Technology has heavily contributed to our ever-evolving understanding of pitching. The Rapsodo system, in particular, can be attributed for this change, by allowing both players and coaches to maximize a pitcher by observing the physicalities of his pitches.

Kyle Boddy and his company, Driveline, have been at the forefront of the “Rapsodo movement”, continuously releasing articles on how to maximize the effectiveness of certain pitches. Rapsodos, which can found in the bullpens of almost every Major-League club, track, break down, and analyze a pitcher by using slow-motion cameras. By analyzing the data gleaned from a Rapsodo machine, pitchers can be recommended to change their arm slot, boost their spin efficiency, or locate their pitches better.

With technology dictating the future of the pitching landscape, amateur coaches have been forced to rethink their now-outdated adages. One aspect of their lessons they have been forced to change involves the idea that pure velocity isn’t the name of the game anymore. What good is a 100 mph fastball if it’s as straight as a string? Velocity can’t be the only weight to evaluate pitches; the movement, the spin axis, and spin efficiency are only some of the other factors that come into play.

That’s where Pitch Design comes into play.

Using the information provided from the Rapsodo system, Boddy and the rest of the pitching geniuses over at Driveline have created a slew of new metrics that have advanced our understanding behind the physics of pitching. Terms like gyro spin, transverse spin, and spin efficiency didn’t exist ten years ago, yet, they have completely revolutionized pitching as we know it.

It’s always confused scouts and analysts how certain pitchers can throw 100+ mph fastballs and quality secondaries in their bullpens, but can’t translate that to above-average ERA numbers. Take Gerritt Cole, for an example. Cole was stuck with the old-fashioned Pirates, a club that relied on old and outdated information. But once Cole was moved to the analytically-inclined Astros, they took full advantage of his repertoire.

Houston emphasized the usage of his high-spin fastball, instructing him to throw it in the upper echelon of the strike zone, where it would be more difficult for batters to square up to the pitch. Lo and behold, the next months found Cole in the discussion for the best pitcher in baseball and the owner of the richest contracts in Major League Baseball history.

Enter the Mets’s saver: Seth “Quarterrican” Lugo.

Lugo’s certainly an unique ballplayer. He has a partially torn UCL in his pitching elbow, suffered on the outset of the 2017 campaign. When his UCL tear was discovered, there were two options on the table: Tommy John Surgery or rest and continue pitching with a slightly frayed ligament in his elbow.

Lugo, coming off his first season in the Majors, opted for the latter option. Risk be damned, he wanted his 100 innings in 2017. After sitting out the first two months of the season, he returned in June and has fortunately avoided any more major arm injuries ever since.

Over the last four seasons, Lugo’s role has changed more times than a Mets free-agent signee hasn’t panned out. In his debut season in 2016, he functioned as a swingman, appearing in the rotation only after Steven Matz was placed on the IL with ulnar nerve irritation. After the Mets’ starters slowly began to emerge from the depths of the IL the following season, Lugo was shifted back to the pen, despite a clear preference to stay in the rotation.

In spite of a ticking time bomb that only time will set off embedded in his elbow, Lugo has transformed from a decent swingman option into one of baseball’s most dominant relievers.

Moving Lugo to the pen wasn’t big news at the time, but it has quietly become one of the brightest decisions the Mets have made this decade. That being said, there aren’t many choices to choose from.

Edwin Diaz, Jeurys Familia, Justin Wilson were brought aboard last offseason to shore up the Mets’s bullpen corp, leaving Lugo without a prominent role. A year after the acquisitions, it’s clear everything didn’t go to plan. Díaz had fans wishing Armando Benetiz was back after merely two months into the season. Meanwhile, the performance of Former Proven Closer™ Jeurys Familia didn’t inspire much hope that’d be able to reclaim his old role. A 7.50 ERA at the All-Star Break will test the patience of any competent manager.

