Who’s Responsible for the Cubs’ Incredible Pitching Stats?
The Chicago Cubs are the unquestioned best team in baseball at the moment. There is no aspect of the game where the team struggles. They hit, hit for power, field and run the bases at a high level, pitch well as starters, and pitch well as relievers. When we ask questions and delve into the numbers, we do not ask if they are good. Instead, we ask how good are they, how this happened, and who is responsible. On the hitting side of things, numbers are easier to come by and believe in. On the run-prevention side, however, assigning value between pitching, defense, and luck can be difficult.
Back in June, August Fagerstrom noted that the Cubs’ opponent BABIP, then at .250, was basically the lowest of the past 55 years when adjusted for league average. Back in June, we had not yet completed half the season. Now in September, with the season nearly complete, the Cubs BABIP has risen… all the way to .251, increasing just one measly point. The Cubs are preventing balls in play at a record level.
On balls in play there are three principal groups of actors: pitchers, hitters, and defenders. While an individual hitter might have a decent amount of control over whether a batted ball becomes a hit or an out, pitchers face so many different hitters over the course of a season that, for any one pitcher and any one team, the control by the pitcher and defense on batted balls is likely very influential. So how do we break this down?
First, let’s back up a step, and note something else the Cubs have been doing at a historic level. Generally speaking, a team’s FIP is going to be fairly close to a team’s ERA. Since World War II, there have been 1,716 team seasons, and all but 108 (6.3%) have produced an ERA and FIP within a half-run of each other; two-thirds of teams, within a quarter-run. The Cubs are one of the biggest outliers we have ever seen.
| Season | Team | ERA | FIP | E-F |
| 1954 | Giants | 3.10 | 3.86 | -0.76 |
| 1999 | Reds | 3.99 | 4.74 | -0.75 |
| 1948 | Indians | 3.22 | 3.94 | -0.72 |
| 2016 | Cubs | 3.08 | 3.80 | -0.72 |
| 2002 | Braves | 3.14 | 3.83 | -0.69 |
| 1965 | Twins | 3.14 | 3.81 | -0.67 |
| 1955 | Yankees | 3.23 | 3.90 | -0.67 |
| 1990 | Athletics | 3.18 | 3.84 | -0.66 |
| 1967 | White Sox | 2.46 | 3.11 | -0.65 |
| 1957 | Yankees | 3.00 | 3.65 | -0.65 |
So we see the Cubs up there, and wonder what could be causing this. Do the Cubs have a secret sauce? Is it the pitching? Is it the defense? Is this luck?
First, let’s find some statistical causes that would allow a team’s ERA to beat its FIP. Two of the main components for which FIP doesn’t account and that ERA does are (a) sequencing (i.e. the order in which events happen and whether an event occurs with runners on base), and (b) balls in play (i.e. whether a ball is a hit or an out when it stays in the ballpark). The two relevant statistics that measure those things are left-on-base percentage (LOB%) and BABIP. Here’s the chart above, with LOB% and BABIP included.
| Season | Team | LOB% | BABIP | ERA | FIP | E-F |
| 1954 | Giants | 77.6 % | .255 | 3.10 | 3.86 | -0.76 |
| 1999 | Reds | 74.2 % | .262 | 3.99 | 4.74 | -0.75 |
| 1948 | Indians | 74.5 % | .252 | 3.22 | 3.94 | -0.72 |
| 2016 | Cubs | 78.1 % | .251 | 3.08 | 3.80 | -0.72 |
| 2002 | Braves | 77.2 % | .271 | 3.14 | 3.83 | -0.69 |
| 1965 | Twins | 76.7 % | .250 | 3.14 | 3.81 | -0.67 |
| 1955 | Yankees | 75.9 % | .247 | 3.23 | 3.90 | -0.67 |
| 1990 | Athletics | 75.7 % | .256 | 3.18 | 3.84 | -0.66 |
| 1967 | White Sox | 76.9 % | .245 | 2.46 | 3.11 | -0.65 |
| 1957 | Yankees | 77.2 % | .254 | 3.00 | 3.65 | -0.65 |
You might notice that all of those teams conceded pretty low opponent BABIPs, with the highest being the 2002 Braves’ .271 mark. Those LOB% marks are quite high, as well: the league average is generally in the low-70s — this season, it’s 73% — indicating that the Cubs are stranding runners at high levels. Last season, Ben Lindbergh took a pretty in-depth look at a St. Louis Cardinals rotation that had produced a very low ERA and very high LOB%, searching for the causes of that disparity. The Cubs have joined those ranks this season.
