overall 20 turnovers out of which only 4 are double dribbles yet the main issue is unforced balls that have been thrown away” all the while meaning to state that the team needs to practice their passing skills more than anything else is how analytics of this type should be properly executed.


Do not get the wrong impression! Stats at a per game level are not the same thing as possessional analytics. Its rare that analytics tools in terms of game logging tools really delve into this area but by far Pivot Sports Analytics do a great job in directing attention to these values accurately and bring out the strength/weaknesses of players accordingly.

In a nutshell, possessional analytics shed light on various players or lineups that end up playing alternating amounts in game situations when we look at the data that is captured or logged.

Plainly stated it really inefficient and not any way accurate when you’d compare PPG of a player that say plays +20 minutes versus a rotational player that only gets about 8-9 minutes in the same competition.


When looked at all three points they all intertwine to one overall concept, analytics, details that the old school or the modern way basketball is seen can explain many things. The good old eye test that everyone can comment through or those that prefer to make sensible understanding of the numbers converted into smart decision making allows teams to compete smarter, win at a slightly better percentage and even train accordingly.


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