Dissecting the Power of STATS TVL Data


Advanced analytics in baseball have come a long way since STATS was founded almost 37 years ago. Advanced metrics derived from complicated formulas have changed how teams and media at all levels analyze the game, and STATS’ advanced analytics team has made powerful contributions to that movement.

One of the tools at the forefront of this movement is STATS TVL. STATS TVL tracks pitch type (T), velocity (V) and location (L) to better explore pitchers’ efficiency and hitters’ approach at the plate. Analysis has gradually drifted from basic, easily calculated numbers like ERA, batting average, home runs and RBIs. And despite teams’ most recent foray into deep data for performance improvement and conditioning strategy, this evolution has been largely influenced by fans and media.

Baseball consumers crave the behind-the-score story, wanting to know the how and why that support those basic statistics. Media groups are not only looking to enrich their content, but they also vote for player awards. The outcomes of these awards are almost entirely determined by unique differentiators that are only detectable through advanced analytics. In that sense, every single pitch thrown either tells its own story or contributes to a greater narrative. STATS TVL not only provides in-depth and unique pitch-by-pitch data, but that data supports predictive element that allows media, fans and teams to look into the future of a player’s career.

Take, for example, this article from STATS following the Chicago Cubs signing Yu Darvish, which broke down Darvish’s numbers against left-handers last season by pitch type and usage. The NL Central is loaded with quality left-handed hitters, and Darvish’s second-half performance versus lefties was quite average. Using that data, combined with the TVL data showing those NL Central sluggers fared against the pitches Darvish throws most, STATS arrived at conclusions regarding how Darvish should approach particular hitters – and which pitches hitters should wait to see.

STATS TVL also powers STATS Video Solution (SVS), which allows teams, players and media to easily search video of any pitch thrown during an entire season with filters for particular pitcher-hitter matchups. By combining these products, STATS used TVL data and SVS video to help us understand how AL East aces should approach a revamped New York Yankees lineup that now features Giancarlo Stanton and Aaron Judge in the newest version of the Bash Brothers. Previous matchups were analyzed through pitch type and location to give a sense of what was successful for both the hitter and pitcher. One conclusion drawn from this level of analysis determined Stanton didn’t hit very well against sliders from right-handers. With Tampa Bay’s Chris Archer thrives on the slider and 19 regular season divisional match-ups against Tampa Bay in 2018, there’s a story building that fans would love to get their hands on.

But one story that got an extreme amount of attention this past offseason was MLB teams’ pursuit of young Japanese two-way star Shohei Ohtani, who eventually signed with the Los Angeles Angels. With STATS’ 600-league coverage span, TVL data was collected from the Nippon Professional Baseball league in Japan, allowing STATS to dive into Ohtani’s pitching performance as well as his approach at the plate. From the mound, which pitches did Ohtani throw the most and how effective were they? What percentage did hitters swing and miss on each pitch? How many of each pitch ended up outside the strike zone? From the plate, STATS TVL data showed Ohtani sat on fastballs and crushed them to the tune of a .353 average throughout his Japanese career. But when he faced a splitter?  A meager sub-Mendoza .191. SVS video from his at-bats showed how Ohtani turned on an inside heater, but rolled over on a splitter. The hype around Ohtani paired with the lack of domestic historical data begs for this level of analysis. What will we see when this rumored phenom take to the field for the first time in the MLB? The fans demand prediction, and TVL delivers just that.

So whether you’re looking to carefully examine the impacts of a divisional shift, the potential of a league new-comer, STATS TVL delivers the innovative unique data points media groups need to carefully and accurately analyze baseball in the way the fans crave.

Analyzing the NCAA Tournament’s ACC Powers Using STATS SportVU


Questions arise annually for the NCAA Tournament selection committee when the bracket is revealed on Selection Sunday. No one ever is fully happy with the results when bubbles burst, and those who received a bid often wonder about their seed or where they’re headed on opening weekend.

The ACC doesn’t have much to complain about this year, though, tying the conference record set last season with nine teams in the tournament, the second-most ever for any conference. Virginia is the tournament’s No. 1 overall seed, North Carolina and Duke both landed on the No. 2 line, and a couple teams toward the bottom of the league standings snuck in, too.

During the ACC Tournament, STATS had its SportVU player-tracking cameras placed above the Barclays Center court and accumulated data during each game to deliver advanced analytics to the ESPN broadcast and fans watching or following on social media. Now, we’ll go even deeper into that data for the first time.

Below is a breakdown of SportVU data gathered during Virginia, Duke and North Carolina games and how those analytics could help or hurt each team heading into the NCAA Tournament. We’ll also delve into some KenPom.com metrics from the mind of Ken Pomeroy, who receives his statistics from STATS’ industry-leading data feeds to power his proprietary model and deliver the most respected college basketball advanced metrics in the game.

According to KenPom, Virginia has the second-best chance of winning the national championship at 17.6 percent, with Duke third (12.1) and North Carolina sixth (5.7).

Virginia (31-2)

KenPom rating: 1
Seed: No. 1, South Region
First-round opponent: UMBC

If you haven’t heard overwhelming praise for Virginia’s defense by now, you wouldn’t be reading this. The Cavaliers rank No. 1 in KenPom’s adjusted defense rating with an average of 84.4 points allowed per 100 possessions. Virginia is dead last in the nation with an average of 59.1 possessions per 40 minutes, slowing the game down to a snail’s pace and forcing long, closely guarded possessions on the defensive end. Does that mean the Hoos can’t score? Absolutely not.

The Cavaliers are 21st nationally in adjusted offense with an average of 116.5 points per 100 possessions. They balance their attack with only three guys averaging double figures in Kyle Guy (14.1), Devon Hall (12.0) and Ty Jerome (10.5) with a very deliberate offensive scheme.

Just how deliberate? During the Cavaliers’ three ACC Tournament games tracked by SportVU, they threw 0-2 passes on 15 percent of possessions, 3-5 on 41 percent, and 6+ on 44 percent. Virginia averaged 1.00 points per possession with 0-2 passes, 1.04 when throwing 3-5, and 1.31 points with 6+ passes.

For comparison’s sake, during Duke’s two ACC Tournament games, the Blue Devils threw 0-2 passes 45 percent of possessions and 6+ only 16 percent. Virginia is patient when it comes to shot selection, constantly setting screens to free up an open man.

During its three victories to win the ACC Tournament – including a win over the Tar Heels in the title game – Virginia led all teams with an average of 1.28 points per possession when setting a screen. It set 46 screens for Jerome according to STATS SportVU tracking, resulting in an average of 1.43 team points per possession. SportVU also compiles who sets specific screens, and the list below shows Virginia’s top three combinations involved Jerome during the ACC Tournament (click to enlarge).

