As Performance Data Becomes More Complex, STATS Finds Ways to Streamline Analysis

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The volume of sports data available to teams and leagues is expanding exponentially. It’s causing sports to move faster and competition to become even more intense. It is increasingly difficult to capture all of the relevant data points available and distill the complex information contained in those millions of data points per season into a series of simple representations that can be quickly absorbed, tailored and shared to enhance the teams’ performance and win more games.

STATS’ vision is to collect all of the world’s sports data and make it simple, meaningful, fast and intuitive. The aim is to bring new levels of context to sport through the application of cutting edge technologies – such as computer vision, machine learning and AI – to help teams game plan, build their teams, and maximize athlete training programs to find their winning edge.

Brentford Use Data and Analytics with Hopes of Premier League Promotion

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In the three seasons since Brentford climbed from England’s League One, 23 different clubs have finished in the top half of the Championship. As one of three sides along with Derby County and Cardiff City to finish in the top 12 in each of those campaigns, the Bees don’t seem far from reaching the top rung of English football’s ladder.

Behind manager Dean Smith, the Bees are looking for ways to differentiate themselves to reach the Premier League for the first time in club history. Smith explains here how his staff focuses on two key areas when preparing for an opponent: opportunities and threats.

Player Tracking and Deep Learning Innovations Lead to Greater Interactions with Data

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Fans regularly consume STATS’ data without knowing the original source of the information, and that isn’t necessarily changing as the company explores future applications of richer data. What is different in 2017 from 1987, 1997 or even 2007 is STATS’ specialization from often drawing the line at providing sports information to more properly contextualizing it for clients.

One of the leaders making that happen at STATS emerged from behind the scenes to speak with Sirius XM Wharton Moneyball hosts Adi Wyner and Shane Jensen earlier this month. Patrick Lucey, STATS Director of Data Science, reflected on five years of STATS SportVU tracking data collection and provided insight on the answers now coming from growing sample sizes and industry advances.

STATS began tracking NBA games with its optical system SportVU half a decade ago, which happened to coincide with what Lucey marked as a particularly interesting time in sports science.

“Something happened in 2012. Deep learning came along,” said Lucey, co-author of the 2016 MIT Sloan Sports Analytics Conference first-place research paper on patterns of player movement and ball striking in tennis.

“It’s like a perfect storm. I like to think of it as a three-legged stool. First of all, for deep learning to work, you need three things. The first thing is you need a lot of data. Luckily at STATS, we have that. The second thing is you need the computational power. … The third thing is having the people to actually know how to work or set up the network.”

For nearly two years, Lucey has sat atop that stool at STATS and helped expand player tracking into additional sports with an emphasis on the global game of football. Plenty of his current work, including his 2017 MIT Sloan Conference runner-up paper on shooting styles in basketball, has involved finding the proper ways to ask and answer the what-if questions that weren’t confrontable in STATS’ earlier years.

“The big thing – and this is what we can do really well – we can contextualize the data,” Lucey said. “…You can ask us specific questions. You can say, ‘Well, what’s the likelihood of this player making that shot? Or, what happens if I switch that player with another player?’

“So, we can really do fine-grain simulations and ask those what-if questions. … We have the box score or we have these players’ stats, but (I think the next stage in analytics) is to simulate these kinds of specific plays and see what a different player will do in these situations. In a given situation, we can model that context and we can give more precise answers because we understand the data in those situations.”

The particulars of body pose have become one of his key interests. Specifically, advances in player tracking – and the potential for more accurate predictive analysis – lies in an increased emphasis on measurements that can go beyond using a basic center of mass to establish the XY coordinates in optical tracking.

“Once upon a time, we could capture body pose, but we had to do that in a lab setting,” Lucey said. “… Now we can actually do it in the wild.”

Lucey’s team is constantly honing in on the next big thing in its field, and his view for how performance will be evaluated more closely in the future might surprise some. It’s not necessarily about creating fresh analytical metrics. It’s about the relationship between people and technology.

