NBA Season Preview: Stats Are Your Friends, But You Need Better Friends

With the start of the 2011-2012 NBA season only weeks away at this point, I wanted to take this opportunity to pass along a few general concepts and specific stats that can greatly enhance an NBA fan's appreciation of the finer points of the game. Back of the basketball card stats (Pts/gm, Reb/gm, Ast/gm, etc.) and standard game box scores undeniably represent a familiar and comfortable style of analysis deeply embedded in the lexicon of NBA fans everywhere, but it is important to know that intelligent efforts have been made to interpret and express the information provided in traditional box scores in more meaningful ways.

I would never defend traditional box scores as the best available information on individual performance in a basketball game, and seriously better alternatives exist for those more serious about detailed events in the game, but this post is starting small by showing some ways you can learn more precise things just by repackaging information in those old, faithful box scores. As far as I am concerned, you can never have too much information, and every attempt to achieve a deeper understanding of player performance has something to teach us all about how to watch and enjoy basketball on a deeper intellectual level. Here are just a few basic concepts to keep on your mind when the NBA gets back to business. Enjoy.

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(1) Possessions are the indisputable essence of performance analysis in basketball. The singular goal in every game of basketball is to outscore your opponent, and each opportunity to score points (or to prevent the other team from scoring points) comes in the form of a possession. Possessions always alternate between teams within a game, so in a head-to-head matchup each team will use roughly the same number of possessions. Therefore, the team using their possessions more efficiently in a given game will win.

None of the statements above may seem very controversial at first blush, but many people still mistakenly rely on per game measures of offense and defense when attempting to assess and compare the effectiveness of different NBA teams. The problem with relying on per game measurements (points scored per game and points allowed per game) for this purpose is that teams play at a variety of different "paces" when not in direct competition, and thus per game measurements inadvertently obscure true team efficiency. Here is an example that highlights the problem:

Example: Team X is a run and gun team that averages a stunning 108.8 points per game, which is the second highest points per game average in the NBA. Meanwhile, Team Y is a plodding team that thrives in half-court sets and averages only 98.1 points per game, which is the 21^st-ranked average in the NBA. Team X appears to be a superior offensive team based on per game numbers, but we intuitively know that Team X has more opportunities to score in each game because they play at a much faster pace than Team Y. So how much bias does style of play introduce into the comparison? Let's see how each team grades out on a per possession basis.

Despite the lofty per game scoring numbers, Team X really only scores 1.054 points per possession, which is the fourteenth most efficient in the NBA. Meanwhile, Team Y scores 1.080 points per possession, which is the seventh most efficient in the NBA. Team Y actually has an offense that is significantly more efficient than the offense of Team X. Although the difference seems small when expressed on a per possession basis, it is often expressed on a per 100 possession basis (usually called Offensive Efficiency and Defensive Efficiency) to put the important differences in efficiency in a more digestible form. Team X has an Offensive Efficiency of 105.4, while Team Y has an Offensive Efficiency of 108.0. Even though Team Y plays at a slower pace than Team X, Team Y clearly superior offense because Team Y uses its possession more effectively.

Note: In case you were interested, Team X is the 09-10 Golden State Warriors (25 wins - 56 losses). Team Y is the 09-10 Portland Trailblazers (50 wins - 32 losses).

Here is the ultimate point I am trying to make about focusing on points per possessions: the only reason we take the effort to make comparisons between the offensive or defensive numbers of different teams is to help determine which team actually has the better offense or defense. Per game measures of offense/defense are inaccurate measurements because they obscure true efficiency by failing to account for pace. Per possession measures of offense/defense precisely capture team efficiency because effectiveness is measured with regard to each opportunity a team will have.

If we make a comparison between teams, why not take the effort to use the measurement that most precisely expresses what we are actually interested in? Offensive Efficiency and Defensive Efficiency give us the precision we desire to make meaningful comparisons between teams, and that is why these measurements should be used in place of any per game stats.