A No. 1 seed has never lost to a No. 16 seed in the NCAA Tournament, and Virginia’s body of work suggests UMBC doesn’t stand a chance. Some might say UMBC needs to get extremely lucky. It so happens KenPom defines luck in college basketball as “a measure of deviation between a team’s actual winning percentage and what one would expect from its game-by-game efficiencies.”

Which team ranks No. 1 in KenPom’s Luck Rating? UMBC. And that luck seems to be kicking in already. Virginia announced Tuesday that ACC Sixth Man of the Year De’Andre Hunter suffered a broken wrist in the conference tournament and will miss March Madness.

If Virginia can overcome the UMBC luck factor and Hunter’s injury, it’ll still have to survive a bracket featuring No. 2 seed Cincinnati, third-seeded Tennessee and fourth-seeded Arizona, which seems awfully low for a team with a talent like Deandre Ayton.

Duke (26-7)

KenPom rating: 3
Seed: No. 2, Midwest Region
First-round opponent: Iona

The preseason No. 1 team is back to being a national title favorite despite finishing just 2-2 down the stretch. The Blue Devils certainly appear to have the most talent with freshman Marvin Bagley III – who is No. 3 in KenPom’s national player of the year standings – and senior instigator Grayson Allen, along with a supporting cast that features lottery pick Wendell Carter Jr.

Duke is one of only two teams to finish in the top 10 in both KenPom’s adjusted offensive efficiency (third) and defensive efficiency (seventh), with Michigan State – the No. 3 seed in the Midwest – being the other. The Blue Devils can beat any team inside or out given their shooters (Allen, Gary Trent Jr.) and their front line (Bagley, Carter).

STATS SportVU tracked four of Duke’s games this season, with two at the ACC Tournament and one each at Indiana and at Wake Forest. In those games, Bagley and Carter combined for 81 close touches (originated from a pass within 12 feet of the basket), leading to 1.26 team points per possession. Carter’s free-throw rate (free throws made/field goals attempted) was 64.3 percent on close touches and he shot 78.6 percent after a close touch.

The inside domination doesn’t stop there. According to SportVU, Bagley shot 12 of 14 when contested at the rim by two or more defenders, and Carter went 4 of 5 in those same situations. With only a single defender, Bagley was 8 of 14 and Carter 7 of 10. Essentially, if the ball gets inside, forget about it.

And if Allen is on his game from deep, the opposition stands little chance – unless defenders can keep him moving. In Duke’s tracked SportVU games, Allen shot 5 of 15 (33.3 percent) on non catch-and-shoot 3s. When he caught and fired? A red-hot 8 for 13 (61.5 percent).

Allen is at his best when he doesn’t have to create. When taking zero dribbles, Allen shot 11 of 18 overall and 9 of 14 from the 3-point line.

As for Trent? He’d rather be on the move. Trent went 11 of 22 (50.0 percent) from the field when taking at least one dribble in Duke’s four games SportVU tracked. When he didn’t take a single dribble, he went 7 for 23 (30.4 percent) overall and 4 of 17 (23.5 percent) from deep. Have a look at Allen’s and Trent’s numbers from the ACC Tournament (click to enlarge):

Bagley, Carter, Allen and Trent all played well in the ACC Tournament semifinals, but the Blue Devils ran into the Tar Heels, who came away with a 74-69 victory. Now the defending national champions are seeking a repeat.

North Carolina (25-10)

KenPom rating: 7
Seed: No. 2, West Region
First-round opponent: Lipscomb

A 10-loss No. 2 seed that finished sixth in its own conference with a home loss to Wofford on its resume? Crazier things have happened, even though North Carolina is 3-3 in its last six games. But a run to the ACC Tournament title game convinced the committee big things are in store for the Heels.

Theo Pinson, Luke Maye – who is No. 9 in KenPom’s national player of the year standings – and last year’s NCAA Tournament’s Most Outstanding Player Joel Berry II are the nucleus from a title team looking to make another run. And since the Tar Heels ranked 104th in the nation in 3-point percentage, they’ll go as far as their attack-the-hoop game takes them.

In North Carolina’s four ACC Tournament games tracked by SportVU, Pinson scored 16 points on a team-high 17 drives, which are defined as touches that start at least 20 feet from the basket and end within 10 – excluding fast breaks. Those attacks led to 26 team points, more than any other UNC player who drove to the hoop in Brooklyn.

But Berry and Pittsburgh graduate transfer Cameron Johnson had success, too. Have a look below at the team points per drive for each player, according to SportVU (click to enlarge):

All three teams have their strengths, but anything can happen during March Madness. STATS SportVU gave us a deeper look into ACC powers, and the advanced metrics listed above are just a sliver of the data collected during the conference tournament.

Imagine if we could evaluate every college basketball team the same way with SportVU player tracking.

South Side Surge: Yoan Moncada Ready to Break Out for White Sox


Complete teardowns are the new hip thing to do in professional baseball, with the Chicago Cubs and Houston Astros winning the last two World Series after years of rebuilding the farm system through trades and high draft picks.

The Chicago White Sox seem to be one of the next teams in line to break out, with a number of prospects acquired via trade or the draft who are almost ready to contribute on the South Side. Outfielder Eloy Jimenez, acquired last season from the Cubs in the Jose Quintana trade, is the No. 4 overall prospect in baseball according to MLB.com. There is Lucas Giolito, a former No. 1 overall prospect, acquired in the Adam Eaton trade with Washington.

Seven White Sox prospects are littered across MLB.com’s Top-100 ranking this spring, but possibly the most-hyped prospect of all gave up his rookie status last year with the White Sox — Yoan Moncada.

Moncada, acquired from the Boston Red Sox along with No. 10 overall prospect Michael Kopech in the Chris Sale trade, was himself a former No. 1 overall prospect out of Cuba. However, his .231 average and .753 OPS last season leaves much to desire from the young second baseman.

Moncada made his White Sox debut on July 19 last year, and proceeded to slash .105/.261/.263 for the rest of the month. He was better in August, slashing .238/.368/.413 in 18 games, but he was downright good in the final month of the season, slashing .305/.374/.500 over his last 20 games with four home runs and 10 RBI.

His final month upped his season WAR total to 1.9, although he only played in one-third of the White Sox’s games.

What adjustments did Moncada make to his game during the second half of his season? For one, he started by hitting the fastball better, according to STATS TVL data, which tracks pitch type (T), velocity (V) and location (L). He didn’t register a single hit off four-seam fastballs in July, and only one on a two-seamer. He upped that total number to 11 in August, and in September/October, he collected 18 hits off four- and two-seam fastballs.

That success came partly because Moncada was seeing the fastball better later in the season. Moncada swung and missed at 33 percent of four-seamers from righties in July, but improved to 26 percent in August and 28 percent in September. After swinging and missing on 20 percent of two-seamers against righties, he didn’t swing and miss a single time in August or September. And after registering a 20 percent swing-and-miss rate against lefty four-seamers in July, it dropped to 8 percent in August, and he didn’t miss a single one in September.