“I don’t actually think new metrics is the way to go,” Lucey said. “I don’t think that’s the future. I think it’s a symbiosis between a human and a computer. So can we develop new technology to help a domain expert do their job better. I think that’s really the next step in sports analytics. Just enabling, creating this kind of technology just to help coaches or analysts or people at home to be able to ask these what-if questions. I don’t think we’re that far off.”

Tough Shots No Problem for Cavs’ Smith in NBA Finals

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Irving, Durant Also Stand Out in STATS SportVU’s Tough Shot Score Metric

There are many ways to measure the greatness of players like LeBron James, Kevin Durant and Kyrie Irving, but perhaps the simplest involves no advanced stat at all.

They make it look easy. Durant gliding down the left wing and stopping on a dime for a pull-up 3. James darting into the lane and spinning past his defender for a lay-up in one silky smooth motion. Irving leaving a would-be road block in his dust after a series of crossovers and using the perfect amount of English to will the ball in off the backboard.

It’s not.

STATS has created a metric called Tough Shot Score with the use of its revolutionary STATS SportVU cameras that measure how difficult a given shot is based on a variety of factors: the position of the defender, where the shooter is on the floor and whether he’s moving or stationary. The score is normalized from 0-100, with 100 being the most difficult shot possible. Here’s a little of what we found out about just how tough some of the NBA Finals’ biggest stars had it on basketball’s grandest stage.

 

Watch J.R. Smith play for any five-minute stretch of his career and it’s obvious that he doesn’t mind taking tough shots. It’s almost like he prefers them, often dribbling into what seems to be a more difficult, suddenly contested shot than what he had when he caught the pass.

Of the eight top scorers in the Finals, Smith’s regular-season Tough Shot Score (0.61) was easily the highest. So it shouldn’t be surprising that among the 11 players in the Finals with 20 field-goal attempts, Smith’s TSS (0.62) was the only one above 0.58.

Player Total FGAs Tough Shot Score
Smith (CLE) 36 0.62
K. Thompson (GS) 70 0.58
Curry (GS) 87 0.57
Irving (CLE) 123 0.54
Love (CLE) 67 0.54
Durant (GS) 106 0.54
James (CLE) 117 0.50
Green (GS) 55 0.50
Iguodala (GS) 34 0.49
Livingston (GS) 28 0.47
T. Thompson (CLE) 22 0.44

 

Not that the level of difficulty seemed to bother him. After going scoreless from 10:26 of the first quarter of Game 1 until Game 3, Smith was unconscious in the series’ final three games, going 17 of 27 from 3-point range. That includes going 7 for 13 when his defender was contesting within 0-2 feet (very tight) or 2-4 feet (tight).

There’s one player in the series who took more tightly contested 3s than Smith, and he happened to be the one who wound up raising the Finals MVP trophy.

Durant took 312 3s during the regular season, less than a third of which were tightly contested. He hit just 31.4 percent of those, a big drop from the 40.3 percent he hit when open (4-6 feet) or wide open (6-plus feet).

In the Finals? Durant was masterful in transition and was a huge factor defensively, but there was one major reason he wound up sharing a handshake with MVP namesake Bill Russell at the end of Game 5. Of the 38 3s Durant took against the Cavs, 24 of those (63.2 percent) were tightly contested. He made 13 of them, including the Game 3 dagger over James that gave Golden State a lead it would never relinquish. It stands out as the series’ signature moment. All that added up to was a 0.65 TSS from 3-point range, which was actually a shade under his regular-season TSS from beyond the arc (0.66).

Irving had more than a few eye-popping performances in the series, going 7 of 12 from 3 in the Cavs’ lone win. But it was what he did around the basket – particularly in Cleveland’s Game 3 loss – that really stood out. Irving went 14 of 28 on very tightly contested 2s in the series, giving him 11 more attempts with a defender draped all over him than James and two more than the two most heavily guarded Warriors (Durant, Draymond Green) combined.

Only Eric Bledsoe and the Splash Brothers themselves shot better than 50 percent on 2s when tightly contested during the regular season, so for Irving to hit that mark in the Finals while wearing Klay Thompson like a compression shirt is quite a feat. Yet his TSS from inside the arc was higher during the season (0.51) than in the Finals (0.49), so Irving’s Finals’ circus act wasn’t really much different than what he’s been doing since October.

