The Real Reason Spurs Players Are Underrated

In the next two weeks, we’re going to hear all the explanations for why the Spurs get so little publicity. The most popular reasons – they’re businesslike, they feature an unselfish balanced attack, and they play in a small market – are somewhat accurate. However, the main reason Spurs players get so little publicity is simple – they don’t play a lot.

San Antonio did not have a single player average 30 minutes per game during the regular season. Every other NBA team had at least two, and most clubs had three or four. What does this have to do with publicity? Most of the media still uses meaningless per game stats for evaluation, and it is hard to shine in these categories while getting so few minutes per game.

Only one Spurs player, Tony Parker, ranked among the league’s top 50 in points per game (minimum: 1,000 minutes played), and he placed 45^th. Points per 40 minutes, which evaluates scoring far better, tells a completely different story. San Antonio placed four players in the top 50 in points per 40 minutes – Parker, Tim Duncan, Manu Ginobili, and Patty Mills) – which tied the Suns for most in the league.

The Spurs had five players among the top 50 in John Hollinger’s PER (Player Efficiency Rating), with Kawhi Leonard joining the aforementioned group. That led all NBA teams. Their NBA Finals opponent is the only other team with four. PER also does not get impacted by playing time.

Parker ranked just 15th among point guards with 16.7 points per game. However, he placed seventh with 22.7 points per 40 minutes. He doesn’t play nearly as much as other elite point guards, and that’s the main reason he gets less attention.

Given the rapid growth of the San Antonio market – combined with the soaring population of Austin just an hour and a half to the north – it’s not exactly remote. The Spurs also do not possess a balanced attack. Four San Antonio players attempted 15 or more field goals per 40 minutes. Only the Pistons (five) had more. The Spurs scoring appears balanced because Gregg Popovich distributes playing time so evenly, but Parker, Duncan and Ginobili all have high usage rates.

Like so many topics in sports that get overanalyzed, the truth is in the numbers.

 

A Breakthrough for Role Players

For several years, The Sports Resource has recommended companies use non-superstar players for endorsements. Role players who excel in specific ways or possess unique traits can build brands at a much lower cost than superstars.

The news that Hawks guard Dahntay Jones signed a partnership deal last week demonstrates that companies are coming around to this concept. The 6-6 Jones sees just 12.4 minutes per game, but plays sensational defense.

With this approach in mind four years ago, we created a sample on Marreese Speights. What makes this a winning strategy for brands? 

1)      Many role players, such as Jones, have large audiences on social media. He had over 21,500 Twitter followers. This creates opportunities for brands to interact with thousands of fans through the player’s voice. 

2)      Every NBA player excels in at least one vital area, or else he wouldn’t be on a roster. For a defender like Jones, brands could use insightful defensive metrics to activate the sponsorship. 

3)      The cost to sign role players to deals is far less than what it takes to land a superstar.

We also believe companies should identify and sign promising young players for endorsements before they break out – a tactic where analytics provides a huge edge and can save millions of dollars.

Speights, now just 25, possessed considerable upside four years ago. And while he’s yet to see big-time minutes, he remains a very productive role player. Speights puts up 20 points and 10 rebounds per 40 minutes. Only 10 other players currently match that achievement, including stars like Blake Griffin and Tim Duncan.

Should this trend gain traction, players who build their brand on social media will get endorsement opportunities that only the superstars previously enjoyed. As for brands, we’ve already detailed why it pays to activate sponsorships with statistics. And that approach works great for all types of players.

Complete Halftime Analysis

Most halftime shows include comments from former players and coaches about how teams must “pick up the intensity” or “step up” in the second half. In basketball games, analysts talk about strategies like “getting the ball inside” or “taking better care of the basketball.”

While such input from former players and coaches is valuable, it is far from complete analysis. You need to get into the numbers for that to happen. Sports analytics provides powerful insight and doesn’t need to involve anything complex. The concept of regression to the mean reveals far more about what to expect in the second half, and only requires comparing a few key stats.

Let’s say one team shoots 8-for-10 from three-point range to grab a 10-point lead while the other clanks 1-for-9. If both teams entered the contest shooting 40 percent on the season, it is almost certain that both teams regress to the mean – the 40 percent mark – in the second half. Defense impacts these stats, but randomness (or luck) is a huge factor in small samples. As more shots get taken, teams should move toward their season percentage and cause the score to tighten up.

Free throw percentages are another great stat to examine at halftime. Unlike three-pointers, they aren’t defended. So randomness plays an even greater role.

I believe broadcasts will soon have a statistical expert offering such insight – alongside coaches and/or former players – on halftime shows. But until that happens, we can all do it ourselves.

Do-It-Yourself Three-Point Shooters

With five seconds left on the shot clock and all their teammates covered, guards have to create. Some perform much better at it than others.

Creating and then converting a three-pointer is basketball’s version of a grand slam. A 24-second violation nets nothing – and a wild shot attempt isn’t much better. So it’s a three-point swing if a player can nail a three off the dribble. Since few players shoot high percentages in these situations, the players who excel have tremendous value.