| Season | Team | LOB% |
| 1968 | Tigers | 79.5 % |
| 2015 | Cardinals | 79.4 % |
| 1972 | Indians | 78.8 % |
| 1972 | Athletics | 78.1 % |
| 2016 | Cubs | 78.1 % |
The Cubs have recorded a historically high LOB% and historically low BABIP. Those two statistics explain most of the difference between FIP and ERA. For the 1289 pitchers who have qualified for the ERA title since 2002, the correlation coefficient between BABIP and ERA-FIP is 0.70 and the correlation coefficient between LOB% and ERA-FIP is -.73. On a team level, in that time, the correlation is even stronger for BABIP (.79) and LOB% (.81). A multiple linear regression for those two stats and ERA-FIP produces an r-squared of 0.80 using the 450 team seasons over the past 15 years.
When Lindbergh looked at the Cardinals last year, he found the Cardinals were getting considerably better results with runners on base — in which situation most teams actually fare worse. The Cubs also have bucked the trend of faring worse with runners on base results-wise: teams have posted nearly identical wOBA (.274 with bases empty, .276 with runners on) despite a higher FIP, thanks in part due to a slightly lower BABIP (.246 with runners on, .255 with bases empty). This is part of the equation when it comes to the Cubs beating their FIP, and this part is going to be mostly luck-based. As that’s not particularly satisfying so far as explanations go, let’s move on to the other part: BABIP.
We already know the Cubs have historically low BABIPs right now, and that’s true both for the starters and the relievers. As the starters get most of the innings, let’s look at their BABIP figures from this year, last year, and their careers overall.
| Career | 2015 | 2016 | |
| Jon Lester | .297 | .303 | .257 |
| Jake Arrieta | .265 | .246 | .228 |
| Kyle Hendricks | .268 | .296 | .236 |
| Jason Hammel | .299 | .288 | .264 |
| John Lackey | .302 | .295 | .249 |
All five starters are posting BABIP numbers well below both their career averages and also last season’s figures. There are certain pitchers who might be able to post low BABIPs regularly, but those pitchers are not only rare but also difficult to identify. Over the last 15 years, 142 starters have logged 1,000 innings and only one pitcher, Chris Young, has posted a BABIP below .265, and he is a very rare, very tall, extreme fly-ball pitcher. Of the 10 pitchers who even posted a BABIP under .275, only Clayton Kershaw and Carlos Zambrano were ground-ball pitchers. It’s possible Arrieta might be in that Kershaw-type mold right now, but the rest of the pitchers on the staff have career numbers that don’t match with what is going on this season.
Even if you ignore career numbers, it’s possible you have heard about pitchers inducing weak contact, and perhaps that is part of the reason why the Cubs’ pitchers are so good. Cubs pitchers are among the leaders for lowest average exit velocity. There’s some evidence to suggest that an average low exit velocity limits home runs, but there is little to no relationship between average exit velocity and BABIP. We know exit velocity plays a strong role for hitting outcomes, especially slugging, but there is little to no relationship with the hard, medium, and soft designations. Weak contact can lead to good numbers for the Cubs’ pitchers. Moreover, most of the Cubs staff have above-average FIPs and have collective produced the fourth-best WAR in baseball. However, being recording strong fielding-independent numbers doesn’t necessarily lead to a low collective BABIP — and that’s a big part of what’s allowing the Cubs pitchers to beat their FIP.
So if pitcher skill isn’t lowering BABIP, how about defense? The Cubs have a fantastic defense, with good to great defensive players all over the field. They upgraded to Jason Heyward from Jorge Soler in right field. They made Addison Russell the full-time shortstop over Starlin Castro and put Ben Zobrist at second base. They have deployed Javier Baez all over the infield, and Kris Bryant has taken to the outfield fairly well in addition to his duties at third base. While single-season UZR numbers come with some sample-size problems, it is interesting to note that the Cubs’ UZR of 67 runs above average confirms the eye test and the individual players’ reputations and is about 25 runs ahead of the second-place Giants this season.
Over the last 15 seasons, 29 teams have posted a UZR of at least 50 runs above average, and the average BABIP against for those teams is just .284. Only two teams, the 2006 and 2007 Kansas City Royals, posted BABIPs above .300 in those seasons. Looking back at the UZR and BABIP over the last 15 seasons, a sample that includes 450 teams, the correlation coefficient between the two is -0.56, fairly strong. The graph below shows all of those teams.

