Is Tanking a Viable Team Building Strategy?
Introducing the Sauriol Success Matrix

By David Sauriol
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1 January, 2018

(Editor's Note: David Sauriol is a student that I had in a class that I teach at SMWW. During that class, I generally advise not to create a player-valuation system because several exist and because improving upon them is very hard. What David is introducing here is actually a simplified system that separates from an analysis of how players add to winning, but creates a more analytics-independent classification system. This is useful because it is easy and because a lot of people think this way. It can be used in concert with more analytically-based metrics to look for where analytics and public perception are different. It can be used in a lot of other ways, but I'll let David take it from here.)

Success not just in basketball, but also in life is a highly subjective thing.  What you personally see as success in a NBA player might be a lot different than what I personally see. Is a player successful if he can score 12 points a game or have 8 rebounds per game? Analysts and talent evaluators could debate forever what the thresholds statistically would be, and even still it would be very contextual. The Sauriol Success matrix (or SSM) was created to provide a uniform framework for classifying the levels of success of NBA player careers based on unambiguous but simple statistics.

The SSM uses the most direct sources to determine what constitutes NBA career success: the views of NBA coaches, media and executives. These are the people that will decide which players get into games, start games, are selected to All-Star and All-NBA Teams, and even how long their careers last. By analyzing the number of All NBA team appearances, All-Star Game appearances, seasons played, games played, games started, and minutes played, the players are grouped into six categories:

• Superstars,
• Starters,
• Reserve/Spot Starters,
• Reserves, and
• Fringe Players

The first four tiers – Superstar, Star, Starter and Reserve/ Spot Starters – cumulatively make up another grouping, “Core Rotation” which essentially indicates players that play regularly. All relevant statistics required for the SSM have been available since 1981.

Tiers of the SSM

The following graphics show the SSM tiers and a simplified version of their basic rules. Though the rules have some nuances to handle edge cases, these simplified rules capture a lot. The detailed elements of the SSM and how to calculate it are found here.

Look at the following graphic to see examples of players since 1981 that fall into each tier of success.

Why develop the SSM when a lot of player rating methods exist?

Whereas other rating systems rank players numerically, the SSM is a categorical system that takes some basic statistics and general consensus to classify players broadly into categories. This distinction means that rather than viewing players individually they can be studied as a group within their SSM classification. For instance, the 399 players classified as “Starters” can be examined with high quality analytics to help understand who is “underrated” and “overrated” in a systematic way. The SSM also simply provides a summary of a lot of the basic stats people start with when discussing players – which is commonly used in making draft decisions, trade decisions, or starting contract negotiations.

What can the SSM Do?

By being a good historical reference on players, the SSM can also play an important predictive role in uncovering the next successful NBA players. Historical documentation of the factors that have led to Superstar, Star, and Starter level players previously can be combined with existing analytics (like for the Draft) and scouting methods to uncover players with similar indicators of success. This means that by sorting through both statistical (ex: a player’s career rebounding percentage) and non-statistical (ex: where a players is from) factors, the SSM can help basketball talent evaluators predict future successful players.

Of course this is not all it can do. The following case study will show one of the SSM’s potential uses.   

Is Tanking Worth it?

Trust the Process… that’s what they have said around Philadelphia, beginning with the period with Sam Hinkie as general manager. The Stanford MBA grad cum NBA general manager felt that he was using the only device at his disposal to acquire a Superstar - tanking three straight seasons! In his view, a team needs a Superstar to have any chance of winning an NBA title. Time is going to show whether Ben Simmons or Joel Embiid becomes that Superstar he coveted. In the meantime, however, the SSM can be used to look at the question historically to see if tanking gives a good chance for a team to land a Superstar in a single season or, like the Sixers, over multiple seasons. The Sam Hinkie teams are a useful example, as from 2013 team to the 2016 team (not in sequential order), these teams had the worst, second worst, and third worst records in the NBA. 

First, see the table below for some example #1 picks that qualify as Superstars and Stars under the SSM method. Obviously, getting access to a pool of players that has included Lebron James, Hakeem Olajuwon and Shaq “might” be worth enduring some losing. I say “might” as it is hard to say culturally what extended losing potentially does to a team. On the other hand, Derrick Coleman and Ralph Sampson may have qualified as Stars due to their All-Star selections and their teams may have been happy to have had them, but whether they really added as many wins as true stars is up to analytics.