Brett Huston is a Senior Editor at STATS LLC. Contact him at bhuston@stats.com or on Twitter at @BHuston_STATS.

Sports Content Leads to Increased Website Traffic

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The best time for digital media companies to capitalize on sports content unsurprisingly coincides with popular athletic events, and spikes in traffic grow more valuable each year as digital advertising grabs dollars from the traditional media working to air coverage of those competitions.

STATS Hosted clients are among the beneficiaries of this effect on two-fold levels.

Consider March Madness. The days of calling in sick on the first Thursday of the tournament might be a thing of the past as digital and mobile connectivity send consumers real-time scores and highlights from their office chairs. Analytics comparing the day preceding the tournament to the tournament’s first Thursday show collective pageview growth of 91.7 percent for STATS Hosted clients.

It only got better as people traded the swivel chair for the couch. Data comparing the day preceding the tournament and the tournament’s first Sunday show an increase of 103.5 percent for the same client pool.

Spikes for one North America-based client saw shifts comparing Wednesday to Sunday from 59,529 to 282,264 views of Hosted content – or 374.2 percent.

The frenzy wasn’t limited to sites of that size that depend on a national or continental audience. An East Coast regional broadcaster saw traffic growth of 156 percent on the same dates.

Another spike came soon after as the madness quieted and the national pastime uncovered its infields. The end of this year’s tournament coincided with MLB’s first full slate of games on April 3. Hosted clients saw an increase of 89.1 percent from March 27 – the week before MLB’s Opening Day when clubs were still packing for the spring training exodus.

As for how this translates to earnings, the dollar values associated with such content are only increasing with projected digital ad spending becoming a more substantial prize in coming years.

In the second half of 2016, eMarketer reported U.S. digital ad spending would surpass television spending for the first time. Digital ads grabbed 36.7 percent of market, and there’s no going back. Digital spending reached $72 billion in 2016, and projections over the next four years indicate that reaching $83 billion in 2017 and $129.2 by 2021 – or roughly half of all U.S. advertising spending.

That means another substantial medium is losing out. Television’s overall share is projected to decline from 35.2 percent to 30.8 in that four-year period. It won’t be long before mobile ad spending makes television settle for bronze, which gives content providers additional opportunity.

The customizable nature of personal devices is at the forefront of future optimization steps from content providers. eMarketer projects mobile will overtake TV by 2019, but mobile as a subset is already accounting for 70 percent of all digital spending. With evolving tools such as real-time widgets and personalized sports content leading the way to easily adaptable digital products – both for media outlets and their consumers – the ways in which to engage and provide consistently relevant content on key competition days should only grow along with the shifting market share.

Believe Anything By Impactful Players? Look At BABIP Before Thinking PEDs

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When a player is performing well above expectations based on past results late in his career, one question still sadly comes to some baseball fans’ minds: Will someone please test that man for performance-enhancing drugs?

That was certainly the case after Eric Thames lit up the majors upon his return from a three-year stint in Korea in which he had a combined .349 batting average and hit 41 home runs per season. The first baseman had only batted .250 with a total of 21 home runs over 181 games with the Blue Jays and Mariners from 2011-12. But the steroid speculation ran rampant after Thames seemed to come out of nowhere (well, really Changwon) to put up a .333 average with 13 homers in his first 32 games with Milwaukee this season.

Apparently the league office was skeptical as well, as according to Yahoo Sports, Thames was tested immediately after a five-game homer streak and a four-gamer in April. The second MLB drug test during that stretch was what prompted Thames’ defiant “I have lots of blood and urine” response. He was reportedly tested for the fifth time after snapping a 15-game homerless streak with a first-inning shot off Mets right-hander Jacob deGrom on May 31, leaving Thames to wonder if MLB’s random drug testing is actually that at all.

