Big data and sports analytics are changing the ways many things in sports have traditionally been done. They are allowing for new processes that have the potential to alter the way that organizations conduct their scouting. This is because data science and sports analytics are opening up new data points and avenues of information about draft prospects.

Predictive analytics are beneficial to teams because it gives them even more information that they can take into account when making their draft selection. Smart organizations understand that they should look at each situation from as many angles as possible, especially when making such important decisions as who to draft. And so all these new metrics and data points are being generated, allowing teams and fans to get as much information about a prospect as possible.

Teams utilize film and scouting services such as Synergy Sports Technology to streamline the process of accessing that information. Data science and technology are now also playing an increasing role in the fans perception of draft prospects, as ESPN is one of the many groups that create their own statistical models designed to identify which players are more likely to succeed at the next level, and which players have a higher probability of disappointing. Overall, data science has been trickling into every part of the NBA scouting process, from the front office to the media to the fans and is altering it in new ways.

Data science really started to enlarge its profile in the world of basketball scouting after the introduction of Synergy Sports Technology. It is a service that collects film and statistics and compiles it into an easily accessible and user friendly database. Game film is cut from the NBA, Division I college basketball, the G-League, and leagues all across Europe and Asia. Using this computer program, scouts are able to track the most minute of details and statistics and then immediately access the relevant game film in order for them to see those statistics in action. This means that scouts are easily able to see the efficiency with which a certain player drives to the basket with his left hand, and then see clips of him doing that exact thing.

This service is currently being used by all 30 NBA teams and a large number of Division I college programs, and it has had a tremendous effect on the scouting process of these organizations and teams. Having all of a player’s game clips for each statistic within a few clicks of the mouse makes the scouting process quite a bit easier and also helps to integrate more advanced statistics into the process as they are much easier to make a visual connection with when there is relevant game tape available to see the  numbers in action.

Outside of front offices, there are a myriad of independent groups that are developing their own statistical models to project a prospect’s future in the league. ESPN has developed a model that aims to project a player’s chances of becoming an All-Star, starter, or role-player. They try to project a player’s Statistical Plus-Minus for his 2nd through 5th seasons. Statistical Plus-Minus is a metric that takes all of a player’s box score stats and uses them to make an estimation on a player’s impact on their team’s scoring differential per 100 possessions.

ESPN’s model attempts to project a player’s Statistical Plus Minus in order to predict the quality of player they will be. There are many other groups making similar models, and they all add to the discussion of draft prospects and their potential. This is a noteworthy development because it demonstrates how it is not just the NBA front office scouts that are delving into this field, but the media and the fans as well.

During the night of the NBA draft ESPN would display each drafted players’ standing in this metric. This meant that fans watching at home were having conversations about the analytical side of basketball and how it can give us more information about a draft prospect’s future potential.

Ultimately, data science and sports analytics has been spreading all over the modern sports industry, and the scouting process of NBA teams is one of many key examples of this. Teams are increasingly relying on these methods in order to help their scouting departments gain as much information as possible about individual prospects. But it is not just the organizations themselves that are delving into this field, as media outlets are increasingly integrating advanced metrics and analytics into their draft coverage which in turns influences the fan conversations regarding draft prospects resulting in a bottom line that has data science flowing into every part of the scouting and drafting process in the NBA.

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The Golden State Warriors are on top of the NBA after winning their second championship in three years. They have been in the finals for three consecutive years, set the regular season wins record at 72 wins in the 2015-16 season, and came one game away from going undefeated through the whole playoffs in the last season. The Golden State Warriors have emerged from the darkness of a 40 year title drought to become one of the most promising dynasties in NBA history. Their front office has assembled  an incredible roster through smart planning, excellent talent evaluation, an organizational willingness to weigh all possible  information available, and of course a bit of luck. Golden State Warriors owner Joe Lacob has previously sparked controversy by boasting about the team being “light years ahead“ of the rest of the NBA in terms of structure, planning, and organizational operations. While Lacob’s comments were certainly hyperbolic, they were not entirely baseless as Golden State has been one of the NBA’s earliest adopters of sports analytics and data science.

Analytics, from Santa Cruz with love

The Golden State Warriors’ first foray into attempting to use analytics and other such data science came from a test of their G-League affiliate, the Santa Cruz Warriors. Joe Lacob’s son Kirk Lacob, fresh out of Stanford, was made assistant GM and was put in charge of the G-League team, where he employed a statistics-heavy approach to front office management. The plan here was for Santa Cruz to be a test bed for the team’s more forward-thinking plans, where they dealt with much lower-stakes scenarios. The successes from Santa Cruz would then be evaluated and then employed by the main organization in Oakland.

The Santa Cruz Warriors became a model developmental team under the younger Lacob. In his first two seasons in Santa Cruz, the team made the development league finals each year. In addition to the consistent winning, Santa Cruz consistently pumped out solid NBA contributors such as Kent Bazemore and Dewayne Dedmon. It became clear that the experiment in Santa Cruz was a success, and the younger Lacob was brought up to join the head front office of the Golden State Warriors

The Golden State Warriors front office became one of the early adopters in the field of basketball analytics, partially due to the success of the Santa Cruz affiliate. They began to look into many new types of technologies in order to gain any news bits of information about their games. The more data they could get access to, the more they would be able to learn about their team’s strengths and weaknesses.