Traditional box scores record many meaningful events (made/missed FG, made/missed FT, assist, steal, offensive/defensive rebound, foul, turnover, etc.) that take place during a basketball game. Prevalent back-of-the-basketball-card stats (Pts/gm, Reb/gm, Ast/gm, FG%, 3PT%, FT%, etc.) are familiar to everyone and are certainly a comfortable point of reference for basic player comparisons, but in some cases we can use advanced metrics to get a better snapshot of player efficiency. Let's take a look at a few of the most valuable advanced metrics:

(2) Advanced metrics are often materially superior expressions of player efficiency in comparison to the traditional box score measures.

A. True Shooting Percentage (TS%) = PTS / (2 * (FGA + 0.44 * FTA)). A made three-point field goal is worth more than a made two-point field goal. That statement is far from profound, but the tandem element rarely acknowledged is that both types of shot attempt only use one possession. This has serious meaning when it comes to performance analysis, and TS% is a metric that adjusts for the added value of a three point make.

Furthermore, TS% also incorporates the different costs associated with free throw attempts as well, allowing two and three-point efficiency and free throw efficiency to be distilled into a single number. Free throws are of course still shot attempts, so it makes sense to include these shots in a metric that seeks to express shooting efficiency. However, a single free throw does not typically use a full possession, because many times a player is awarded two free throw shots (the .44 multiplier is used because it is estimated that 44% of free throw attempts represent the end of a possession). Like the three pointer, the free throw is another high efficiency shot that tends to be undervalued by traditional box score metrics.

We try to make these informal adjustments based on position and opportunity all the time (we expect big men to have higher FG% because they shoot closer to the rim, and we expect guards to have higher 3PT% and FT%), but the ultimate goal is to have your team allocate the majority of their possessions to their most efficient offensive players, regardless of position. Since we really want to know about the shooting efficiency of given player, it makes sense to embrace TS%, a metric that does the heavy lifting with a guaranteed accuracy.

With TS%, fans can have a single shooting percentage to compare players who might have opportunities to shoot from very different places on the floor, instead of being forced to make informal (and probably inaccurate) adjustments between FG% and 3PT%. Observe:

Example: Imagine you open your browsers and find last night's box score. Look at the three listed players and rank their overall shooting performances in order from best to worst. ***Answer posted at the bottom of the article.

B. Assist Rate (AR) = (Assists * 100) / (FGA + (FTA * 0.44) + Assists + Turnovers). Assist per game numbers can tell you some basic information about a player's passing prowess, but what if you want more? Assist Rate works to approximate the percentage of possessions used by a player that end in him dishing out an assist to a teammate. AR not only provides information about how well a player dishes out assists and avoids turnovers, but also highlights a player's distributive tendencies relative to his appetite for shooting and turning the ball over.

If you have ever wanted to dig deeper into learning about the most effective and willing creators in the NBA, check out Assist Rate numbers for the percentage of plays in which a given player creates an assist. Players like Andre Miller, Kyle Lowry, Mike Conley, Hedo Turkoglu and Andre Iguodala shine brighter under AR, while high volume players like Russell Westbrook, Monta Ellis, Tyreke Evans and Derrick Rose take a bit of a hit. Similar stats exist for turnovers and rebounds as well, aptly named Turnover Rate and Rebound Rate, so if you are interested in the concept of rating player skills in a normalized manner, be sure to head to hoopdata.com for more information.

One of the biggest complaints I hear about advanced statistical analysis is sports is that it sucks the fun out of the game. I fully understand and appreciate that few people want an informal statistics course to break out in the middle of a basketball discussion, but statistics aren't meant to take the fun out of basketball, they are meant to enhance our knowledge and refine our level of observation and understanding. For being so simple, basketball is exceedingly complex; therefore, I encourage you to find ways to use advanced stats and the underlying concepts that inform them to find new ways to view the game and digest the story of what is happening on the court. Now that you are equipped with some tools that will accentuate the finer points of the game, enjoy the 2011-2012 NBA season.

Here are just several basic stats that deserve your attention heading into the season:

***TS% Example answer: If properly ranked from best shooting night to worst, the list should go: C-B-A (see how I made a sick lockout joke out of a math-based hypothetical? Yeehaw partystyles. Here's the actual breakdown:

For more information on advanced stats, make sure to check out this wonderful advanced stats primer from SB Nation's Golden State Warriors blog, Golden State of Mind.