Tag Archives: rbi

The Nine Best Seasons Under 70 RBI

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By now I’m sure you’ve seen our series explaining why RBI is not a good statistic for measuring individual value. The reasons are simple. RBI is simply too dependent on the quality of the team around you to be a good measure of individual value because the number of baserunners, location of baserunners, and number of outs are outside of a player’s control. To catch you up, we’ve already seen:

Now, let’s turn the question on its head. Below you’ll find the best seasons since 1920 (when RBI became an official stat) in which a player had fewer than 70 RBI while also having 600 or more plate appearances. In other words, these are players who had a full season of at bats, played great, and didn’t have many RBI. The ranking uses wRC+ (what’s wRC+?) which is an offensive rate statistic that compares a player to league average and park, meaning that you can use it to compare across eras. 100 is average and every number above or below is a percent better or worse than league average.

Rank Season Name Team PA RBI AVG OBP SLG wRC+
9 1938 Arky Vaughan Pirates 650 68 0.322 0.433 0.444 150
8 1993 Rickey Henderson – – – 610 59 0.289 0.432 0.474 151
7 1968 Pete Rose Reds 692 49 0.335 0.391 0.470 151
6 1975 Ken Singleton Orioles 714 55 0.300 0.415 0.454 152
5 1987 Tony Gwynn Padres 680 54 0.370 0.447 0.511 153
4 1974 Rod Carew Twins 690 55 0.364 0.433 0.446 153
3 1968 Jimmy Wynn Astros 646 67 0.269 0.376 0.474 159
2 1974 Joe Morgan Reds 641 67 0.293 0.427 0.494 162
1 1988 Wade Boggs Red Sox 719 58 0.366 0.476 0.490 167

What you can see from this list is that these are excellent seasons and none of them gathered more than 68 RBI. Let’s put this in the modern context. In 2012, only 8 players had a wRC+ of 150 or better. Cano, Encarnacion, Fielder, McCutchen, Braun, Posey, Cabrera, and Trout. On the other hand, 80 players had 70 or more RBI in 2012. Among them were Alexei Ramirez who had 73 RBI and a 71 wRC+ and Delmon Young who had 74 RBI and a 89 wRC+.

Usually big RBI numbers and high wRC+ go hand in hand, but there is a lot of variation that obscures the results. Good hitters usually have a lot of RBI, but not always. You’ve seen it in our previous posts on the subject and now you can see that great seasons don’t guarantee you anything in terms of RBI.

RBI isn’t the worst statistic in the world, but it just isn’t a good way to measure individual value when you consider how some players can have 100 RBI in a year and be 25% below average and some can have fewer than 70 RBI and be 50% better than league average. These numbers don’t even out over an entire career and you can’t use RBI to compare two players.

There isn’t a lot RBI can tell you about individual players. You can be good and not have them, you can be bad and have them, and this isn’t about small samples. RBI describe what happened on the field, but they are a blunt and unhelpful tool in measuring individuals. It’s time to move forward and stat lining up our valuations with better measures like wOBA, wRC+, and wRAA. If you use RBI to measure players, you going to end up thinking Ruben Sierra’s 1993 season in which he had 101 RBI is better than Rickey Henderson’s 1993 in which he had 59 RBI when in reality Sierra was 20% below average and Henderson was 50% below average. That’s way too big a mistake to make when there are much better alternatives.

RBI Are Misleading Even Over Entire Careers

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In keeping with the recent theme, I’d like to take another look at RBI as a statistic. Recently, I’ve shown you why RBI can be misleading when comparing two players’ value and why having a lot of RBI doesn’t necessarily mean you had a good season. To catch up on these and other similar posts about baseball statistics, check out our new Stat Primer page.

Today, I’m turning my attention to RBI over entire careers. You’ve seen already that RBI aren’t a good way to measure players in individual seasons, but we’ve yet to see how well they do at explaining value in very large samples. The answer is not much better.