With a few weeks of the season left to go, the Cubs’ UZR is the seventh-highest of the past 15 years, and could go higher before the season is out. In an ideal study, we might regress all of the defensive numbers and get three-season sample sizes, but doing that is still going to confirm that this Cubs defense is a very good group. We might try to avoid taking away credit from pitchers, but the Cubs pitchers are good without giving them extra credit for the work of others. Weak contact and low exit velocities might help make the Cubs good pitchers, especially when it comes to limiting home runs and extra-base hits; however, a lot of pitchers give up weak contact and have low exit velocities, and none of them are beating their FIP quite like the Cubs are. None of them have a defense like the Cubs do, and those players deserve a ton of credit for their share of the work.
Craig Edwards can be found on twitter @craigjedwards.
Ben Lindbergh and Rob Arthur had an article earlier this summer on this subject that came to different conclusions.
“That leads to a larger takeaway from our models: Leaguewide, the impact of pitchers’ contact management is more than twice that of defense, which seems to contradict the traditional defense-independent pitching theory that most pitchers have little ability to prevent hits on balls in play. (It’s probably no coincidence that the career leader in Inside Edge’s Soft Contact rate is fabled bat breaker Mariano Rivera.) In other words, much of what appears to be good or bad defense might really be good or bad contact management, which can produce easier (or more difficult) fielding opportunities that make certain fielders look better or worse than they are. In theory, only a Statcast-derived defensive stat could account for this heretofore-camouflaged effect.”
http://fivethirtyeight.com/features/the-cubs-pitchers-are-making-their-own-luck/
Doesn’t really explain Lackey and Hammel, who have exit velocities well above average and are among the leaders in Hard-Hit% yet are still among the league-leaders in lowest BABIPs allowed.
I made a joke on some article about the NL Cy Young that the Cubs defense should be given the trophy. I’m pretty sure at this point, it’s no longer a joke and I believe it for real.
(Okay, maybe not. But holy crap.)
I definitely think it is some combination of pitching, defense, front office/coaching and luck.
I’m not sure if this is a serious statement or not.
And surprise, and fanatical devotion to the Pope.
This article could also be titled “Why Kyle Hendricks does not deserve the NL CY Young Award”
Ditto for Jon Lester.
So the best pitcher on the best team this year is not deserving of the Cy Young award because he limits hard contact and the defense is really good?
Huh, I didn’t know that John Lackey won the Cy Young least year.
Hendricks isn’t even conclusively the best pitcher on his own team, let alone in the National League.
Since when does being the best pitcher on the best team mean you’re the best pitcher in the league or most deserving of the Cy Young? And he’s arguably not the best pitcher on the Cubs anyway.
Rather than singling out Hendricks specifically, I do think this raises a very interesting question: when voting for the Cy Young award, should we dock a pitcher for an excellent defense? In the debate between awarding based on what actually happened and awarding based on our estimation of each individual player’s performance, a lot of people don’t like someone saying that “Pitcher X got lucky on his HR/FB rate and his BABIP” because it is denying a significant part of that player’s agency in the eventual results (regardless of what historical research tells us about likely regression), yet defensive contributions should be less controversial since they affect the player’s statistics while clearly existing outside of that player’s agency. It feels reasonable to say that Pitcher X shouldn’t get extra credit for having a much better defense behind him than Pitcher Y, and therefore attempting to adjust the pitcher’s statistics by the quality of their defense to better approximate the contribution of their own agency would be a more accurate method of determining the “most outstanding” pitching performance that season.
All of the Cubs starters having a significantly lower ERA than FIP along with the quality of the team’s defensive metrics compellingly argues that the Cubs’ defensive contribution to pitching stats is significant, and therefore if you buy into the notion of attempting to isolate the pitcher’s agency, then all of the Cubs’ starters should be docked some amount of their performance when assessing how individually “outstanding” each has been this season.
It’s not so much docking the pitchers for defense, more not giving them extra credit for it. It’s really no different than adjusting for ballpark factors.
“There’s some evidence to suggest that an average low exit velocity limits home runs, but there is little to no relationship between average exit velocity and BABIP. We know exit velocity plays a strong role for hitting outcomes, especially slugging, but there is little to no relationship with the hard, medium, and soft designations.”
I’ve read these two statements multiple times now, then digressed to THT article, and now I’m hella confused. What do you mean regarding hard% / medium% / soft% doesn’t have a relationship with hitting outcomes? Isn’t talking about exit velo and H / M / S % the same thing?