 

The following table shows a summary of the SSM results by top Draft picks since 1981. The chance of obtaining a Superstar with the first pick has historically been about 25%. The chance of obtaining at least a Star with that pick has been about 66%, with about a 94% chance of getting at least a Starter (non-starters: Anthony Bennett and Kwame Brown). After the first pick, the chance of getting at least a Star drops significantly, in the 20-35% range up through the fifth pick. Things get worse after the fifth pick, with the odds falling below below 15% over the rest of the lottery and significantly lower the rest of the first round. By the time the second round arrives, there has never been a Superstar drafted and there is less than a 2% chance of landing a Star, with about a 10% chance of landing at least a Starter.

SSM Category	1st Pick	2nd Pick	3rd Pick	4th Pick	5th Pick	All 1st Round Picks	All 2nd Round Picks	NBA Player Overall
Superstar	25.71%	11.43%	8.33%	5.56%	11.11%	3.02%	0.00%	1.21%
Star	40.00%	11.43%	27.78%	13.89%	13.89%	8.56%	1.67%	4.02%
Starter	28.57%	54.29%	44.44%	58.33%	38.89%	30.31%	8.93%	16.06%
Reserve/ Spot Starter	2.86%	8.57%	11.11%	13.89%	22.22%	17.82%	9.62%	11.95%
Reserve	2.86%	11.43%	8.33%	8.33%	13.89%	28.70%	33.75%	28.81%
Fringe	0.00%	2.86%	0.00%	0.00%	0.00%	11.58%	46.03%	37.95%
Core Rotation Players	94.29%	85.71%	91.67%	91.67%	86.11%	59.72%	20.22%	33.24%
Total # of Players	35	35	36	36	36	993	717	2485

 

The History of the Draft Lottery

Prior to 1985, the teams drafted in reverse order of their record, with no random chance involved. This meant that teams truly could tank to get the first pick. It took a while, but the NBA eventually realized that teams would go through the pain of intentionally losing games to try to get players like Ralph Sampson and Hakeem Olajuwon. So in 1985, they created the first draft lottery which gave all non-playoff teams an equal chance of getting the 1st through 14th picks. Only 2 years later in 1987, this was changed to allow reverse order by record for all but 3 teams. Originally, the odds were fairly low for the team with the worst record getting the first pick sitting at 16.67%. These odds were altered in 1994 to 25% and again in 2005, with the latter changing the odds for picks below first. The odds were changed again at the 2017 NBA board of governors meeting. Coming into effect at the 2019 Draft lottery, the first 3 teams will all have a 14% chance of receiving the first pick.

Lessons from the 76ers

So what does this mean for the formerly Sam Hinkie led 76ers? Let us consider the single season finishes (worst record, second worst record, etc.) for those teams and look at the odds historically that they, or any team that finished at the same position, would have landed a Superstar or a Star to make their tanking worth it. Shown below are the applicable draft lottery odds (during the Hinkie years) that are then multiplied by the odds of landing a specific SSM tier player, resulting in an overall probability of getting a Superstar, etc., based on record. As you can see the odds of getting a Star level player are fairly flat from the worst record to the sixth worst record, declining by about half from first worst to sixth worst. The Superstar chances decline by more than that and drop under 1% at around the tenth pick.

SSM Category	Worst Record	2nd Worst Record	3rd Worst Record	4th Worst Record	5th Worst Record	6th Worst Record	NBA Player Overall
Superstar	12.35%	11.84%	11.31%	10.09%	7.40%	3.96%	1.21%
Star	22.36%	21.01%	19.52%	17.64%	15.43%	13.82%	4.02%
Star or Superstar	34.71%	32.85%	30.83%	27.73%	22.83%	17.78%	5.23%

Figure 1: The odds of the Philadelphia 76ers landing top picks and their corresponding chance of A) getting a Superstar and B) Either a Superstar or a Star level player based upon that chance. 

2013-14 The Sixers were 19 – 63 and finished 29^th out of 30 teams in the league. In a normal year, as you can see in Figure 1, even with the second worst record it is no easy feat to land a Superstar level Player. The odds of landing a Superstar player historically, not accounting for the specifics of the 2014 draft class, are 12%.  They improve to 21% for landing a star, or 32.85% of landing one or the other.

In that year, the Sixers fell to the third pick (with the second worst record) but were able to land the consensus top player in Joel Embiid because of medical concerns. Time will tell if Embiid will be able to hold up physically. He has already missed his entire first two years in the NBA due to injury, but he has shown in very limited time in his third and fourth years the talent that earned him the label “Olajuwon with a jump shot”.