Here is a clip using STATS Video Solution showing Moncada getting overpowered and swinging through a four-seamer up in the zone in July, followed by a clip of him all over the same pitch in September, both off Kansas City’s Ian Kennedy:

It wasn’t just the swing-and-miss rate that improved for Moncada, though. A 55 percent groundball rate in July turned to 51 percent in August and 41 percent in September. That led to a higher hard-hit rate, which naturally leads to more extra-base hits, a higher slugging percentage, and more production overall.

Moncada had a 32 percent hard-hit rate in July, which is a respectable number (for reference, Francisco Lindor had a 33 percent hard-hit rate last year). But in August it bumped to 37 percent, and in September it moved to 38 percent. Overall, Moncada registered a 37 percent hard-hit rate last year, the same as Houston phenom Carlos Correa.

Obviously, Correa and Moncada are not the same hitter at this point in their careers. Correa hit 84 points better than Moncada last year, although their batting average on balls in play was only 27 points different. That boils down to how much Moncada struck out.

While the league-wide strikeout rate was just over 24 percent in 2017, Moncada struck out in 37 percent of his official at-bats. Just like with his swing-and-miss rate, though, he was trending in the right direction as the season got older. After striking out in 43 percent of his at-bats through the end of August, he lowered that number to 31 percent in September.

The combination of three things – making more contact, hitting the ball harder when he did make contact, and hitting the ball in the air more – led to a .818 OPS in September, which included five home runs and 11 RBI. Not-so-coincidentally, the White Sox had a 15-14 record the final month of the season after heading into September at 52-80.

If Moncada carries that production into his first full season with the White Sox, he’ll cement himself as a cornerstone of the franchise’s rebuild.

How STATS Helps Digital Media Outlets Enhance MLB Coverage


Likening the length of a Major League Baseball season to a marathon wouldn’t nearly do justice to the year-round sport. A six-month regular season, 40+ days of nail-biting playoffs, trade-rumor stacked Winter Meetings, and pitchers and catchers reporting mid-February for a six-week spring training just to do it all over again? Running 26.2 miles over a few hours suddenly feels like a walk in the park (or at least to first base).

Needless to say, the chance to captivate a country by way of America’s pastime is nearly a year-round opportunity chock full of thrilling milestones, record-breaking contracts, and tear-jerking sports magic moments. What’s daunting for digital media outlets, broadcast partners and fantasy sports companies is figuring out how to provide quality and unique coverage during MLB’s seemingly endless, expansive campaign.

MLB plays roughly 1,200 more games per season than any other North American major sport on a nearly daily basis, requiring every outlet to reach their customer base with essentially zero down time. And unless you’re outfitted with a full staff of data collectors, researchers, analysts, and writers, this massive opportunity quickly looks more like an expensive, nearly impossible task.

Enter: STATS. Only the correct data provider can help simplify the delivery of advanced analytics, real-time live updates, historical data, quality research and in-depth fantasy notes to fans of all 30 MLB teams. That’s where STATS’ MLB coverage steps up to the plate.

STATS is MLB’s official data provider and has a full slate of products that captures every moment during and surrounding the 2,430-game regular season before the month-long playoffs, ranging from the most minor of transactions to record-breaking player and team achievements. Whether using STATS PASS’ historical database tracking statistics back to 1876, or accessing unique advanced metrics through TVL data and STATS Video Solution, digital media outlets can fulfill any need necessary to satisfy fans’ MLB cravings.

And for the fans who want their baseball information in real-time? STATS’ data feeds provide not only some of the fastest but also most accurate in-game updates in the industry, which Northwestern University validated through a STATS-commissioned study. By tracking every pitch and producing the correct outcome within seconds, STATS is far and away the industry leader in delivering clients the tools necessary to set themselves apart during the MLB season.

The value of such high-quality, real-time data even extends to fantasy games and the outlets hosting a variety of leagues and contests. Fantasy baseball requires daily attention to player news and updates, injury statuses and performance trends to build the best collection of MLB stars. STATS’ serves digital media companies with daily, automated player notes and headlines through STATS Hosted Solution and up-to-the-minute in-game insights with STATS Widgets. It’s never been easier for clients to present relevant information in such an efficient manner.

That’s especially important for fans who have money on the line in fantasy baseball contests. STATS API produces award-winning Daily Fantasy Sports (DFS) projections available to digital media outlets looking to serve die-hard DFS players. Three times STATS has ranked No. 1 for most accurate baseball projections by FantasyPros and the Fantasy Sports Trade Association (FSTA).

Keeping focused throughout the long MLB season can be challenging and often requires a plethora of support tools to satisfy customers craving baseball data. STATS’ full suite of MLB products lightens the load for digital media companies and gives fans the means necessary to remain informed regardless of their needs.

Have a look at the MLB products STATS offers at www.stats.com/mlb.

STATS’ Advanced Analytics Featured in Sirius XM NFL Radio Interview


STATS’ advanced analytics team is constantly developing new metrics to enhance player evaluation and team performance in college football and the NFL, and those efforts received more national recognition at the NFL Combine.

STATS’ Manager of Advanced Analytics Kyle Cunningham-Rhoads appeared as a featured guest on SiriusXM NFL Radio show Late Hits with hosts Alex Marvez and former college and NFL coach Rick Neuheisel to discuss STATS’ unique advanced metrics and its new product, X-Scout. During the nearly 17-minute interview, Cunningham-Rhoads explained some of the science and research behind a new wave of analytics changing player evaluation at all positions.

“Everyone has access to data, whether it’s the tracking data that comes from the NFL or the third-party data like STATS provides,” Cunningham-Rhoads said during the interview. “The difference we can make is we help teams get the most out of that data through all of these metrics.”

Cunningham-Rhoads and his team have made revolutionary strides in player evaluation, including efficiency metrics for offensive and defensive line and cornerback positions. STATS’ new X-Scout product is a result of game-tracking data – such as pressures allowed, pressures forced and defensive targets, among many others – that powers a model producing an efficiency metric based on a player’s position.

X-Scout will assist NFL teams as they lead up to the draft and player-selection process, while also helping clubs evaluate college players during the season. During the Sirius XM interview, Marvez and Neuheisel asked which cornerback STATS rated the best heading into the 2017 draft, and Cunningham-Rhoads said LSU’s Tre’Davious White, who was the fifth cornerback selected, and 27th overall by Buffalo. White validated that lofty ranking by tying all rookies with 18 passes defended and also intercepting four passes.