After evaluating all three-point shooters for volume, accuracy and the ability to create their shot without an assist, Spurs guard Gary Neal stood out. He hit 41.9 percent overall from three-point range last season, even though only 54.2 percent of his made threes were assisted. On average, 84.2 of NBA three-pointers were assisted in 2011-12.

Most top three-point marksmen have a very high percentage of their threes assisted. That’s no problem of course, it’s their job to spot up and drain threes. But it makes players who can convert threes off the dribble even more valuable, especially for teams that don’t get many open three-point looks from their set offense.

In addition to Neal, other players who shine in this area include Kyrie Irving, Kyle Lowry, Jose Juan Barea and Lou Williams. 

The Common Factor

Besides playing for the Oklahoma City Thunder, Kevin Durant, Russell Westbrook and James Harden don’t seem to have much in common. And that was the case when the Sonics/Thunder selected them in three consecutive drafts, except for one key factor.

All three players were exceptionally young for their class. At 18.74 years old on draft night, Durant was the youngest freshmen (and player) taken in the past five drafts combined. One year later, they landed the youngest sophomore from these five draft classes. Westbrook, at 19.62 years old, was actually younger than many freshmen in the 2008 draft. Then they took Harden in 2009. Only one other sophomore besides Westbrook was younger than Harden at 19.83.

As a result, the Thunder nabbed three players with far more college playing experience than prospects their same age. The Sports Resource Newsletter covered this topic last year. Westbrook, for example, had played 75 games for UCLA. Most of the draft selections close to his age had fewer than half that many.

Obviously, it wasn’t just about their age relative to their class. Durant and Harden also put up outstanding statistics, but so had many others in their draft class. Their numbers were made far more impressive by the fact that they were over one year younger (in some cases) than players that shared the same college class.

Maybe other teams valued this common factor, but went another direction on draft night. Perhaps it’s just a coincidence that Oklahoma City exploited this edge three straight years. Whatever happened, the Thunder may soon start the next NBA dynasty because of those selections.

The Accelerators: Point Guards who Pick up the Pace

When Pooh Jeter took the court for the Sacramento Kings last season, his teammates had to be ready to run. Based on a metric comparing team pace with and without each NBA player on the court, Jeter increased the pace more than any other point guard.

The Kings had 4.1 more possessions per 48 minutes when Jeter played versus when he sat. Only three players at any position – who saw at least 750 minutes in 2010-11– surpassed him.

This stat is just one way to put words into numbers and tell a story. While a scouting report saying a player pushes the ball is strong evidence, it becomes even more powerful when hard statistical information backs it up.

Three starting one guards followed Jeter in this category: Jose Calderon, Russell Westbrook and Stephen Curry. Jeff Teague, another backup point known for his quickness, placed fifth.

This metric may not always demonstrate speed. Calderon, for example, could excel at getting the Raptors a good shot early in their offensive sets. So while he’s not the type of guard who usually pushes the ball, Toronto still played faster with Calderon in the game.

This stat does get influenced by who shares the court with each point guard. Obviously, you can’t run if your teammates can’t keep up. It also matters who plays the same position for their team.

Nonetheless, NBA agents now have another tool to show how their free agents can impact clubs looking to up the tempo.

The Problem with Per Game Statistics

With so many better metrics available, it’s hard to believe the mainstream sports media still uses per game statistics to evaluate player performance.

ESPN Radio’s Colin Cowherd recently compared Derrick Rose to Allen Iverson. The comparison makes sense on some levels. Both players are shoot first, pass second point guards. Both are incredibly quick and great finishers. Cowherd’s mistake was using per game statistics, which made the players appear closer in performance than they really are.

Cowherd started by saying Iverson had the edge in points per game over Rose in their third NBA seasons: 26.8 to 25.0. This brings up the biggest reason per game numbers fall short: starters vary tremendously in how many minutes they see per game. Iverson played 41.5 minutes per game versus 37.4 for Rose. Using points per 40 minutes to even the playing field, Rose (26.7) has actually scored more than Iverson (25.8).

Rose had a huge edge in assists per game (7.9) over Iverson (4.6) in their third seasons. That difference increases with the more revealing assists per 40 minutes figures: 8.4 to 4.5. Iverson did spend extensive time at shooting guard that year while Eric Snow played point for the Sixers, which impacted his assist numbers. Still, Iverson never came close to matching Rose’s assists per 40 minutes figure in any career season. Rose had also shot for the higher percentage from both two-point (47.2 to 44.0) and three-point range (33.2 to 29.1) in season number three.

Rose had the advantage in John Hollinger’s PER as well, 23.4 to 22.2 over Iverson. Both players have high usage rates – which estimates the number of their team’s plays they use while on the court – of nearly 33 percent. So while they both use a high percentage of their team’s possessions, Rose produces more in those opportunities.

Iverson did have a big edge in steals per 40 minutes in his third season. And while he reached the foul line more often than Rose, they made nearly the same number of free throws per minute due to Rose’s far superior free throw percentage.

Most importantly, Rose is younger than Iverson was in his third season by one year and four months. It makes more sense to compare Rose’s third season to Iverson’s second campaign, which would cause the gap between the players to widen even further. Finally, Rose stands three inches taller than Iverson and weighs 25 pounds more.