Sorry that was confusing. It’s hard, medium, soft and BABIP where there is little relationship.
Ahhhhh that makes more sense. Thanks Craig, this was a superb piece. Well done.
Actually latest xbabip formula does include hard% as a significant factor.
http://cdn.fangraphs.com/blogs/wp-content/uploads/2015/06/Non_Normalized_BABIP_HH-.png
Trajectory matters a lot more than exit velocity, as a soft line drive has a significantly higher chance of landing for a hit in play than a hard hit fly-ball, admittedly in part because very hard hit fly-balls often land beyond the field of play.
Obviously the contact data explain something and the fielding data explain something but a huge amount is just luck, like the cardinals last year. In the first few weeks in july this year the giants pitchers had better contact data than the cubs and the giants filelding statistics were better than the cubs, but the cubs babip was still more than 30 points lower.
No.
http://www.fangraphs.com/leaders.aspx?pos=all&stats=pit&lg=all&qual=0&type=8&season=2016&month=7&season1=2016&ind=0&team=0,ts&rost=0&age=0&filter=&players=0&sort=11,a
http://www.fangraphs.com/leaders.aspx?pos=all&stats=pit&lg=all&qual=0&type=2&season=2016&month=0&season1=2016&ind=0&team=0,ts&rost=0&age=0&filter=&players=0&sort=17,d
Meant to post July’s batted ball profile
http://www.fangraphs.com/leaders.aspx?pos=all&stats=pit&lg=all&qual=0&type=2&season=2016&month=7&season1=2016&ind=0&team=0,ts&rost=0&age=0&filter=&players=0&sort=17,d
I meant the data through July (the data for the year in July), not the data for July. In the second link you posted, the Cubs have a higher Hard% (30.0% to 29.6%), a higher LD% (20.6%), and a lower IFFB% (32.6×9.3 vs. 35.0×9.6). They are worse than the Giants in all three parameters related to xBABIP (see http://www.fangraphs.com/fantasy/hitter-xbabip-v20-a-long-needed-update/). For that matter, the situation is the same in the July data–there too the Giants’ pitchers are better in all of the stats related to xBABIP. If you think that Soft% is the only statistic which matters for xBABIP, then I suggest that you discuss this matter with the fellows who have worked out the xBABIP formula, because they don’t agree with you.
Sorry you have trouble clearly stating what you mean.
But if you want to talk xBABIP THROUGH July with Alex’s calculator found here : http://www.fangraphs.com/fantasy/the-rotographs-x-stats-omnibus/
Cubs xBABIP .294
Giants xBABIP .297
Now go home and get your shine box!
What kind of a ridiculous claim would it be to just focus on July? What I meant was obvious.
I was talking about through the first few weeks in July (as I wrote above), not the end of July (as you calculated). But since you’ve taken the trouble to calculate the Cubs’ pitchers xBABIP through July, we can go with that, since it makes the same point and since you calculated it yourself you can’t argue with it (I would assume). Do you seriously think that the Cubs defense accounted for anything remotely resembling 40 points of BABIP? And considering that at the end of July there was very little difference in fielding ratings between the Cubs and the Giants, and by your own calculations there was only 3 points xBABIP difference between their pitchers, how do you account for the 30 points difference in their pitchers BABIP if not luck?
Be serious. Look at the team BABIP/UZR graph. See how much of an outlier the Cubs are, even among teams with comparable fielding? You yourself just admitted that the Cubs’ pitchers are only 6 points better then average in terms of lowering BABIP (the league average is 300). Fair enough, move the dot 6 points to the right. It’s still a total outlier, a good 25 points lower than the average for teams with comparable UZRs. That’s luck. Sorry if you don’t like it.
xBABIP, BABIP has an adjusted R-squared = .456
Nonsense will be in may? I think it’s clear.
I spent a few weeks in July, the first (as I wrote above), than at the end of July (as calculated). But since you bothered to calculate a desperate pitcher kBABIP until July, we’re going with it, because it’s the same thing, and it’s just cannot argue with (I assume). Do you really think that their defense has nothing to Little distance from BABIP 40 points. By the end of the day, there is little difference between the Cubs put in and the Giants, and he continued his calculations are only 3 points difference between kBABIP and bowls, how to care for 30 points in BABIP Bowl, if not happiness?