That brings us to first baseman Ryan Zimmerman, who is hardly an unknown after spending the past 12 years as a staple in the Nationals’ infield. Zimmerman appeared to be in the twilight of his career and possibly even headed out of Washington in 2016 after posting a career-worst -1.5 BatWAR (batting wins above replacement), which measures a player’s contributions to his team at the plate. That means he was actually costing the Nationals wins when he was in the lineup, the third straight year that number had dropped.

The veteran, however, has experienced an eye-opening rebirth at age 32. Through June 7, he owns a 2.4 BatWAR, has a major league-best .362 batting average and is tied for the NL lead in home runs (17) after hitting a total of 36 over his previous three seasons. Zimmerman also ranks second in MLB with a .459 weighted on-base average, which combines all the different aspects of hitting into one metric and weighs each of them in proportion to their actual run value. For good measure, he’s third with a career-high 185.2 OPS+, which adjusts for league and park factors.
BABIP-Baseball-Post_Image3-2

It’s important to note that, by all accounts, Zimmerman hasn’t done much to change his approach this season, which brings us back to the question raised at the start. Oddly enough, Zimmerman was cleared of any sinister activity by Major League Baseball in August, months after a pharmaceutical dealer named Charlie Sly claimed in an Al Jazeera America documentary that Zimmerman used PEDs.

We’d like to believe such occurrences have nothing to do with drugs, but rather the variety of factors that can contribute to any player’s surprising stretch. Batting average on balls in play can provide an indication of how much a player is performing above the norm. Typically, anything north of a .300 BABIP is considered above average, though defensive positioning, luck and how hard a ball is hit can affect that number.
BABIP-Baseball-Post_Image1

Zimmerman, for example, has a .392 BABIP that ranks sixth in the majors and gives us an area in which to dig deeper. He’s also sixth in the majors in line-drive percentage (30.9) and 18th in average exit velocity (92.9), according to MLB.com, so he is hitting the ball hard. However, he’s obviously had some luck since he has never finished a full season with a BABIP greater than .334. Zimmerman is expected to be among those who will come back to Earth as his BABIP number almost certainly figures to dip over the rest of the season.

The BABIP leaderboard features many young players having breakout seasons. Minnesota’s Miguel Sano isn’t likely to break the 122-year BABIP record of .443, which was set by Jesse Burkett of Cleveland, and is due some regression after finishing with .396 and .329 marks in his first two seasons. However, he does have a better chance than most to keep a high BABIP because of his 98.8 average exit velocity – tops in all of baseball. Similarly, Aaron Judge of the Yankees isn’t expected to maintain his BABIP but may be able to avoid a severe drop as he ranks second in the bigs with a 96.3 average exit velocity that includes the two hardest-hit balls (119.4, 119 mph) so far this season.
BABIP-Baseball-Post_Image2.jpg
(MLB.com)

Avisail Garcia of the White Sox is an obvious candidate to fall back as he ranked fourth in the majors with a .392 BABIP. Garcia may have been on his last opportunity in Chicago after posting a .311 BABIP while hitting a combined .250 with 32 home runs over his previous three seasons. He seems to be using an even more aggressive approach than usual as he’s swung on the first pitch an MLB-high 47.5 percent of the time and has missed on just 28.8 percent of his swings overall. Both marks are his best numbers since playing in just 23 games in his rookie 2012 season as a highly regarded prospect with the Tigers.

One might notice that the aforementioned Thames isn’t on the BABIP leaderboard. In fact, the Brewers slugger only has a .303 BABIP that’s right around the typical league average. Because of this, he’s more likely to stay on his current production path than most of the BABIP leaders — no matter how much blood and urine the league office may take from him.

Sports and The Second Screen

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According to eMarketer, in 2014, only 51 percent of respondents used their smartphone at the same time as watching TV. By 2017, that number rose to 74 percent, and if tablets are included in the tally, more than 88 percent of US adults will use a mobile device while watching TV at least once a month this year.

As the trend of second screen multitasking has accelerated, media and advertisers alike have taken notice of the opportunity. Like any consumption shift, research has raised questions around whether the second screen could actually distract from engagement on each device.