While they have some similarities, Rose holds a decisive edge over Iverson at the same stage of their careers. That becomes clear when taking a look beyond their per game statistics.

Iverson was a great player. But in both performance and from a branding perspective, Rose is on track to soar much higher than Iverson ever did.

Opportunity and Statistics

Most sports statistics – especially the ones that get attention in the mainstream media – are opportunity based. Other metrics filter out opportunity, and they carry tremendous comparative value.

Many still fixate on per game numbers, and they don’t begin to tell the story for players like DeJuan Blair. His 7.8 points per game and 6.4 rebounds per game in 2009-10 look pedestrian. However, Blair posted these numbers in limited opportunities – playing just 18.2 minutes per contest.

Rebounds per 48 minutes is not impacted by how much players see action. Among NBA players with at least 750 minutes played, Blair ranked sixth in rebounds per 48 minutes (16.9). He topped all NBA players in offensive rebounds per 48 minutes (6.43), and remember that he was a 20-year-old rookie!

Even the offensive rebounds per 48 minutes statistic gets impacted by opportunity. Some teams play at a faster pace than others, and some miss more shots. Their players have more opportunities to grab offensive boards. The Spurs played at a slower pace than most teams and had the NBA’s sixth-highest shooting percentage. So these factors hurt Blair, yet he still out-rebounded everybody at the offensive end.

The best metric to show Blair’s rebounding excellence is rebound rate, John Hollinger’s measurement for the percentage of missed shots that a player rebounds when he’s on the court. Blair had a 16.0 offensive rebound rate last season. To put that in perspective, NBA teams grab 26-27 percent of available offensive boards on average. The Golden State Warriors had an offensive rebound rate of 20.9. Blair fell just 4.9 short of that figure, by himself.

While playing his final season at Pittsburgh, Blair put up unbelievable stats in this category. Despite playing in the rugged Big East, his 23.6 offensive rebound rate topped the nation’s next closest player by 5.0. Blair even surpassed the team figure for six Division I colleges.

So how did a player – who can out-rebound an entire team – last until the 37th pick of the 2009 NBA Draft? It’s hard to say. Blair’s 2008-09 rebounds per game figure (12.3) looked good but unspectacular, which may have been a factor. Of course, he played only 27.3 minutes per game on a very slow-paced team. Only adjusting his numbers for opportunity made Blair stand out.

Adjusted Double-Doubles

No matter how well a player performs, playing time has a huge impact on per game statistics. Per game metrics remain the favorite of the mainstream sports media, even though playing time varies widely among those considered “regulars.”

A total of 15 NBA players averaged a double-double in 2009-10. The list includes several current and former All-Stars: Tim Duncan, Carlos Boozer, Chris Bosh, Dwight Howard, Pau Gasol, Steve Nash, Deron Williams, Chris Paul, Andrew Bogut, David Lee, Zach Randolph, Gerald Wallace, Troy Murphy, Kevin Love, and Joakim Noah.

Love’s achievement was most impressive considering he only played 28.6 minutes per game. The other 14 averaged 35.1 minutes per contest. Love became just the second active player to average a double-double in less than 30 minutes per game. Lee, the only other, matched his feat in 2006-07. Among the 31 total players to do this in NBA history, Love was the youngest ever.

It’s nearly impossible to average a double-double in less than regular action. Several more players could have reached this level had they seen as much playing time as the first group. So here is a group of additional players that projected as double-double guys based on points, rebounds, and assists per 35 minutes. This adjustment puts them on equal ground with the earlier group, which saw that much game action on average.

Lamar Odom
Brendan Haywood
Emeka Okafor
Udonis Haslem
Samuel Dalembert
Drew Gooden
Shaquille O'Neal
DeJuan Blair
Serge Ibaka
Kris Humphries
Nazr Mohammed
DeAndre Jordan
Louis Amundson

Expect the younger players on this list – Serge Ibaka, DeAndre Jordan, and DeJuan Blair – to emerge as they receive more burn in the upcoming seasons. All they need is additional PT to post big per game numbers.

MIT Sports Analytics Conference

Here’s a brief recap on last weekend’s MIT Sports Analytics Conference. The conference doubled in size from last year, and again delivered invaluable information for sports agents. This post only covers highlights on basketball topics.

One of the most interesting exchanges dealt with how NBA teams value clutch performance. Rockets GM Daryl Morey said he likes when players have shown strong clutch performance in the past, but he wouldn’t spend millions on a player based on that. Mark Cuban countered by saying he would pay for it, and cited Jason Kidd as one example.

Morey later explained that their research revealed how well Kevin Martin had performed against tough opposing defenses before trading for him at the deadline. Agents may want to emphasize this point for their free agents who excel in this area.

Cuban believes certain NBA teams have an advantage in analytics. Why does he think that? For one, he examines the combinations that some teams place on the court. By comparing that to data that the Mavericks research, he knows which clubs are informed and not, as some of these lineups have poor track records.

Morey also said the Rockets thoroughly research how well a player will perform in their system versus with their current team before acquiring them.

Agents can feel free to contact me for a more detailed rundown on the conference.