To evaluate this, I took every qualifying player from 1920 (when RBI became and official stat) to 2013 (2,917 in all) and calculated their career RBI rate by simply taking their RBI/Plate Appearances. This will allow us to control for how often each player came to the plate so Babe Ruth’s 10,000 PA can go up against Hank Aaron’s nearly 14,000. Next, I compared that RBI Rate to wRC+ (what’s wRC+?) which is a statistic that compares offensive value to league average while controlling for park effects. The simple explanation is that wRC+ is a rate statistic that controls for league average, meaning that a 110 wRC+ means the same thing in 1930 as it does in 1980. League average is 100 and every point above or below is a percent better or worse than league average in that era.

The results aren’t great for RBI as an individual statistic. Overall, the adjusted R squared is .4766 which means that about 48% of the variation in wRC+ can be explained by variation in RBI Rate. Put simply, players who have more RBI per PA are better hitters on average than those with fewer, but there is a lot of variation that isn’t explained by RBI Rate meaning you can’t just look at RBI and know how good a player was.


What this graph is showing you is quite striking. First, notice how many players have similar RBI Rates who have wildly different wRC+ and second notice how players with the same wRC+ have wildly different RBI Rates. Generally more RBI mean you’re better, but there’s a lot left unexplained by this stat.

Like I’ve said before, RBI isn’t a made up stat that is useless like wins for a pitcher because RBI reflects a real event on the field and is critical for score keeping. The problem with RBI is that it is too dependent on context and the team around you. Two players who are equally good on offense can have very different RBI Rates because they have a different number of opportunities to drive in runs. Similarly, players who drive in the same number of runs may be much different offensive players in terms of quality.

Even if you’re someone who thinks clutch hitting is a predictive skill, surely you can recognize that RBI is extremely context dependent. Your RBI total depends on how good you are, but also how many runners are on base, how many outs there are, and where the runners are positioned on the bases – all of which you have no control over as a hitter.

I’m on the front lines of the #KillTheWin movement, but I don’t think we should kill the RBI. The RBI just needs to be put in proper context and understood as a descriptive stat and not a measure of player value. Miguel Cabrera gets a lot of RBI, partially because he’s awesome, but also because his team gets on base in front of him all the time. Driving in runs is an important part of winning, it just isn’t an individual statistic. It’s a team statistic and we should view it as such.

You’ve seen that RBI can mislead you when comparing two players, that bad players can have a lot of RBI, and now you’ve seen that this isn’t something that evens out over time. RBI is simply not a good way to measure individual value when it can tell you the wrong thing this much of the time. There are better ways to measure the same concepts like wOBA, wRC+, and wRAA. Feel free to click on the links to learn more and check back for more on why you should put less stock in RBI.

The Nine Worst 100 RBI Seasons in MLB History

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Yesterday we took a look at a case study in RBI to help explain why it’s a misleading statistic. The idea here is that RBI is very dependent on your team and the context you’re in. Two identical hitters will accumulate much different RBI totals depending on how many runners on base ahead of them and which bases those runners occupy. You can read all about it here.

Today, I’d like to start highlighting some broader evidence of the problems with RBI as a stat. You’ve already seen how a better season can result in fewer RBI depending on how the team around you performs, now let’s take a look at The Nine Worst 100 RBI Seasons in MLB History. This list is meant to show you that you can have a very poor season and still accumulate 100 RBI, which is often considered a magic number by people who value RBI. The phrase “100 RBI guy” is something you might here an analyst like John Kruk say when commenting on a player’s value. I’m here to show you that 100 RBI does not necessarily mean the player had a very good season.

Below, we have The Nine worst seasons by wRC+ since 1901 in which the player drove in 100 or more runs. wRC+ is a statistic that measures how a player stacks up to other players in the league and it factors in park effects. It’s easy to interpret the number. A wRC+ of 100 is league average and every point above 100 is a percent better than average a percent below average is a 99 wRC+. For example, an 85 wRC+ is a player who is 15% worse than a league average player. 115 wRC+ is 15% better than league average. You can read all about wRC+ here.