Get real. See the team marketing BABIP/UZR. See how spam neceljeni even between the two teams in terms of Fielding. Just enter the Cubs struggling just 6 points average and better in reducing BABIP (League average is 300). fair, move 6 points on the right side. However, the overall index, well, 25 points below the average for other teams to compare UZRs. This is happiness. I’m sorry if you don’t like it.
jfc just drop it already
Why, because you have no argument and it’s embarrassing to have this pointed out?
1) the cardinals ran a league average .babip last year, saying that the cubs situation is identical is blatant contrivance. 2) comparing the giants defensive contributions to the cubs is also a misnomer seeing as how the cubs grade plus defensively in every position, whereas the giants are running out a well-below average defensive outfield (which the cubs rank 1st in, and aside from the royals, are blowing the entire league out of the water). 3) youve admitted you dont watch the cubs regularly yet you keep relying on the same argument that this full season’s body of work is all just an illusion due to luck and 4) any embarrassment is second-hand.
By jfg logic, having Jason Heyward on your is all that is required to beat your FIP in any given year, regardless that the Cardinals last year were all about LOB%, exemplified by Lackey’s stat line.
This guy says every post about the Cubs he knows stats, and it’s all luck. It’s one thing to say it on August’s piece after 60 games. It’s another thing to say it after 145 games — with the intervening 85 games confirming almost exactly the previous 60 games of data. Baseball Prospectus says this is the best defensive team ever.
http://www.baseballprospectus.com/sortable/index.php?cid=1960534
(1) I wasn’t talking about the Cards xBABIP last year, I was talking about what Craig mentioned (‘When Lindbergh looked at the Cardinals last year, he found the Cardinals were getting considerably better results with runners on base — in which situation most teams actually fare worse’) (2) The Giants’ defense ranked better than the Cubs’ in this year up to the first few weeks in July, but even then the Cubs’ BABIP was way lower, and (3) I’m not claiming the Cubs’ whole season is due to luck, I’m claiming a huge amount of the Cubs low pitchers’ BABIP was due to luck + I don’t see what how I watch games matters. Stats are stats.
the cubs and giants defense rated almost identically in april, the cubs rated higher in may, and more than twice as high in june, and also more than twice as high in july. also, at not point in the season has the giants OF rated well, so where are you pulling this “The Giants’ defense ranked better than the Cubs’ in this year up to the first few weeks in July” from?
Your whining about luck is annoying when its April and May. By September, it’s just pitiful.
The Cubs’ pitchers may luck out for the whole year. The Cardinals’ pitchers lucked out on LOB for the whole year last year–their LOB% last year was 79.4%, their ERA was 2.94 (lower than the Cubs’ pitchers this year of 3.07–Lackey was 2.77, didn’t lower it significantly, so don’t try to claim that he brought something magical to the Cubs this year), it was just luck, this year the Cardinals’ LOB% is 71.8% and their ERA is 4.04.
In retrospect, no one would doubt that the Cardinals’ pitchers just got very lucky last year. All of last year. It just happened. The same thing is going to happen with the Cubs this year. Like the Cards LOB% last year, the Cubs’ BABIP is a statistical outlier which can only be explained by luck–some of it can be explained by the pitchers xBABIP, some can be explained by the fielders’ UZR, but this is less than have the variation.
Let’s renew this discussion in a year, okay? There won’t be anything to argue about then.
Let’s say that in any given year the best team in baseball (talentwise) has a 20% chance of winning the World Series. So if a team is the best team in baseball every single year for five years, their expected number of world championships is one.
That would mean that a team that wins 3 World Series in 5 years has lucked out for a whole 5 year period. Now THAT’S lucky!
MI perhaps, or data, and anything but a great value, as well as with the cardinals explained last year. In July this year, during the first weeks of mugs giants want to work their statistics filelding and the best people, the boy, but the boy more than 30 babip.
But you can’t look at UZR and conclude it’s the fielding rather than the pitching. UZR can’t pull those apart given its input data. Badly hit balls will be easier to field than they appear to UZR.
Exactly. Some guy named MGL had this to say about exactly that back in March:
“Hard ground ball is hit down the third base line. Overall 40% of those plays are made, but we know that not every play has a 40% chance of being caught because we don’t know where the fielder was positioned and we don’t really know the exact characteristics of the ball which greatly affect its chances of being caught: it was hit hard, but how hard? What kind of a bounce did it take? Did it have spin? Was it exactly down the line or 2 feet from the line (they were all classified as being in the same “location”)? We know the runner is fast (let’s say we created a separate bucket for those batted balls with a fast runner at the plate), but exactly how fast was he? Maybe he was a blazer and he beat it out by an eyelash.