“We’re by no means saying, ‘You should pick this player,’” Cunningham-Rhoads said regarding X-Scout. “It’s more like, ‘Hey, here’s a list of guys you should be looking at, and here’s how they might fit into your existing system. X-Scout is not replacing the value of the scout, but rather augmenting their skills, and making it possible to see so much more than basic stats well in advance of the combine.’”

Marvez and Neuheisel also pointed out Las Vegas oddmakers didn’t have much confidence in Philadelphia to win the Super Bowl, listing the Eagles with only 40-1 odds to be crowned champions. However, STATS’ combined roster evaluation metrics ranked Philadelphia as the No. 1 team heading into the 2017 season.

Age is Just Another Complicated Number for Bartolo Colon


Bartolo Colon started to show his age last season. Most major leaguers would when they’re just a couple months shy of turning 45. In fact, most major leaguers no longer call themselves major leaguers at that age.

Colon is an exception, and the wear and tear seems to be taking a toll. He was on the mound for 28 starts last season, and 33 the year before that. He was an All-Star in 2016 at the ripe age of 43 for the New York Mets, but sported a 6.48 ERA in 2017 between Atlanta and Minnesota.

Now, he’s in Texas Rangers camp trying to win a sixth spot in a rotation that has almost completely flipped from a season ago. On Opening Day 2017, the Rangers were slated to have Yu Darvish, Martin Perez, Cole Hamels, A.J. Griffin, and Andrew Cashner fill out the rotation. This season Hamels and Perez are the only holdovers, joined by newcomers Matt Moore, Doug Fister, Mike Minor, and the candidates for the sixth spot – Colon, Jesse Chavez, and Matt Bush, mainly.

If Colon wants to make the big league roster, he needs to prove he can manufacture the production he showed in 2016, and that he hasn’t finally fallen off with age, like 2017 might suggest.

What changed for Colon in 2017? Not much on the surface, according to STATS TVL data. His average velocity was the same, his pitch-mix didn’t fluctuate very much at all, and his strike percentage was roughly the same for all his pitches, along with his swing-and-miss percentage and chase percentage.

One major difference was Colon’s opponent’s batting average on balls in play – in 2016, it was .291, and in 2017 it was .331. That’s a significant bump, and it’s due mostly to guys teeing off on Colon’s two-seamer. In 2016, right-handed hitters slashed .266/.290/.378 off Colon’s two-seamer and lefties slashed .244/.284/.466. In 2017, righties slashed .352/.378/.557 and lefties slashed .349/.397/.627.

Colon threw it for a strike 70 percent of the time in both ’16 and ’17. His swing-and-miss percentage fell from 10 to seven, but that’s not major. The major difference was the fact that Colon missed inside the zone far more often in 2017 in critical counts than he did in 2016.

The two charts below show where Colon gave up hits on 0-1 counts with his two-seam fastball, from the pitcher’s perspective.

The chart on the left shows 2016. Colon gave up hits when he made mistakes in the zone (he almost always wants to paint the outside corner to righties with his two-seamer), but he did a good job minimizing those mistakes. In the chart on the right, 2017, he missed in the zone much more, and paid the price. Here are a couple videos pulled from SVS, the first from 2016 when Colon executed a 0-1 two-seamer to get Addison Russell to ground out, and the second from 2017, when he missed inside the zone and gave up a big fly to Ryan Braun.

He ran into the same mistakes against lefties on 0-2 counts in 2017. In 2016, lefties hit .167 and slugged .250 off 0-2 two-seamers from Colon. In 2017, they hit .429 and slugged .500 against the same offering. During Colon’s 2016 All-Star campaign, he didn’t give up a single hit inside the zone on 0-2 counts. Pitchers typically feel like they can waste a pitch or two in an 0-2 count trying to get hitters to chase, and Colon was no different. However, as you can see from the screengrab below, in 2017 he missed multiple times in the zone, and paid for it.

Colon got in trouble on full counts against righties, as well. In 2016, right-handed hitters hit .185 and slugged .259 against Colon’s two-seamer in 3-2 counts, and in 2017 they hit .389 and slugged .611 off him. Part of that is because Colon gave in to hitters more in 2017, and part of it is because he was up in the zone more this past year.

In 2016 on 3-2 counts when Colon threw two-seamers to right-handed hitters (these may seem like incredibly narrow parameters, but Colon threw a two-seamer 84 percent of the time against righties in a 3-2 count that year), he was in the strike zone 61 percent of the time. He was middle/up in the zone 43 percent of the time. In 2017, he was in the strike zone 71 percent of the time and middle/up in the zone 54 percent of the time.

The solace Colon can take from 2017 is that he found his changeup, and it turned into a good pitch for him after he used it only four percent of the time in 2016. He more than doubled his usage in 2017, and got better results.

In 2016, hitters slashed .367/.412/.600 off Colon’s changeup, but in 2017 slashed .243/.284/.443. And although he doubled his usage of the pitch, his strikeouts from ’16 to ’17 were five-fold.

Colon strikes out Elvis Andrus with a changeup in the following clip from STATS Video Solution. From the way Andrus’ head snaps back towards Colon after he swings and misses, you would think he had no idea Colon throws a changeup.

Colon may be wise to up his changeup usage even more this season to help keep hitters off his two-seamer, or else he may not find himself in the Rangers’ rotation come summer time.

Pick Your Poison: How AL East Aces Should Approach Judge and Stanton


American League East teams not located in the Bronx have a problem. It’s two problems, really, and they both stand at about 6-foot-6 and have over 500 pounds of pure muscle between them.

Aaron Judge and Giancarlo Stanton combined for 111 home runs last year, clearing outfield wall after outfield wall at a historic pace. They played their home games 1,300 miles away from each other, though. This year, they’re sharing a dugout.

That causes a problem for first-year Yankee manager Aaron Boone, though his is a good one. Where do you hit the new-age Bash Bros in the order?

If one follows the other, opposing pitchers won’t want to pitch to either of them. They wouldn’t be able to afford to pitch around both of them either, or they’re putting a guy into scoring position before bat meets ball. This kind of problem is the bad kind once again, and it falls back in the lap of opposing pitchers.

How do you choose who to pitch to, and who to tip-toe around? A lot of that has to do with matchups, of course. Some of it has to do with what you do well as a pitcher compared against what Judge and Stanton do well at the plate. STATS TVL projections – pitch type (T), velocity (V) and location (L) – take all of that into consideration (along with many other factors). We’ll take those projections for the 2018 season, and with an assist from STATS Video Solution we will go through which Bash Bro each of the projected Opening Day starters in the AL East should choose to attack.

Chris Sale, Boston Red Sox

For all the success Judge had last year, Sale owned him. The AL Rookie of the Year was 0 for 12 against Sale with 10 strikeouts.