On the contrary, research released in November 2016 from Ericsson showed a 25 percent increase in multichannel engagement since 2014, including a specific rise in online discussion and mobile surfing relating to the content being watched. Content format also contributes to engagement levels – live television may inspire more content multitasking than streamed content or time-shifted TV, according to a separate study from TiVo in 2015.

Sporting events represent the apex of unrehearsed, live television, and academic research arising from University of Texas supports the hypothesis that second screen use particularly enhances engagement for sports programming. The study confirmed prior research on the general influence of engagement across technology mediums, with fresh evidence of added engagement rather than distraction when it comes to sports. The low degree of overlap between capabilities of the second screen and the first screen (TV) means the two media’s diverse functions complement each other and coexist during the viewing experience – not compete for attention.

The rise of second screens does not pose a threat to first screen media – in fact, it’s an opportunity to pioneer complementary content and campaigns.”

The second screen phenomenon is probably not sport specific, either – the University of Texas study could not find a significant relationship between the type of sport watched and the level of second screen activities. Instead, user experience was a bigger factor in multi-channel engagement. If new devices and applications are difficult to use or don’t synchronize properly with the live event, content providers will not be able to maintain and grow their audiences.

At STATS, we’re already helping media, teams and leagues achieve amazing user experiences, whether in traditional media, through search engines, with voice-activated assistants or via social networks like what we’re doing with Snapchat LiveScore geofilters. But we’re also looking ahead to the next era of personalization. We are gearing up with deep learning and data science to prepare for the next frontier of fan engagement, whether that means creating interaction between personal devices and stadium signage, customized in-game advertising or delivering next-generation statistics to fans on their second – and soon, maybe even third and fourth – screens .

 

2017 NBA Finals Preview

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The top of any list of great sequels in cinema could easily double as a list of some of the finest – and most financially successful – movies ever made. The Empire Strikes Back, The Godfather: Part II, The Dark Knight, Terminator II, Aliens – we could go on.

That’s typically where the creative juices stop flowing.

Sure, there are some noteworthy third acts. The Return of the King is the best Lord of the Rings movie, though that’s more properly viewed as one colossal installment instead of three smaller ones. Indiana Jones and the Last Crusade both made up for the weirdly terrifying Temple of Doom and was popular enough for Harrison Ford to keep playing the character as a senior citizen. Goldfinger was arguably the best James Bond movie.

There haven’t been many third acts in the sports world, which is just one small reason why Cavs-Warriors: Part III should be so compelling. The Lakers and Celtics have met in 12 Finals, but never three in a row. It’s a first for the NBA and just the fourth such threequel in American professional sports history, the likes of which haven’t been seen since the Red Wings and Canadiens battled for three straight Stanley Cups in the 50s.

We’ve already detailed the lack of big-screen triumphs when it comes to third acts, but the success of screens could have everything to do with a Finals that’s rightly drawing as much hype as anything since the days of Jordan, Magic and Bird. Let’s take a look at what the Cavs need to do to repeat and what the Warriors can do to make these Finals more Rise of the Machines after last year’s epic Judgment Day.


When you have 30 percent of the All-Stars from a few months ago in one Finals series, it’s easy to get excited about matchups. Will Steph Curry or Klay Thompson guard Kyrie Irving? Does LeBron have no choice but to spend most of his time checking Kevin Durant? We know Draymond can cause issues for Kevin Love, but can Love be matched up with him on the other end?

Those seven will all find one another at some point, but the winner of this rubber match figures to be the team that consistently creates, and then takes advantage of, the most opportune mismatches.

That the Warriors move the ball and move away from the ball better than any team in the league is no great secret. It’s what almost every team in the league dreams of emulating and one day building themselves. Setting screens is still a major part of an offense that hums like a Ferrari when it’s at its peak, but ball screens are a different story. Golden State set 3,324 of those in 2016-17, per STATS SportVU, its third straight season bringing up the NBA rear in the category. Orlando was 29th, yet the Magic set more than 4,000.