Lugo racked up six saves and WPA of 3.04 before the season’s end, utilizing a curveball that had to be taught to him by Dumbledore. The thing looks like it has Locomoter spell attached to it. It comes out of Lugo’s hand, moves up a tad, then dives to the depths of the strike zone. Nearly impossible to hit.

Here's 90 seconds of Seth Lugo making hitters look silly with his curveball to get you through your Monday. pic.twitter.com/snDsXGffMg

— Jacob Resnick (@Jacob_Resnick) November 25, 2019

Anthony Rizzo was Lugo’s first strikeout in the Majors. He swung and missed on a curveball.  That hit him in the foot. Just shows how dastardly the pitch is.

Here's a look at the @seth_lugo high-spin curve that got Rizzo: pic.twitter.com/3o9LeeW7Va

— Mike Petriello (@mike_petriello) July 2, 2016

His curveball quickly gained some hype as one of the more deceptive pitches in the Majors, earning a breakdown from Fangraphs‘ Dave Cameron shortly after his debut. Cameron looked at the outstanding spin rate of the pitch, noting that, if everything gelled right, Lugo’s arsenal could help him settle in as an above-average hurler.

His curveball has baseball nerds, like myself, salivating. It has the analytical qualities you’re looking for in an effective pitch, such as fantastic spin rate marks and a high spin efficiency. Over the last four seasons, the spin on his breaker averaged 3164 RPM, peaking out 3498 RPM.

It also possesses tremendous movement. In 2019, his curveball had 61.9 inches of drop, a number that came in 17% more than the average player. Meanwhile, the pitch had 12.7 inches of horizontal movement, a mark that was 28% better than the league-average curveball.

While the breaker has earned the credit for Lugo’s breakout (and for good reason), it’s far from the only reason he’s found himself at the backend of the Mets’s pen. Lugo’s been commended for his quality pitch tunneling skills in the past. Last year, Devan Fink of Fangraphs explored his tunneling efforts, noting that Lugo’s curveball, fastball, and sinker have created one of the more formidable trios of offerings in the game.

His sinker certainly isn’t his standout delivery, but it’s quietly become one of the more underrated deliveries of his arsenal. Michael Augustine sent out this tweet in early May, noting the impressive physicalities behind Lugo’s sinker.

https://twitter.com/AugustineMLB/status/1258418227308384256

Augustine cited Lugo’s spin direction and Magnus efficiency, terms that might confuse the average fan, but are commonly used in pitching labs to measure the effectiveness of certain pitches. These phrases deal with the analysis of a pitch’s spin.

A couple new terms to introduce here.

First off, spin direction. Spin direction describes the angle a pitch leaves a pitcher’s fingers. The angle of release influences a pitch’s vertical and horizontal movement. It is usually expressed in a “time” format, as the concept is much better understood when seen with a clock and the exact release point.

Rapsodo.com states its definition as “reading the direction the seams are traveling as the pitcher releases the ball.”

For those are visual learners, here’s a couple of fantastic tweets.

Pitch design wizard @ericjagers has been using DrivelineEDGE to overlay ball visualizations on top of high-speed footage as a means of fixing seam orientation. This has trimmed the learning curve tremendously in terms of picking up spin axis on video.https://t.co/xHL0tCXRmu pic.twitter.com/bJXhVxoqdS

— Driveline Baseball (@DrivelineBB) December 7, 2019

Meanwhile, Magnus efficiency, which is more commonly known as spin efficiency, calculates how much the pitch moves, in relation to the spin direction. A high spin efficiency allows the pitch to function better. Take Lugo’s sinker, for example. Thanks to its high spin efficiency, it retains the shape of the pitch better, generates more spin, and doesn’t fall into a zone that would allow for hard contact. If his spin efficiency was, let’s say, 50%, the pitch would get hit a lot harder. The same can be said for his curveball. A high spin efficiency gives the pitch more late life.

For visual learners:

How does Spin Efficiency affect fastball movement?