For the Golden State Warriors, EPV is the real MVP

The team looks at all sorts of analytics as part of their planning and research process. One of the most often utilized advanced metrics is EPV, or Estimated Possession Value. This metric is generated in a statistical model that absorbs information from an army of cameras trained on every inch of the court. The model tracks the exact location of every player on the court, and gives an Estimated Possession Value number for each moment of play on the court. This means that if a great three point shooter like Klay Thompson were to receive a pass right behind the three point line after coming open off a screen, then his team would have a relatively high EPV in that moment. Alternatively, if a poor shooter like Aaron Gordon were to receive a pass at the top of the key whilst being closely guarded by a great defender like Draymond Green, then his team would have a relatively low EPV in that moment.

Ultimately, this is a tracking model that attempts to evaluate the spatial positioning of every player on the floor through a series of cameras and quantify that information into a metric that states how likely that positioning is to result in points scored. The technology behind EPV came primarily through the release of SportsVU cameras back in 2009. These cameras are able to get 25 frames per second. There are six cameras in the rafters of an NBA arena, strategically positioned to cover the entire floor. The cameras are so advanced and able to quickly track objects that the original technology behind these cameras actually came from a missile tracking system in the Israeli military. Because of these hyper-advanced cameras, teams now have access to a myriad of new data points and metrics, and EPV has been one of the main ones to emerge. Golden State was one of the first 6 teams(Dallas, Houston, San Antonio, Boston, and Oklahoma city being the other 5) to have these advanced cameras installed at their home arena. This is the sort of advanced analytics that the Golden State Warriors embraced early on, and that all NBA teams are utilizing today.

Overall, Golden State has shown an enthusiastic willingness to embrace all new forms of technology and data and utilize it to their benefit. They have been rewarded for the pioneering work they have done in this field, as they are now at the top of the mountain in the NBA, and the methods that they embraced over 6 years ago have now become common-place all around the league.

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Advanced data analytics has been used across the whole sporting spectrum to improve scouting, coaching and fan engagement. Baseball, football, and even ice hockey teams have got in on the act. The NBA themselves are no strangers to data analytics– but the latest tech in basketball talent scouting is a bit of an oddity.

In an attempt to pick up the team’s declining performance, the Milwaukee Bucks, hired facial coding expert Dan Hill last May. Dan’s job profile is to read facial expressions of prospective NBA players to pick out the ones with the right set of emotional attributes.

“We spend quite a bit of time evaluating the players as basketball players and analytically,” said David Morway, Milwaukee’s assistant general manager, explaining the context. “But the difficult piece of the puzzle is the psychological side of it, and not only psychological, character and personality issues, but also team chemistry issues.”

Psychologist Paul Ekman had developed the Facial Action Coding System (FACS) in the 70s which provided guidelines into reading a person’s emotional status through minute movements of 43 facial muscles, movements which reveal “intentions, decisions and actions.” Seven core emotions are identified: happiness, surprise, contempt, disgust, sadness, anger and fear.

As New York Times reports, Hill had spent 10 hours with Milwaukee’s team psychologist, Ramel Smith, watching video of various college prospects and picking apart the psyches of potential picks, prior to the 2014 draft.

Unsurprisingly, some have questioned the method and its efficiency. Martha Farah, a cognitive neuroscientist and director of the Center for Neuroscience & Society at the University of Pennsylvania, has her doubts about how well it works.

“It’s not easy to get good evidence, because a player’s performance and teamwork are complex outcomes, and the teams are not run like clinical trials, with coaches and managers blind to the facial coding findings and so forth,” she told NYTimes.

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(Image credit: V’ron, via Flickr)

Second Spectrum, a sports analytics startup has developed a software that enhances audience viewership through data visualisations and live-statistics during the game, in real time.

Garnering support from former Microsoft Chair and New Clippers owner Steve Ballmer, the Second Spectrum’s proprietary software system was debuted at Staples Center for the Los Angeles Clippers’ opening game in the new NBA season that began last week.

“We have this product called DataFX that combines storytelling, video, advanced stats and special effects, all together to tell sort of the hidden side of what is going on in the game that you might not see,” enunciates Rajiv Maheswaran, co-founder and CEO of Second Spectrum.

Found in 2013, the Los Angeles-based outfit’s software provides Clippers and six other NBA teams with advanced statistics and also allows fans to “take control of the Jumbotron in real time,” Maheswaran told NPR. Using smart devices, fans can choose to see video clips of their liking on the big screen, now aptly dubbed Clippertron, with the person’s name showing up as well.

“It’s not just going to be highlights,” Maheswaran said. “It’s highlights with a lot of effects but also telling the story with numbers you can’t get anywhere else. Nobody else on the planet is going to have them.”

An optimistic Maheswaran believes that the show at the Staples Center is only an example of things to come. “There’s a lot of ways to slice and dice and interact with data that we haven’t started to explore yet,” he noted.

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(Image source: Second Spectrum)