“So what does that have to do with whether the fielder caught the ball or not? That should be obvious by now. If the third baseman did not catch the ball, on the average, it should be clear that the ball tended to be one of those balls that were harder to catch than the average ball in that bucket. In other words, the chances that any ball that is caught should or would have been caught by an average fielder is clearly less than 40%. Similarly if a ball was caught, by any fielder, it was more likely to be an easier play than the average ball in that bucket.”
…
“Keep in mind that this problem will be mitigated in large samples but it will never go away. It will always overrate a good performance and underrate a bad one. But, in small samples, like even in one season, it will overrate so-called good fielding performance and underrate bad ones. The better the numbers the more they overstate the actual performance. The same is true for bad numbers. This is why I have been saying for years to regress what you see from UZR or DRS, even if you want to estimate “what happened.” (You would have to regress even more if you want to estimate true fielding talent.)”
https://mglbaseball.com/2016/03/04/how-important-is-bayes-in-advanced-defensive-metrics/
You can’t look at UZR and conclude exactly how much is the fielding rather than the pitching, but you definitely can say that a pitcher on Team X benefited more from his defense than a pitcher on Team Y did. Not only do the Cubs have a gigantic lead in UZR over all other teams, but all five of their starting pitchers are running a significantly lower ERA than FIP. Clearly that defense is having a substantially positive effect on those pitchers’ statistics.
This is all especially unusual as they have shifted the fewest times of any MLB team.
They do start guys at different positions depending on the starter…
They shift a ton, they just don’t overshift a whole lot. Most of their “shifts” are on the order of 10-20 feet, not what most people would call a “shift”, hence how they fly under the radar despite their next level positioning.
Part of me wishes Clayton Kershaw had stayed healthy all year–there would be no NL Cy Young discussion (we’d then be having the “can a pitcher win the MVP” discussion).
But the other part of me enjoys the chaos of these discussions where stuff like BABIP and team defense and exit velocity all make their way into the fray.
But the “can a pitcher win MVP” discussion wouldn’t be what it normally is because he’s won one and because he was so dominant that it’d be difficult to argue with
And Kershaw still has a higher WAR (Fangraphs) than everyone but Syndergaard and Fernandez.
One thing you don’t seem to consider is outs on the bases. The Cubs have had some terrible games allowing runners around and some great games with catching stealers — but the thing that has stuck out the most to me is catcher pickoffs (on non-steals). Sometimes it seems like they average more than one pick per week from the catchers (Contreras and Ross especially). Do those outs on the bases count toward LOB%? Also you don’t discuss any sort of correlation between OBP/WHIP allowed and LOB%, I would certainly expect there to be a relationship there in the same way that reducing an already extremely low wOBA would have exponential effects on the corresponding runs scored.
http://www.fangraphs.com/library/pitching/lob/
Given how LOB% is calculated, outs on the bases definitely still count towards LOB%. Anyone who reaches base via a hit, walk, or HBP (though not reaching on an error) but doesn’t score counts towards LOB%. Still, it doesn’t look like that’s the reason either, at least according to the DRS stats.
http://www.fangraphs.com/leaders.aspx?pos=all&stats=fld&lg=all&qual=0&type=1&season=2016&month=0&season1=2016&ind=0&team=0,ts&rost=0&age=0&filter=&players=0&sort=7,d
Ross and Contreras are 3rd and 4th at rSB, which would account for pickoffs as well as caught stealings, but Montero is worst in the league, so the cubs are only 8th overall.
The only big outlier according to DRS is at rPM, which is defined as “Plus Minus Runs Saved evaluates the fielder’s range and ability to convert a batted ball to an out.” which doesn’t really help elucidate anything more than is already discussed in the article.
I’ve always found it interesting that LOB% is strictly treated as “sequencing”. There’s a reason all the teams in the “FIP Beaters” table have both a high strand rate and a low BABIP.
If you look at all of the team pitching seasons from 2002 to now, the correlation of BABIP and LOB% is nearly 0.6 (negative, obviously, low BABIP -> high LOB%). I’ve always thought LOB% should be related to BABIP and K%, since those are the two ways to get outs and strand runners as a result.
I should say two *primary* ways, obviously there’s pickoffs, TOOTBLANs, etc., but in-play outs and strikeouts are the two most common ways.
Tom Tango, MVP & Cy Young.
No one has yet shown how to be FIP better than Tango, he’d obviously know how a low FIP prevents runs, but also knows what else is needed to cover remaining issues.