Here are 7 fastballs recreated in Driveline EDGE
(https://t.co/tWECLaIr5M)

1:00 axis 2300 rpm 90 mph
Fastball Efficiency ⬆️ by 10% starting at 40% (red) and ending at 100% (green).

pitches zone location = break plot (hb/vb) pic.twitter.com/ymzx3JtTmX

— Anthony Brady (@BaseballFreak_9) October 21, 2019

The post Exploring Seth Lugo’s Pitch Design appeared first on Metsmerized.

The St. Louis Cardinals and Tampa Bay Rays have struck a deal for Tommy Pham.

Pham is hitting .248/.331/.399 this season with a 101 wRC+. This is a far cry from his 2017 slash of .306/.411/.520 and 148 wRC+ but Pham is still a good defender and baserunner under team control.

Pham currently sports a .320 wOBA but his expected wOBA is .369, which is a sign that he is due for some good luck in the future.

The Rays gave up OF Justin Williams, LHP Genesis Cabrera, and RHP Roel Ramirez. Williams is ranked as the 14th best Rays prospect on MLB pipeline. Cabrera ranks 25th on the list and Ramirez is a right handed reliever in AA.

The Rays really look like they made out great in this deal.

The post Rays Acquire Outfielder Tommy Pham appeared first on Metsmerized.

It’s easy to forget how awesome Michael Conforto‘s 2017 season was for several reasons.

For starters, it ended with him writhing in pain on the ground with a dislocated shoulder, a crashing hault to his breakout campaign. Another was how the Mets season devolved into irrelevance. But in many ways, Conforto was, and still is, a rising star.

The 24-year old slashed .279/.384/.555 with a .392 wOBA and 146 wRC+ over 440 plate appearances prior to his injury in August.

There are only two players in Mets history who had a higher wOBA than Conforto did in a single season at age 24 or younger: Darryl Strawberry and David Wright, the latter of which did it twice. In regards to Mets history, that is some strong company to be with.

Conforto ranked 14th in wRC+ in all of Major League Baseball among everyone with 400 plate appearances in 2017. He ranked seventh in wRC+ among outfielders and was third among all center fielder in wRC+ behind just Tommy Pham and Mike Trout.

Trout, Pham, and Charlie Blackmon were the only center fielders with a higher wOBA and OBP than Conforto in his third year of play.

Conforto is an elite offensive outfielder and Fangraphs ranked him as the third best center fielder in all of baseball for this year.

There’s nothing to indicate that Conforto was just lucky in his breakout season. Conforto posted a .577 wOBA on fly balls and a .818 wOBA on line drives.

His exit velocity on fly balls and line drives was a stout 95.3 MPH, which was good for 35th out of 387 in Major League Baseball players among hitters who hit at least 100 balls into play. So the fact he hits the ball so hard in the air is certainly a reason to think his performance on “air balls” is sustainable.

There are concerns about Conforto in center field, but he definitely has the tools to hold his own out there.

His sprint speed is 27.6 feet-per-second which is slightly above average for center fielders in baseball. His sprint speed is better than Adam Jones, Joc Pederson, and Odubel Herrera. Of course, sprint speed is not everything, but being reasonably fast in center and having good defensive positioning should help Conforto. He could be a modest or average defender in center, which is more than fine giving the impact of his bat.

Add to the fact that he is just 25 and is only improving from here on in and there is a lot to be excited about.

The only real concern is whether his shoulder injury will linger with him long-term. So far, given his quick rehab and solid reports from the minor league camp, it would appear that his power and bat speed might still be the same.

Of course, many fans become skeptical when it comes to propping up their own players, but feel good, Mets fans. Conforto by all means is a rising star in Major League Baseball and his return will be a huge boost to this team both on and off the field.

The post Despite Injury, 2018 Still Looks Bright For Conforto appeared first on Metsmerized.

My colleague, Connor O’Brien, did a series of getting to know your sabermetrics statistics in 2016. I wanted to continue his efforts to bring more stats to you that many baseball front offices believe are important in player evaluation.