2014-15: The Sixers were 18 – 64 and finished 28^th out of 30 teams in the league (or third worst). With this record, a team would have a 11% chance of drafting a Superstar and a 20% of a Star for a combined 31% probability of getting one or the other. In this draft, the Sixers got the third pick and selected Jahlil Okafor. At this point in time, Okafor is a player who would have been better playing 10 years ago as he is struggling to find a place in the modern NBA. He did put up solid numbers his first seasons but advanced analytics have consistently shown that his team is better when he is not playing. In fact, in 2017, the Sixers did not pick up his fourth year rookie option.  

2015-16: The Sixers were 10 – 72 and finished 30^th out of 30 teams in the league, the first year that the Sixers “succeeded” in tanking with the worst record. Even with the worst record in the NBA, the Sixers only had a 12% chance of getting a Superstar and 35% of getting either a Star or Superstar. The Sixers did get the first pick in this draft and selected Ben Simmons. Like Joel Embiid before him, he ended up missing his entire rookie year due to injury. In his second year, there are some very encouraging signs that he may develop into a Superstar or at least a Star level player. With both these players, they are clearly Starters by the SSM method, but it will take time to determine if they are Stars or better.

Overall, the 76ers were a bit lucky to have not fallen further in the Lottery than they did. They were also lucky - in a sense - to have had Embiid's injury issues show up pre-Draft and deter teams ahead of them from drafting him. (How different would the league look had the Cavs taken Embiid over Andrew Wiggins, who they traded to get Kevin Love?)

Final Thoughts on Tanking  

Beyond the Sixers and looking at the numbers for a single season, one has to question tanking as a team building strategy. Trying to get "ahead" by losing even more than some of the other bad teams doesn't dramatically increase the blind odds of getting a Star. Getting a Superstar is easier in the worst five records, but those blind odds are still roughly 1 in 10, not a guarantee. Not shown above are the pick-by-pick odds from #7 out to #14, but the Star blind odds tend to be in the 10-15% range and the Superstar values are in the 0.5% to 5% range. Whether teams find it valuable to tank for those additional few percentage points is, in some ways, up to them, but we put the probabilities out there for them to make calculations as they wish.

We call these odds "blind" because they don't account for the quality of the talent in the Draft nor of the quality of the scouts helping to select the player in the Draft. Any individual team can improve the quality of their staff to make better picks probably as much as through tanking, if not more. This then avoids the negative consequences of intentionally losing, such as

·        Financial: The majority of owners would not be willing to see the brand of their team take such a hit. Multiple years losing with a clear pathway towards success will definitely impact the ability a team has to sell tickets to games, draw television viewership and sell team merchandise.

·        Fan Base: Consistent losing will push away a lot of casual fans and see them move to other sports. Beyond the revenue loss this entails the more serious issue is that it could take years of success to attract their interest again.

·        Team Culture: Losing at that level can become systemic within the team and create a culture whereas losing is accepted as “normal.” A culture like this might not simply reset with potential star level players like Embiid and Simmons finally taking the court together, it could take years to redefine itself into a positive.

(See this for some previous work on the matter)

In conclusion, although the odds of landing a Superstar are not amazing at any finish record wise, teams can still land solid Starters with top draft picks. Within the draft lottery 75% of players end up in the core rotation, meaning they are players who at least start between 25 – 49% of their career games and play regular NBA minutes. Often they are better than that. This might not sound like much, compared to our previous conversation about landing Superstar and Star players, but having these foundational players are crucial for teams. For some context the rate of core rotation players falls to 40% from picks 16 to 30 and down to 20% in the second round. Collecting solid rotational talent has been a strategy that the Boston Celtics have used to rebuild their roster. Once they had collected enough solid players they had pieces that could be used to acquire a Star level talent in Kyrie Irving via trade and attract other Star level free agents like Gordon Hayward.  

The Future of the SSM

Evaluating whether tanking is a good NBA strategy is just the tip of the iceberg. Here are a couple topics to look for in the coming weeks.

·        What regions of the world produce the most successful NBA Players?

·        Grading NBA trades using the SSM

·        What is the architecture of NBA championship teams? What is the SSM composition of some of those teams? Is there a pattern?

Larger topics will be assessed using the SSM also. Two major projects I will be looking into are first evaluating college or international performance to look for indicators in young players that can be used as predictors for future NBA success. Secondly, I am looking at NBA players first three seasons to identify traditional and advanced statistical indicators that can also be later used as predictors of success for the remainder of that player’s career.