Rank Season Name Team PA RBI AVG OBP SLG wRC+
9 1927 Glenn Wright Pirates 626 105 0.281 0.328 0.388 86
8 2006 Jeff Francoeur Braves 686 103 0.260 0.293 0.449 84
7 1983 Tony Armas Red Sox 613 107 0.218 0.254 0.453 84
6 1934 Ray Pepper Browns 598 101 0.298 0.333 0.399 82
5 1990 Joe Carter Padres 697 115 0.232 0.290 0.391 80
4 1993 Ruben Sierra Athletics 692 101 0.233 0.288 0.390 79
3 1999 Vinny Castilla Rockies 674 102 0.275 0.331 0.478 78
2 2004 Tony Batista Expos 650 110 0.241 0.272 0.455 77
1 1997 Joe Carter Blue Jays 668 102 0.234 0.284 0.399 72

What you have here is a list of players who are “100 RBI guys” who were substantially worse than league average. Perhaps some comparisons might be help. Let’s find a couple of current MLB players who slot in around 70-85 wRC+. Brendan Ryan has a career 72 wRC+. Jason Nix is at 72. Ramon Santiago is 75. Willie Bloomquist is 78. Ruben Tejada is 83. I’m not saying any of the guys on this list are bad players, I’m saying they all had bad seasons in which they still had 100 or more RBI. They guys had Ramon Santiago seasons at the plate and drove in over 100 runs.

Do you really want to place so much stock in a statistic that says a guy who hits like Brendan Ryan is among the league’s best hitters? I don’t. RBI is very much a team dependent statistic and we shouldn’t use it to value individual players. Players can’t control the situations you put them into, they can only control what they do in those situations. As seen here, even players who don’t do very well can still add RBI to their resumes if they are put into situations with many runners on base.

RBI Is A Misleading Statistic: A Case Study

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One of our missions here at New English D is to help popularize sabermetric concepts and statistics and diminish the use of certain traditional stats that are very misleading. If you’re a return reader, you’ve no doubt seen our series about the pitcher win:

I encourage you to read those posts if you haven’t already, but I’m confident in the case I’ve laid out. Wins aren’t a good way to measure pitchers’ performance and I’ll let those five links stand on their own. Today, I’d like to move forward and pick up the mantle with another statistic that is very misleading based on how it is currently used: Runs Batted In (RBI).

I’ll have a series of posts on the subject, but I’m going to start with a case study in order to explain the theory. RBI are a bad statistic because they are a misleading measure of value. Most people consider RBI to be really important because “driving in runs” is critical to success, but RBI is very much dependent on the performance of the other players on your team. A very good hitter on a bad team will have fewer RBI than a good hitter on a good team because even if they perform in an identical manner, the first hitter will have fewer chances to drive in runners. Even if they have the same average, on base, and slugging percentages overall and with runners on and with runners in scoring position. The raw number RBI is a blunt tool to measure the ability to drive in runs.

Factors that determine how many RBI you have outside of your control are the number and position of runners on base for you, the number of outs when you come to the plate with men on base, and the quality of the baserunners. If you get a hit with runners in scoring position 40% of the time (a great number) but there are just 100 runners on base for you during a season, you will get no more than 40 RBI. If you get a hit 40% of the time and have 400 runners on base for you during a season, you could have 100 RBI. That’s a big difference even if you perform in the same way.

I’m not making the case here that RBI is completely meaningless and that hitting with runners on base is exactly the same as hitting with the bases empty, but simply that RBI as a counting stat is very misleading. Even if you think the best hitters are the guys who get timely hits and can turn it up in the clutch, you surely can appreciate that certain guys have different opportunities to drive in runs. RBI is very dependent on context and that means it’s not a very good way to measure individual players.

Allow me to demonstrate with a simple case study. Let’s start with comparing two seasons in which the following two players both played the same number of games.


As you can see, Player A leads in average, OBP, and wOBA (what’s wOBA?) and is just a but behind in slugging. In wRC+, Player A leads 177 to 166 over Player B. If we take a look at BB% and K%, Player A looks much better.