The one we will discuss today is expected weighted on base average or xwOBA. Weighted on base average (wOBA) gives hitters credit for the types of ways that they reach base. The biggest complaint with OBP is that it doesn’t measure the fact that hits are better than walks. Which is absolutely true, hence, we have wOBA. wOBA does what batting average doesn’t, it includes walks and it gives hitters more credit for hitting home runs or doubles.

For example, if hitter A went 2-for-4 with two singles, hitter B went 0-for-2 with two walks, and hitter C went 2-for-4 with two homers, then who had the best day? Well the answer should be easy, it was hitter C because a home run is always the best outcome. Here’s the issue: they all had the same OBP and both hitters A and C had the same batting average. So there itself is wOBA’s value, it gives proper weight to hits unlike batting average or OBP. I linked Connor’s explanation of wOBA if you want a more detailed explanation of the statistic.

Expected wOBA measures the players luck when it comes to his wOBA. It uses exit velocity and launch angles in its calculation to say why a player was lucky or unlucky. The previous measure was batting average of balls in play, or BABIP. The problem with BABIP is that it does not account for home runs because it is not a ball in play. Additionally, it does not account for walks, sort of like the actual batting average statistic. So xwOBA does a better job of giving a player credit and sometimes, a low BABIP is justified if hitters are not hitting the ball hard.

Take Rhys Hoskins for example. Hoskins slashed .259/.396/.618 with a .417 wOBA and 158 wRC+. He hit 18 home runs in just 212 plate appearances which is simply amazing and he also coupled that with a 17.5 percent walk rate. His BABIP was .241, however, which would suggest he was unlucky and should have been better. Here’s the problem: how unlucky were you if you still managed to slash .259/.396/.618? His xwOBA though was .399, a little bit lower than his actual wOBA. So Hoskins really wasn’t unlucky nor did he benefit that much from luck.

Here’s a Mets related example: Brandon Nimmo. Nimmo really excelled after becoming a regular out there. From the day after Curtis Granderson was traded to the end of the season, Nimmo slashed .259/.375/.453 with a .361 wOBA. He did have a .341 BABIP for that stretch, however, so some people are hesitant in thinking he would be able to maintain this same level of production for the 2018 season. During that stretch though, Nimmo had a .358 xwOBA, almost identical to his actual wOBA.

Why is that? Well Brandon Nimmo had a 14.8 percent walk rate in that time and that number is not too drastic from his season walk rate of 15.3 percent. In fact, Nimmo has shown an elite eye throughout all of his professional career, so there’s a legitimate chance that he is the real deal.

Another guy who did well from that same time frame was Kevin Plawecki. Plawecki slashed .303/.411/.474 with a .391 wOBA. Plawecki made changes to his game because he was hitting more balls in the air than ever before and pulling them with authority. His xwOBA in that time was .371 which would mean he was lucky, but a .371 wOBA for a catcher would still be great.

Well there you have it. This statistic was developed by Baseball Savant and I highly encourage you to play around with Statcast. You can do a lot of your own research as I have on these players and every other player in baseball. These stats are still new, but are becoming very popular around baseball and in front offices.

The post Know Your Stats: Expected Weighted On Base Averaged (xwOBA) appeared first on Metsmerized.

One of the primary concerns heading into the Mets offseason is the third base situation. There are two legitimate free agent candidates in Eduardo Nunez and Todd Frazier. 

In this era of baseball, Statcast is one of the more important parts of the game. Teams are starting to look at it over scouting. The Astros are one of the organizations primarily focusing on it to judge talent going forward.

Of these four players, Statcast really looks poorly on Eduardo Nunez more than anyone else in the third base market. Nunez has a .275 xwOBA according to Baseball Savant, which means .275 expected wOBA. wOBA takes into account the value of certain hits over others. For example, it values hits like doubles and home runs more than it values walks or singles. It makes sense since a double, triple, or home run is more likely to help a team score a run than a single or walk. Nunez had a wOBA of .348 this past season and his xwOBA is .275. For reference, Rene Rivera had a .273 wOBA with the Mets in 2017.