The Boston ace pumped fastballs to opposing right-handed hitters about 50 percent of the time last year, and that was the case against Judge as well. Judge’s stat line against lefty fastballs was nothing to write home about: .203 AVG/.378 OBP/.469 SLG with five home runs, eight RBIs, and 22 strikeouts.

That’s probably why Sale finished off Judge with a fastball seven times. Watch Sale challenge Judge up in the zone twice before getting him to go down on strikes on July 15 of last year.

The 2018 projections against Sale are more favorable for Judge, though they still aren’t too flattering: .214 AVG/.462 SLG. He isn’t projected to hit higher than .187 against Sale’s four-seamer or slider.

Stanton has never faced Sale, though his numbers last season against lefty fastballs – .356/.465/.763 with six doubles, six home runs, 17 RBIs – make his 2018 projections against Sale much better than Judge’s. Stanton projects to hit .317 and slug .927 off the Red Sox lefty, while clobbering his slider to the tune of a .445 average and 1.675 slugging percentage.

Sale isn’t one to back off any hitter, but he would be wise to be careful with Stanton and attack Judge instead, just like he did last summer.

Chris Archer, Tampa Bay Rays

Archer has thrown against Miami twice in interleague play, so there’s a sample size for both Judge and Stanton against him.

Stanton didn’t figure Archer out in those two starts, going 0 for 6 with two strikeouts and no hard contact to speak of. In both at-bats that ended in a punchout (one in June 2014 and one in April 2015), Archer went slider-heavy. In that two-year span, Stanton hit .194 off righty sliders and slugged .453. Here is Archer getting Stanton on three straight sliders.

Those numbers haven’t gotten any better since. He raised his average to .214 against righty sliders, but his slugging percentage dropped to .373. For that, Stanton’s 2018 projections against Archer don’t project much confidence – .227 AVG/.477 SLG overall, and a .223 average and .412 slugging percentage off the slider.

Judge cracked a double off a hanging slider on the first pitch he ever saw from Archer in April of last year. It wasn’t a forecast of what was to come, however; since then, Judge has gone 0 for 8 with five strikeouts.

Like with Stanton, Archer’s slider has been the catalyst. Here is a video from SVS of Archer getting Judge on three consecutive sliders, just like he did with Stanton.

However, Judge’s 2018 projections against Archer don’t scream doom – .252 AVG/.593 SLG. That has a lot to do with the assumption Judge will eventually get fastballs to hit off Archer, as he’s projected for a .364 average and .953 slugging percentage off that Archer offering.

If Archer wants to steer clear of too much damage against the Yankees, he’s better off testing Stanton than Judge, and with a steady diet of sliders.

Marco Estrada, Toronto Blue Jays

Estrada has seen plenty (in our view and in his, probably) of Stanton and Judge, because of his stint in the National League with the Milwaukee Brewers.

Stanton is 4 for 11 with a double, three home runs, and six strikeouts against Estrada, but that’s a little skewed; Stanton struck out the first four times he faced Estrada. He has figured him out since then, and if you do some subtraction, you see he’s four for his last seven against him with those three home runs and the double.

Estrada is essentially a fastball-changeup pitcher against right-handers, leaning more on his changeup late in at-bats, and he’s more likely to start an at-bat with a curveball than he is to end one with it. That’s what’s gotten him into trouble with Stanton in their most-recent encounters.

Here he peppers him with three straight fastballs, before Stanton puts one over the center field wall in Miami.

Stanton’s 2018 projections against Estrada look similar to the moonshot in that video – .320 AVG/.745 SLG. His individual pitch projections (four-seam: .296 AVG/.678 SLG, changeup: .314 AVG/.779 SLG) don’t give him an avenue to get Stanton out, so he might be better off pitching around the slugger, if it weren’t for one detail – Judge’s projected numbers against Estrada are even better.

In Judge’s short career, he has already collected seven hits in 14 at-bats off Estrada, with two doubles, two home runs, three walks, and five RBI. That’s after starting his career 1 for his first 4 off him.

Six of his seven hits off Estrada have come on a fastball, which is why Judge’s 2018 projections off the Blue Jay righty scream to not throw him a fastball –  .385 AVG/.900 SLG overall and .439 AVG/1.080 SLG off the fastball.

Estrada fell behind in this at-bat against Judge (after, admittedly, a pretty good changeup) and was forced to throw a fastball. It ended up in the seats.

Choosing to pitch to either Stanton or Judge will be like pulling teeth for Estrada. The projections say less damage will be done by Stanton; common sense says tell the outfielders to move back either way.

Kevin Gausman, Baltimore Orioles

Gausman has suffered the same fate as Estrada against Judge, giving up six hits in 12 at-bats, including one double, three home runs, four walks, and five RBI.

The young Orioles righty was 65 percent fastball last year, which is appetizing for Judge, who hit .352 and slugged .819 off right-handed fastballs in 2017. Each of his three home runs off Gausman have been off four-seamers, including the one in the video below, which ended up about 10 rows deep in the center field seats.

However, if Gausman made the decision to go offspeed-heavy against Judge, he might have more luck. He struck Judge out three times with the slider in 2016, though Judge wasn’t the same player during his September call-up that year as he was in 2017. His splitter is his “out” pitch, and it projects well against Judge – .209 AVG/.341 SLG. He struck Judge out with a nasty one in this video in May.

His splitter really projects well against Stanton – .036 AVG/.241 SLG – and should give Gausman some clarity on who to attack between the two 50-home run sluggers. Stanton has struggled with the splitter in his career, hitting just .143 on the offering in 2017 with a 59 percent swing and miss rate. Overall, Stanton projects to hit .209 and slug .511 off Gausman, who he has yet to face in his career.

Each of these pitchers made Opening Day starts last season, except for Sale (when the Red Sox gave the nod to reigning Cy Young winner Rick Porcello instead), and they all could very well take the mound on Opening Day again this season. These are some of the best pitchers the AL East has to offer, and to see what Judge and Stanton have done to them in the past and what they are projected to do against them in 2018 should raise the eyebrows of every member of every pitching staff in the division and beyond.

To make matters worse, they might seem them back-to-back, and if they aren’t careful, they might see them trot around the bases back-to-back.

Yu Darvish Has Much to Prove vs. Lefty-Loaded NL Central


The MLB’s cold-stove offseason upgraded to at least lukewarm Feb. 12 when the Chicago Cubs and top free agent target Yu Darvish closed on a potentially $150 million deal. That could wind up being a bargain for the game’s preeminent strikeout pitcher over the last five seasons when considering the usual cost of quality starting pitching.

The Cubs now can rest easy with their rotation set heading into spring training, as Darvish’s signing officially signals the end of Jake Arrieta’s tenure on the North Side. The basic numbers support the Cubs’ investment that provides them with a solid top end of Darvish, Jon Lester and Jose Quintana in some undetermined order.