There’s less movement in Cleveland’s offense because it’s less necessary. Possessions can come to a screeching halt in the final 10 seconds of the shot clock and Irving and James can save the day as few individual players can. Irving was the best isolation player in the league this season at 1.12 points per ISO, and he’s been even better in the playoffs. James can’t blow by defenders 1-on-1 like he used to, but his 42 percent success rate from 3 in the postseason adds a more complicated wrinkle for opponents than Batman suddenly wielding an assault rifle would for Gotham miscreants.

The Cavs relied on ball screens to generate offense less this season than they had in the past two, funneling through around 57 per game instead of the 65 or so they’d used in James’ first two seasons back home. Whatever way you slice it – and given the overall levels of talent and execution, this shouldn’t be a surprise – both Cleveland and Golden State get a lot out of their screens. Individually, the Warriors were third in the regular season in points per play (a screen that results in a field-goal attempt, foul or turnover by either the ballhandler or screener) at 0.934; the Cavs were fifth (0.925). As far as team points per possession – this adds in the other three offensive players on the floor as potential factors post-screen – Golden State was fourth (1.12), a tick ahead of Cleveland (1.11).

But those numbers take into account Derrick Williams setting a pick for Kay Felder on a cold February night in Minnesota or James Michael McAdoo trying to free up Patrick McCaw on a November back-to-back in Milwaukee. Let’s eliminate some of the noise and concentrate on what both teams should be focusing on – and what they must work to avoid at all costs.

Golden State DO: Get Curry/Draymond rolling

There was no Love in the 2015 Finals and there was no Irving for the final five games, and while those two are a generally dubious defending combination on ball screens, the Curry/Green combo likely couldn’t have done much better if they were both on the floor. Those six games featured 85 Green screens for Curry, which resulted in the Warriors eviscerating the Cavs defense for an average of 1.26 points.

Fast forward to 2016 and it turns ugly for Golden State. Seven games, a total of 39 Curry/Green ball screens and just 0.78 team points per action.

Green is fronting for Curry 6.7 times per game in these playoffs with excellent results: 1.30 team PPP. If that number stays in that vicinity – like it did two years ago – start sizing up the Warriors for their rings, and perhaps 16-0.

Cleveland DO: Target Curry when he’s guarding the screener

Irving has been known to struggle when he’s checking the ballhandler in the pick and roll, often never finding his original man or the roller and easily providing the opposition with a 2-on-1 toward the hoop. But that Irving/Love combo we discussed a few paragraphs ago? They actually defended quite well when put on an island in the 2016 Finals. There were 19 ballhandler/screener combos that defended at least 10 screens last June, and Irving/Love was by far the MOST effective despite getting torched overall in the postseason (1.31 PPP). Irving fared pretty well in the Finals when paired with Tristan Thompson as well.

Ballhandler Screener Screens Defended Team PPP
Irving Love 39 0.59
K. Thompson Green 12 0.73
Iguodala Livingston 14 0.77
Livingston Green 11 0.78
Irving T. Thompson 41 0.85
Curry Bogut 18 1.00

As for Curry, Cleveland preferred to have whomever he was guarding set the pick for the ballhandler. With Curry already banged-up to some degree in the Finals, the Cavs were physical while guarding him and made him work overtime at the other end. Curry was involved in 88 screens as the screener, nearly 50 more than the Warriors made Irving take on. A look at the difference in how both point guards were attacked in the pick and roll in last year’s sequel:

Player Screens starting on ballhandler Team PPP Screens starting on screener Team PPP
Irving 118 0.805 33 1.06
Curry 68 1.096 82 1.07

On Christmas Day in Cleveland, the Cavs ran Curry through nine more with him initially on the screener, scoring 12 points. Klay Thompson was the targeted on-ball defender – often on Irving – with Cleveland putting him through 28 screens and scoring 40 points. Overall, the Cavs celebrated their comeback win at The Q with 75 total points (1.19 team PPP) as the result of screens – 51 more than Golden State (0.71).