A stat like xwOBA paints a better picture than BABIP (bating average of balls in play) because BABIP does not account for walks or home runs. For example, Brandon Nimmo had a BABIP of .360 but his xwOBA was .346, not a far cry from his real wOBA of .353.

Nunez had a ground ball rate of 53.4% but hit only .332/.332/.359 with a 84 wRC+, and .301 wOBA on balls on the ground. His numbers on line drives and fly balls are what really carried his 2017 season. He had a 132 wRC+ on fly balls and 260 wRC+ on line drives.

Here is the issue with Nunez, those numbers seem unsustainable. Nunez’s percentage of barreled balls in play is just 1.7%. His rank among those with 30 batted ball events is 447th. This is the same percentage of barreled balls as Yankees backup catcher, Austin Romine. Nunez seems unlikely to sustain his production on fly balls and line drives given this statistic.

Nunez slashed .313/.341/.460 with 12 home runs, 33 doubles, 24 stolen bases, 60 RBI and a 112 wRC+ this season. His 3.7% walk rate was the fifth lowest in the majors in 2017.

Also key to point out that Nunez missed most of September with a knee injury that knocked him out of the playoffs after only one at-bat.

Todd Frazier on the other hand has a xwOBA of .352 but his real wOBA was just .340. Frazier has been an adept fly ball hitter since 2014 and could succeed more when working with Kevin Long. Frazier barrels the ball in 9.6% of his batted balls events. That number was good for 88th in the MLB among those with 30 batted ball events.

Frazier finished the 2017 season hitting .213/.344/.428 with 27 home runs, 76 RBI and a 108 wRC+. His 14.4% walk rate was the sixth best in the majors.

Defensively, Frazier is the much better defender. He has 30 career defesnive runs saved and whereas Nunez has -5 DRS at third base. Frazier’s 6.0 UZR/150 bests Nunez’s -10.5 UZR/150, which gives a good idea of who could be a better defender in the long run.

Frazier can also play first base in the event Dominic Smith needs more seasoning but Frazier will likely not hit enough to be considered a long-term first baseman. He is also too good of a defender at third to play first base. Frazier’s ability to play everyday is also very impressive, he has not played less than 147 games since 2012.

While xwOBA is not the end all be all, but it should definitely be looked at when we analyze a player’s season. Nunez might succeed as a Met and get sprinkled with the Kevin Long-fly ball revolution dust. Frazier seems like the better fit though for the Mets in my opinion.

Both will get similar contracts, but Frazier is the better fielder and is the safer bet for the better hitter going forward.

The post A Statcast Look at Two Free Agent Third Basemen appeared first on Metsmerized.

If you think the Mets are going to acquire another Yoenis Cespedes to save the struggling offense, think again. According to Randy Miller of NJ.com, the Mets are targeting role players rather than a big bat.

According to Miller’s source, the farm system has been depleted by the recent graduations of Noah Syndergaard, Steven Matz, and Michael Conforto so the team may not be in a position to make a big splash without giving up most of what’s left.

The Mets are 28th in runs scored this season and 21st in wOBA. They’re also batting a league-worst .207 with runners in scoring position.

The post Mets Reportedly Looking For Role Player, Not Big Bat appeared first on Metsmerized.

In last week’s installments of the widely-beloved “Know Your Stats” series, we looked at both OPS/OPS+ and wOBA. Today we already looked at wRAA and will now cover wRC+.

Of all the popular offensive statistics publicly available in the baseball world, Weighted Runs Created Plus (wRC+) may be the gold standard. It combines the corrections to batting average, OBP, and slugging made by wOBA with the convenience of a park-adjusted index.

wRC+ is basically rooted in wOBA, but there is a multi-step process involved in getting it from start to finish. If you don’t remember from last week, wOBA is a rate stat just like your traditional BA/OBP/SLG, except it corrects each of those stats’ faults.