But STATS TVL data – tracking pitch type (T), velocity (V) and location (L) – is anything but basic, and there should be some cause for concern with the majority of Darvish’s 2018 starts set to come against NL Central lineups loaded with left-handed hitting options due to the unbalanced schedule. The projected numbers combined with Darvish’s history against lefties might cause some Cubs fans to tone down the optimism a little.

Chicago led the NL with a .285 batting average on balls in play (BABIP) against lefties in 2017, and Lester led all MLB starters striking out 34.1 percent of the left-handers he faced. Darvish, whose 11.04 strikeouts per nine innings is the highest rate of any pitcher since he made his MLB debut in 2012, finished 19th punching out 26.9 percent of lefties he faced between his time with Texas and the Los Angeles Dodgers.

That’s a solid rate and not far below the 27.6 percent of right-handers Darvish fanned. But when left-handers put bat on ball? Not as good. Darvish ranked 140th in MLB with a .328 BABIP against lefties compared to a .241 BABIP vs. right-handers that was the sixth lowest in baseball. Despite left-handers having trouble against his slider, Darvish threw his four-seam fastball at a higher usage rate than any of his other pitches.

The results? Well, have a look at how lefties fared against Darvish in the second half:

Of the seven players with at least nine career hits off Darvish, six either bat left-handed or are switch hitters. The outlier is Mike Trout, whose four homers are tied for the most against Darvish with left-handers Brett Gardner and Brandon Moss.

According to Roster Resource, three of the Cubs’ four NL Central foes project to have at least half their non-pitcher spots in the lineup occupied by left-handed hitters. The Reds project to have the most with six, and Darvish might want to refrain from throwing his four-seam fastball against majority of them. TVL data projects Joey Votto to hit .464 against Darvish’s four-seamer with Billy Hamilton (.443) and Scooter Gennett (.427) not far behind.

The Brewers project to start five lefty hitters, and among current NL players with the most hits off Darvish, Stephen Vogt (seven) and Eric Sogard (five, tied for second) are at the top of the list. Milwaukee added another solid lefty bat in Christian Yelich, who came over from Miami in an offseason trade. Yelich is 2 for 5 with a homer and two walks in his career against Darvish, and most of those at-bats are recent.

Yelich has a .471 projected average against Darvish’s four-seamer, and he took that pitch deep in their first-inning matchup July 26 of last season. Using STATS Video Solution, that specific at-bat is easy to find with just a few clicks.

You’ll note in the graphic above that lefties hit only .161 against Darvish’s slider in the second half last season. Darvish didn’t take any chances with the four-seamer after Yelich’s homer and retired him on a slider in the third.

That slider should be used often against Matt Carpenter, according to TVL data. Carpenter, who is one of three Cardinals lefties in their projected lineup, has never faced Darvish, but is projected to hit just .116 against his slider. Everything else? .401 against the four-seamer, .395 against the curve and .330 when facing a two-seamer.

Josh Bell and Gregory Polanco are the only Pirates lefties guaranteed to be on the major league roster, with Polanco going 0 for 2 in his only previous matchups with Darvish. Bell projects to hit Darvish’s four-seamer at a .418 average, but despite what’s on paper, it doesn’t mean the Cubs made a mistake in bringing Darvish to the NL Central.

There’s plenty of good in Darvish’s arsenal and he’ll make a difference in one of the majors’ best rotations. He’ll just need to be especially careful with pitch selection in the lefty-loaded division.

The NCAA Tournament’s Branding Masterpiece and How You Can Benefit


No one gave it a second thought when “March Madness” appeared prominently at center court for the first time in NCAA Tournament history in 2017. The subtle display represented nearly 80 years of the NCAA building a branding masterpiece collecting billions of dollars in revenue each year.

March Madness has become such a commonly used reference for the three-week event that the literal meaning has changed for brands looking to capitalize on opportunities generated throughout one of the most-watched sports showcases in America. No longer does the tournament’s unofficial nickname only mean to prepare for a month of buzzer-beaters and upsets. Brands and advertisers see a whirlwind of potential new consumers to engage throughout the month.

The target audience is simple: Everyone.

Over 70 million people participated in a bracket challenge during last year’s tournament that had an average daily viewing audience of 9.8 million. With the NFL between seasons, MLB yet to get underway, and the NHL and NBA months away from playoffs, die-hard and casual fans alike flock to the NCAA Tournament, craving sports excitement without distraction. This perfect storm of American sports scheduling makes TV advertising revenue soar, hitting a record $1.24 billion in 2016.

Context? In three short weeks, March Madness outpaced two months of NBA playoffs ($1.03 billion) and fell just short of matching the NFL postseason ($1.31 billion) which contained the most watched television program in US history. A large chunk of those marketing dollars spent on the NBA and NFL – and even MLB and the NHL – often go to current professional athletes to endorse brands. And some of those athletes endorse multiple products. But you won’t find that type of marketing during March Madness. Why?

The answer is not as sports-driven as you’d think. The NCAA’s amateur rules prohibit athletes’ names or likenesses from being used in advertising for products or services. Advertisers during March Madness rely solely on mascots, official NCAA-approved gear worn or displayed, former players, and current and former coaches in order to relate to consumers. So beyond the court, the sweat, the alumni pride, and the passion for winning office bracket pools, how has the NCAA figured out how to create such impactful demand? GREAT BRANDING.”

And the on-court branding is just the start. Going beyond the now ubiquitous March Madness tag, the NCAA has created subgroups within its own tournament – Selection Sunday, First Four, Sweet 16, Elite Eight, Final Four – allowing the NCAA and television partners CBS and Turner to entice advertisers looking to reach specific segments of fans. Casual observers come and go depending on their favorite teams’ performance or their standing in a bracket pool, but by creating new opportunities during each week of the tournament, you’re going well beyond just capturing the Duke alumni. These subbrands leave room for brand-messaging creativity, sponsorship, accolade, and tried and true organic hype.

Even strategic brand placement within certain seating areas in arenas helps brand awareness. For example, Wendy’s placing an advertisement for late-night dining near a student-reserved section likely to imbibe after the game seems more effective. As would Northwestern Mutual advertising near luxury suites, corporate boxes and high-end seating. Both are official corporate partners of the NCAA and ramp up their marketing efforts in March.

But spending the most money doesn’t necessarily translate to the best results, especially when it comes to consumer social engagement that included 63 million social media impressions from fans during the 2017 NCAA Tournament. 4C Insights conducted an analysis of the top 20 brands airing at least 10 spots during the 2017 tournament in order to “determine the likelihood a consumer is to engage with a brand on social media within two minutes after their March Madness ad aired,” which is referred to as TV-social lift. According to 4C Insights, Capital One and Geico spent the most on television advertising with 160 commercials, but neither saw much social engagement. Acura ran 37 spots and had a 1,491 percent increase in social media engagements.