Cleveland DON’T: Let Iman Shumpert get screened into submission

The Warriors’ holiday in Northeast Ohio may have been dampened, but they took out seven months’ worth of frustration on the Cavs three weeks later in Oakland. Golden State used 46 ball screens in this one and particularly attacked Iman Shumpert on the ballhandler, often when he was checking Curry. Ten screens of Shumpert led to 22 Warriors points, further lending credence to this stat: In the 128 minutes Shumpert was on the floor in the 2016 Finals, the Cavs were outscored by 13.4 points per 100 possessions. In the 208 he sat, Cleveland enjoyed a plus-9.1 edge.

Golden State could drive Shumpert off the floor entirely in these Finals. In theory, he’s an ideal guy to stick on Curry or Thompson to hide Irving for a bit, but in reality he tends to get lost when he’s asked to do more than guard someone 1-on-1. Richard Jefferson played a key role against the Warriors last season and seems more suited to have a chance of defending Durant than Shumpert. With Kyle Korver a potentially vital offensive piece to stretch the floor, Shumpert may wind up a DNP-CD (can’t defend).

Golden State DON’T: Ignore Kevin Durant as a ballhandler

Let’s get to the elephant in the room of why many expect this series to be short. The Warriors added one of the three best players in basketball at the expense of Harrison Barnes, who went 5 for 32 from the field once Golden State went up 3-1 last year.

As we’ve covered, the Warriors aren’t going to rely nearly as much on the ball screen as the Cavs. But when things start to break down – particularly in the fourth quarter – there will be instances when it could be a necessity.

Logic tends to dictate that should a critical Golden State possession become bogged down, Durant will ISO, Curry will launch a 3 or, perhaps, Durant will come to the ball and screen for Curry. But there’s another option.

Durant has an awfully good handle himself. Curry screening for him should allow KD a moment to turn the corner and pop away from the secondary defender for an open 3. And if Curry can’t get free, Durant proved during the regular season that he was fantastic finishing in these situations. Of the 144 players who participated in 300 screens as the ballhandler, only Wilson Chandler and Paul George scored more points per individual screen than Durant (0.48).

It’s been even more absurd during the playoffs. Durant’s 0.66 average is a full tenth of a point better than any of the other 46 players who have participated in at least 50 screens. From a team perspective, the Warriors’ 1.36 PPP off screens with Durant as the ballhandler is second – and the chart below shows how infrequently that’s used compared to some of the other big names at the top.

Ballhandler Screens Team PPP
Stephenson (IND) 56 1.38
Durant (GS) 77 1.36
James (CLE) 271 1.35
Leonard (SA) 222 1.28
Curry (GS) 256 1.25

 

They’ve only broken the Curry-screening-for-Durant combo out 13 times during the playoffs but it’s led to 21 Warriors points, and frankly, there was no need to even do it that much. It’s a wrinkle that Steve Kerr and Mike Brown have largely been saving to unleash only when they need it, and that alone should terrify the Cavs.

Cleveland and Golden State DO: Get the big men involved

There have been 72 two-man combos that have run at least 30 screens in the playoffs, and the top two involve, as you might expect, James and Curry. But the other half of those equations probably isn’t who you’d expect. JaVale McGee has teamed up with Curry for 52 screens that have resulted in 1.47 Warriors PPP, tied with James and Tristan Thompson for the most effective in the league this postseason.

The James and Thompson combo has been a special kind of deadly on their 112 screens. James has hit 7 of 14 3s directly after Thompson frees him up, and the duo is 31 of 53 (58.5 percent) overall immediately after Thompson screens for James. Thompson is one of the league’s best at rolling off a screen and flushing an alley-oop from James or Irving, and he and James went for an impressive 1.14 PPP in last season’s Finals as well.


There you have it. There’s no shortage of storylines in the most star-studded Finals since Lakers-Celtics was in its mid-80s heyday. Durant’s chasing his first title. LeBron is chasing MJ’s legacy. Curry and Green are seeking Finals redemption. Klay Thompson wants to prove his subpar playoffs so far have been a fluke. Love wants to show that he can play – and play effectively – against the Warriors.

Golden State knows what’s coming. It’s up to the Warriors to keep Cleveland from catching them in bad ball screen combos while picking and choosing their own spots to use them in an offense that rarely does.

In a third act worthy of the big screen, we’re about to find out how big the screen can be.