To get from wOBA to wRC+, the former is first turned into wRAA. That is done through the simple process I outlined this morning.

Once we get wRAA, it is turned into wRC+ through the following formula:

This looks way more confusing than it actually is, but I’ll explain what it does in simple terms. It converts wRAA from a raw total into an index stat like OPS+, where 110 is ten percent better than league average and 90 is ten percent worse.

Like OPS+, wRC+ is league and park adjusted, meaning it makes it easy to compare players from different eras and in different parks.

More thoughts

• If you are thinking about trying to correlate wRC+ to runs scored, don’t. If we were trying to correlate with runs scored, we wouldn’t be adjusting for anything.
• If choosing between OPS+ and wRC+, choose wRC+. The difference probably won’t be very significant, but both are widely available and wRC+ is a bit better.

In context

(Courtesy of Fangraphs)

Previous installments

• OPS/OPS+
• wOBA
• wRAA

The post Know Your Stats: Weighted Runs Created Plus (wRC+) appeared first on Metsmerized.

We continue our widely-beloved “Know Your Stats” series with a “gateway stat:” Weighted Runs Above Average. wRAA is essentially wOBA converted into runs, but understanding wRAA is crucial to understanding Wins Above Replacement and Weighted Runs Created Plus, which we’ll be talking about this afternoon.

One of the biggest issues with rate statistics like wOBA and On-Base Percentage is that they don’t put the production into baseball terms. What does a .340 wOBA really mean? wRAA makes it easy by putting it into the “currency” of baseball: runs. Before we get started, here is the wOBA formula this year

wOBA = (0.688×uBB + 0.719×HBP + 0.878×1B + 1.245×2B + 1.576×3B + 2.030×HR) / (AB + BB – IBB + SF + HBP)

The formula for wRAA is pretty simple. To convert a .350 wOBA to wRAA, you simply subtract the league wOBA (.313 in 2015), and divide that by the wOBA scale for that year, which slightly changes based on the particular weights for that season. Then, to adjust for playing time, you multiply by plate appearances. Here is the formula:

wRAA = ((wOBA – league wOBA) / wOBA scale) × PA

Now here is the formula for someone from last with 600 plate appearances and a .350 wOBA:

wRAA =  ((.350 – .313) / 1.251) × 600

wRAA = (.037/1.251) x 600

wRAA= 17.7 runs above average

Just as it sounds, this player would be worth 17.7 runs above average at the plate. How good is that exactly? Here is a “rule of thumb” chart for the stat, courtesy of Fangraphs:

Of course, it’s important to remember that like wOBA and any traditional rate stat, wRAA is context-neutral. Also, wRAA is critical for understanding Wins Above Replacement, since it is the offensive component. You won’t see it used much in articles because it doesn’t have all that much practical use on its own, but as you’ll see, knowing it makes it easier to wrap your head around a few more widely-used stats. That’s why it’s in some ways a “gateway stat.”

In Context

Further Reading

• wRAA – Fangraphs
• wRAA For Position Player WAR Explained- Baseball-Reference
• How wRAA fits into fWAR

Other installments

• OPS/OPS+
• wOBA

The post Know Your Stats: Weighted Runs Above Average (wRAA) appeared first on Metsmerized.

Yoenis Cespedes is the current team leader in wOBA with a .395 mark.

For the next few days, I will be bringing back my “Know Your Stats” series that I began a few years back to highlight some important sabermetric stats and concepts. Earlier today, we went through OPS and OPS+. Now we continue with wOBA…

Perhaps the best way of describing weighted-On Base Average (wOBA) is to describe the faults of some of the traditional hitting statistics first.