During the tournament’s championship game, Coca-Cola, which is an “official NCAA corporate champion” sponsor along with Capital One and AT&T, purchased more than five minutes of ad time and had the least amount of TV-social lift. Bud Light spent the fewest dollars and increased social media engagements 24,782 percent. All the aforementioned names are recognized major brands, but some went beyond leveraging television and online streams to spend their money wiser, increasing awareness and driving consumer engagement.

The NCAA Tournament takes broadcast breaks, be it before and after games or the off days leading up to the next round. Some web content providers have reported a 91.7 percent increase in traffic during March Madness as sponsored contests and bracket challenges draw an influx of new users. It’s also an opportunity to present solid, impact branding without it disappearing after a 30-second TV spot or having it get lost through social media scrolls. The branding stares back when the user enters the contest and throughout the duration of the tournament while they check back for results. It’s subtle, but sometimes the most influential marketing is done by teasing the brand.

Timing, creativity and audience recognition all play a role in product marketing, and any misstep during an event like the NCAA Tournament could result in plenty of missed opportunities. Get it right, and your brand awareness – no matter the target market – increases exponentially through multiple channels, regardless of company size and marketing budget.

Essentially, the NCAA has laid the groundwork for you. It branded its annual tournament into separate events that helped create exposure opportunities for small and large brands alike. That’s the marketing genius behind March Madness. When the target audience is everyone, opportunities during the NCAA Tournament exist for every single brand.

Now, it’s up to you to capitalize.

STATS DFS Projections: NBA Locks, Fades and Favorite Plays for Friday, Feb. 9


With the fantasy football season over, I wanted to highlight our NBA daily projections – both that we have them, and that they can help you win in DFS. Today’s slate is special, as it occurs the day after the trade deadline, meaning a lot of players are busy flying across the country instead of playing, and some value opened up. It’s a huge nine-game slate, so I’ll try to get to as many of the relevant players as possible.

Keep a few things in mind – first of all, there are tons of late scratches and injuries that impact NBA projections on even a normal day, and this day is particularly volatile due to the traded players. Second, there are even more data points and moving parts if I discuss every DFS site, so I’ll be sticking to DraftKings unless stated otherwise. Third: when I say somebody is a “fade”, that doesn’t mean you should craft 100 out of 100 lineups without them – just maybe avoid them in cash games and lower your exposure in multi-entry GPPs.

New Orleans @ Philadelphia

  • New Orleans injuries: None
  • New Orleans Trades (out): Dante Cunningham
  • New Orleans Trades (in): Rashad Vaughn

New Orleans made their big trade last week when they acquired Nikola Mirotic. He’s always been a 1+ DK point-per-minute guy (averaging 23 points and 9 rebounds per 36 minutes), and now he has a chance to play 30-35 minutes per night (solidified by the Dante Cunningham salary dump). He’s still priced near 30 DKP guys like Lauri Markannen and Tobias Harris, but he’s a much better bet for 40 DKP, making him one of the top plays of the night. Nobody else on New Orleans is a great play – LeBron is a more valuable centerpiece than Anthony Davis.

  • Philadelphia injuries: Markelle Fultz (still)
  • Philadelphia Trades (out): None
  • Philadelphia trades (in): None

They didn’t make any moves, so not much value opened up here. Joel Embiid can always go off, but it’s tough to afford him with LeBron. Ben Simmons is a GPP option as none of New Orleans’ small guards can stop him, but he’s too expensive in cash. The best cash play of the bunch is J.J. Redick, who is back to playing 32 minutes and can score a lot in this matchup, but there are better options out there.

LA Clippers @ Detroit

  • LA injuries: Austin Rivers (questionable), Milos Teodosic (questionable)
  • LA trades (out): None
  • LA trades (in): None

The Clippers made their move already, trading Blake Griffin to tonight’s opponent. If Austin Rivers comes back and Milos Teodosic suits up, their guard rotation gets too crowded for anybody to be in consideration. Lou Williams has gotten overpriced – I’d rather play Zach Lavine at $1500 cheaper, even if Teodosic and Rivers sit. Tobias Harris doesn’t have enough upside to be a GPP play at the same price as Mirotic, with 8 fewer projected points.

  • Detroit injuries: Reggie Jackson (out)
  • Detroit trades (out): Willie Reed, Brice Johnson
  • Detroit trades (in): James Ennis III, Jameer Nelson

Detroit traded non-rotation bigs for much needed backcourt help, but those guys probably won’t play tonight. This means Stanley Johnson and Reggie Bullock will still be playing 34 minutes, and Ish Smith should play around 30, making all 3 fantasy relevant. They’re not my preferred value plays tonight, though. Regarding Andre Drummond, see my Embiid comment, as both have similar projections and prices. Blake Griffin is the best GPP option in his revenge game, but he’s not worth it in cash.

Cleveland @ Atlanta

  • Cleveland injuries: Kevin Love (out)
  • Cleveland trades (out): Isaiah Thomas, Derrick Rose, Dwyane Wade, Iman Shumpert, Jae Crowder, Channing Frye
  • Cleveland trades (in): George Hill, Jordan Clarkson, Rodney Hood, Larry Nance Jr., Kendrick Perkins (called up from G-League)

Cleveland went and got LeBron an entirely new supporting cast at the trade deadline, but those guys aren’t playing tonight, meaning the remaining 6 or 7 rotation players have increased value. The only one I’d avoid is J.R. Smith, who is just a terrible per-minute producer at this stage of his career. Jose Calderon, Kyle Korver, and Cedi Osman should all play around 30 minutes in starts and only need 15-20 DKP to help you, so they’re great cash plays. LeBron will need to play 40 minutes and put up 60+ DKP to keep this game close (even against Atlanta), and he’s the cornerstone of all my cash and GPP lineups today. Jeff Green, even coming off the bench, is a great bet for 30 minutes and 30 DKP – he’s basically Cleveland’s 2nd option tonight. If I had to choose just 3 Cavs to roster, I’d go with LeBron, Green, and Osman.

  • Atlanta injuries: None
  • Atlanta trades (out): Luke Babbitt
  • Atlanta trades (in): Okaro White

Cleveland’s porous defense should be even worse than usual with guys like Calderon starting, but Atlanta players on a 2nd game of back-to-back are still poor cash plays. Dennis Schroder (guarded by Calderon) and John Collins are the best GPP bets on DK. Of note: Taurean Prince is so cheap on Fanduel that he’s a great value play there.

Indiana @ Boston

  • Indiana injuries: Darren Collison (out)
  • Indiana trades (out): None
  • Indiana trades (in): None

This is a tough matchup against a great Boston defense. Myles Turner is nonetheless a great play, as he’s back to playing minutes in the 30s – our baseline projections for him are 14.3 points, 7.5 rebounds, 2.3 blocks, and around 32 DKP, making him a great value at $1700 cheaper than Al Horford. Victor Oladipo will see a variety of long and capable wing defenders and is a fade for me tonight. Even with the Collison injury, Cory Joseph lacks the upside to be an optimal value play tonight.