All in all, Player A is the better player. We’ve looked at all of their rate stats and we’ve looked at wRC+ which controls for league average and park effect. It’s hard to argue that Player B is better. I couldn’t make a case to that effect.

Here’s the big reveal which some of you have probably figured out. Player A is Miguel Cabrera in 2011, Player B is Miguel Cabrera in 2012. This is the same player during two different seasons. In 2011, when Cabrera was clearly the better player, he had 105 RBI. In 2012, when he was worse, he drove in 139. Everything tells us he was better in 2011 except RBI. That should make use skeptical. It’s even more of a problem when you consider his situational hitting.

The graphs below are on identical scales:


Cabrera was better in 2011 in every situation and by each statistic except for his average (very close) and slugging percentage with no one on base. Which tells you nothing about how well he drives in runs. If you look at the HR distribution it tells you the same story.

HRs 2011 2012
Bases Empty 14 27
Men on Base 16 17
Men in Scoring 10 9

We can give him credit for those solo HR RBI from 2012, so let’s just lop 13 off the top. That still leaves 2012 Cabrera with 21 more RBI than 2011 Cabrera. Cabrera had a better season in 2011, but he had fewer RBI than in 2012. Most of this can simply be explained by the Tigers’ team OBP in the two seasons and where he hit in the lineup. If you subtract out Cabrera the Tigers got on base about 32% of the time in 2011 and 32.4% of the time in 2012 while Cabrera got to the plate a little less often because he hit 4th instead of 3rd. So there are more baserunners in general in 2012, but we can break this down even further.

In sum, Cabrera actually had more runners on base for him in 2011 than in 2012 but that doesn’t really tell the whole story. Let’s break it down by the number of baserunners on each base when he came to the plate:

2011 2012
Runner on 1B 235 212
Runner on 2B 150 146
Runner on 3B 74 86

This should tell you the story even better. Cabrera had more baserunners in 2011, but the baserunners in 2012 were more heavily slanted toward scoring position. Cabrera had more runners closer to the plate so it’s easier to drive them in.

I intentionally chose Cabrera for this example because it strips away the idea that a given player just “has a knack” for driving in runs. Cabrera is an “RBI guy” if you subscribe to that idea. Miguel Cabrera had a better season in 2011 than 2012 when you break it down overall and in contextual situations. The only thing that helped 2012 Cabrera accumulate more RBI is that he had more runners on base closer to home when he got there. He played no role in getting those runners on base or closer to home, but he was able to more easily drive them and get credit in the RBI column. This is also isn’t as simple as converting RBI into a simple rate stat because where the baserunners are located and how many outs there are matter too, not just the number of situations.

This is the first step in a longer conversation but the takeaway point here is that RBI is stat that depends a lot on the team around you. Cabrera can’t control how many runners get on base and where they are on the bases when he comes to the plate. We shouldn’t judge a player for where he hits in the lineup and how the rest of the hitters on the team perform. It’s important to hit well with runners on base. I personally think we overvalue that skill over the ability to hit well in general, but I’ll leave that alone for now. Can we at least agree that a player who hits better with runners in scoring position and overall should be considered the better hitter? If that’s the case, then RBI is misleading you as an individual statistic. It’s that simple. I’m going to start laying out more evidence over the next couple weeks so stay tuned, but I’ll leave with this.

RBI is a descriptive statistic. It tells you who was at bat when a run scored and is critical to keeping track of a game in the box score. That’s why it was invented in the 1920s. You want to be able to scan a scorecard and recreate the game. RBI has a place in baseball, but only as a descriptive measure, not as a measure of value. Yet the RBI is still critical to MVP voting, arbitration salaries, and overall financial health of the players. They are judged by a statistic that doesn’t measure individual value and it is bad for their psyches. Players should focus on stats they can control and RBI isn’t one of those. It doesn’t measure individual value because as you can seen, in this very controlled example, RBI is misleading you.

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