Batting average, for all its history, fails on numerous fronts. For one, it values all hits equally, from an infield single to a home run. It also doesn’t include walks, which, however unexciting, undeniably contribute to a team. On-Base Percentage does a little bit better, adding walks to batting average, but again values a walk and a home run as the same. Slugging percentage attempts to weigh certain hits as more valuable than others, but fails to include walks and doesn’t weigh hits properly. A triple, for example, is not worth three times as much to a team compared to a single. We know this because of linear weights, which show that a triple does not create a run expectancy three times greater than one created by a single. Before we get to wOBA, it’s important to understand one very important thing about linear weights, which will clear up the somewhat confusing formula. Take a look at this excerpt from Fangraphs’ library:

There is nothing arbitrary in the exact weighting we have of a home run relative to a triple, or a ground ball to a line drive. Years upon years of data allow us to convert back and forth, or up and down with ease. A common complaint with modern sabremetrics is the bewildering array of fractional coefficients that dot the scene, but if you look at a formula that’s based on linear weight, don’t see them as confusing numbers. Instead, look at them as relative values, derived through years of baseball being played.

Essentially, the coefficients in wOBA come from the decades of baseball history that show us how singles, doubles, triples, home runs, walks, and HBP affect a team’s run expectancy. When you look at the wOBA coefficients, they intuitively make sense before you even look at what the linear weights tell you. A walk is worth slightly less than a single because a single moves runners over two bases more often. Just as eras change, wOBA can slightly change from year to year, although nothing really changes that significantly. You can see the constants going back to 1871 here. Here is the current wOBA formula:

wOBA = (0.688×uBB + 0.719×HBP + 0.878×1B + 1.245×2B + 1.576×3B + 2.030×HR) / (AB + BB – IBB + SF + HBP)

More Thoughts

• wOBA is a context-independent statistic meaning a walk with the bases loaded and a walk with the bases empty are weighted the same, just like most traditional statistics we deal with.
• wOBA and its park-adjusted, indexed counterpart wRC+ are the gold standard for publicly-available offensive statistics.

In Context

Further Reading

• Visual Look at wOBA- Fangraphs
• Intro to Linear Weights- Fangraphs
• All-Time wOBA Leaderboard

The post Know Your Stats: Weighted On Base Average (wOBA) appeared first on Metsmerized.

For the next few days, I will be bringing back my “Know Your Stats” series that I began a few years back to highlight some important sabermetric stats and concepts. We begin this afternoon with OPS and OPS+.

OPS, or On Base Plus Slugging was one of the first sabermetric stats to go mainstream. It is, as the name implies, On-Base Percentage plus Slugging Percentage. It’s crude and simple, but it’s a good quick and dirty reference tool

OPS is expanded on even further when made into an index, OPS+. OPS+ does something very important: puts the OPS into context. The stat makes it possible to compare players from different eras, different teams, and different ballparks.

OPS+ is set on a percentage point scale. Essentially it is the percentage of league OPS. 100 (or 100% of the league average) is the league average, while a 110 mark is ten percent better than league average, and 90 is ten percent worse.

There are many issues with the crude OPS and OPS+. Is one point of OBP worth the same as one point of SLG? The math says no. In fact, the math says a point of OBP is worth 1.7 times what a point of Slugging is. Neither OPS nor OPS+ tell you the composition of OBP or Slugging and thus overvalues extra base hits.

OPS as I mentioned, is crude and the most basic sabermetric stat out there. It has its flaws, but it is a great way to get people to start thinking about sabermetrics. OPS and OPS+ are solid stats and certainly better than batting average, although not as good as wOBA or wRC+.

More thoughts

• Anytime there is a stat with a “+” at the end, that means it is an index and adjusted for park factors. I get a lot of questions and concerns about the fact that these park factors sometimes change from year to year. However, these changes are so miniscule from year to year that they don’t really effect the stat. Here are Yankee Stadium’s park factors going back to 2009:

Formula

OPS= ((H +BB+HBP)/PA) + (TB/AB)

OPS+=100 x (OBP/lgOBP*+SLG/lgSLG*- 1) then park adjusted

In Context

Further Reading

• Shortcomings of OPS as an Advanced Metric- Sports Data Research

• Career OPS+ Leaderboard

Up Next: wOBA

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