  • Boston injuries: Marcus Smart (out)
  • Boston trades (out): None
  • Boston trades (in): Greg Monroe (signed)

Boston is playing the second of a back-to-back, with the first one going to OT. They also didn’t make any moves, and no new value opened up. Even against a fast-paced Indiana team, there’s no value here, and the entire team is overpriced. Kyrie Irving is on a minutes limit, which actually makes him a full fade in GPPs for me.

Milwaukee @ Miami

  • Milwaukee injuries: Matthew Dellavedova (out)
  • Milwaukee trades (out): Rashad Vaughn
  • Milwaukee trades (in): Tyler Zeller

Miami is one of the slowest-paced and best defensive team, so Milwaukee players are bad values tonight. We project Giannis for just 48.3 DKP tonight – any time he is under 50, you know it’s a rough projections night for the Bucks.

  • Miami injuries: Kelly Olynyk (out), Wayne Ellington (questionable)
  • Miami trades (out): Okaro White
  • Miami trades (in): Dwyane Wade, Luke Babbitt

Two former Heat players return to Miami. Wade is clearly the more exciting of the two, and he’s excited too – he’s the only trade-deadline mover to be declared active as of this writing. I envision him as Miami’s primary backup swingman, which kills Ellington’s, Tyler Johnson’s, and Justise Winslow’s values, while not providing enough himself. Josh Richardson is playing too well to lose minutes, though I can see Goran Dragic playing closer to 30 than 35 with Wade taking over more ball-handling. Hassan Whiteside is the most intriguing play, though he’s GPP-only given that he can play 20 or 35 minutes.

Minnesota @ Chicago

  • Minnesota injuries: None
  • Minnesota trades (out): None
  • Minnesota trades (in): None

The Thibodeau Bowl is more interesting this year, with Jimmy Butler back in town for his revenge game. That narrative aside, it’s a pretty typical Minnesota game – Butler and Karl-Anthony Towns are good bets for 40 DKP, while the other 3 starters are 25-30 DKP guys. None of them stand out as particularly good values, and you’ll have trouble rostering them along with LeBron.

  • Chicago injuries: Kris Dunn (out)
  • Chicago trades (out): Jameer Nelson
  • Chicago trades (in): Noah Vonleh

Lauri Markkanen should be back, which means Bobby Portis is back to a 20-minute bench guy, and he’s not a cash play anymore – in fact the entire frontcourt is too crowded for DFS. In a potentially high-scoring game, though, the thin backcourt makes for great plays. We project Zach Lavine for more DKP than Lou Williams at $1500 cheaper, and Jerian Grant is projected for similar output to his counterpart Jeff Teague at $800 cheaper. Both of those guys are great cash and GPP plays in a potentially high-scoring game, and both will be looking to leave their mark before Kris Dunn returns to take away minutes and usage.

Denver @ Houston

  • Denver injuries: Paul Millsap (out), Mason Plumlee (out)
  • Denver trades (out): Emmanuel Mudiay
  • Denver trades (in): Devin Harris

Even in a normal Denver game, their players are typically great DFS options. Tonight, against the Rockets, they’re even better. Devin Harris won’t play yet, which means some of Mudiay’s minutes should go to Will Barton and Jamal Murray – both are great bets for 35 minutes, and Barton especially is a great cash play at $1400 cheaper than Jrue Holiday (with higher projections). Nobody on the Rockets (or in the NBA?) can guard Nikola Jokic, and in this high-scoring affair he’s the optimal 2nd-best-player in lineups next to LeBron.

  • Houston injuries: Trevor Ariza (out), Eric Gordon (quest), Ryan Anderson (quest)
  • Houston trades (out): None
  • Houston trades (in): None

It’s too early to say much about Houston, as a lot depends on whether Gordon and Anderson suit up. If they do, nobody is a great cash play, with James Harden and Chris Paul remaining typically viable GPP-only options. If they sit, I’m increasing my James Harden exposure and making sure I have some Luc Mbah-a-Moute and Gerald Green in GPPs. Chris Paul, by the way, is a great cash-game value on Fanduel, but not on Draftkings.

Charlotte @ Utah

  • Charlotte injuries: None
  • Charlotte trades (out): Johnny O’Bryant
  • Charlotte trades (in): Willy Hernangomez

Charlotte is coming off an OT game last night, and they have a tough match-up against Rudy Gobert and the Jazz. I’ll pass, especially without any injuries or major trades to unlock value.

  • Utah injuries: None
  • Utah trades (out): Rodney Hood
  • Utah trades (in): Jae Crowder

Trading Hood for Crowder solidified Donovan Mitchell’s 35 minutes – he had played less and struggled the last two games (as they were showcasing Hood perhaps), but I think he’ll be fully back tonight and is a solid play. The best value on Utah tonight is Derrick Favors, as he can punish whoever guards him, whether it’s the smaller Marvin Williams or clumsier Dwight Howard. Favors is in a projections tier with Portis, Taj Gibson, and Thaddeus Young at PF, and he’s cheaper than all of them. The only PF I like more tonight is Jeff Green, who is more of a value play.

Portland @ Sacramento

  • Portland injuries: None
  • Portland trades (out): Noah Vonleh
  • Portland trades (in): None

This is a high-upside matchup for the usual suspects (Damian Lillard and CJ McCollum), but there’s some risk involved as they played an OT game last night. Jusuf Nurkic is playing good basketball lately, and he’s a better bet than usual for 30 DKP, as the rebounding recipient of many Sacramento bricks. I still wouldn’t roster him (or any of his teammates) in cash, and there’s not much else going on here.

  • Sacramento injuries: Skal Labissiere (out), De’Aaron Fox (quest)
  • Sacramento trades (out): George Hill
  • Sacramento trades (in): None

Sending out George Hill and cutting Georgios Papagiannis solidifies minutes in the 30s for Fox, Bogdan Bogdanovic, and Willie Cauley-Stein. In the long-run, those guys all benefit, but tonight I’m more interested in Zach Randolph. With Labissiere out and Papagiannis gone, he’s a near lock for minutes in the high 20s, and he’s still capable of producing over 1 point-per-minute. He’s the most optimal play and up there with Favors amongst my favorite PF/C options tonight. A couple GPP-only specials for you: 1) Buddy Hield is a sneaky good per-minute producer and may be the biggest beneficiary of the George Hill trade. 2) Jakarr Sampson could see blowout or youth-movement minutes at PF, and he has proven to be a double-double threat when given extended run – he is a GPP flier, especially to hedge against some of your Randolph exposure.