The St. Louis Cardinals hit .330/.402/.463 with runners in scoring position during the 2013 regular season.
Snarkiness about clutch aside, let’s give the Cardinals their due. The .330 average was 48 points better than that of the second-place Tigers. It wasn’t just empty batting average, either. In OBP, the Cards outpaced their nearest competitor (the Reds) by 49 points in RISP situations. Take another 49-point tumble and you end up somewhere between the 27th-place Pirates (.316) and the 28th-place Mariners (.310).
The .330/.402/.463 line isn’t completely out of left field. Overall, the Cards did hit .269 (fourth place)/.332 (third)/.401 (12th), so we are talking about one of the better offenses in the game, but when there were runners in scoring position, the Cardinals suddenly found 132 points worth of OPS. Even allowing for some sampling issues (in a RISP situation, they’d be more likely to pinch hit for a pitcher), that’s still a fantastic jump. Is this magic?
If you stare at the Cardinals’ team splits for the year, it doesn’t take long to see the number .377 listed under BABIP for hitters. Unlike for pitchers, whom we generally believe will regress very heavily toward a mean of .300 or so, hitter BABIPs stabilize more quickly, so we can believe them. Still, .377 seems like a lot of seeing-eye singles. Perhaps they had a bit of luck there?
Of course, this is where we start to hear the arguments for Clutch and Heart. (A reminder that if you see someone clutching their heart, it’s most likely a heart attack.) We know. The Cardinals have that something special. In addition to having the Best Fans in Baseball™ and getting to elect the Pope, the Cardinals also have magic elves that get them base hits in key situations.
Looking at this from a more rational point of view, there are a couple of possible explanations for this statistical anomaly, none of which are mutually exclusive.
- There is something that the Cardinals do all the time that plays up particularly well in situations in which there are runners in scoring position (RISP).
- The Cardinals change their approach in RISP situations to something that works better in general.
- Some combination of 1 and 2, where there is some approach that works really well but only in RISP situations, and they’ve figured out what it is, so when those situations happen, they switch to that.
- Magic elves.
I took a look and concluded that I believe Cardinal magic is real. There just isn’t anything magic about it.
Warning! Gory Mathematical Details Ahead!
Let’s first take the hypothesis that there is something that is part of the way that Cardinals hitters perform in general that plays up better when there are runners in scoring position. I took all events from 2003-2012 and coded whether there was a runner in scoring position (either on second or third, or both). I then calculated several stats for each player, including rates of various outcomes per PA (K%, BB%, etc.), batted ball profile (GB per ball in play, etc.), and pitch/swing stats (pitches per PA, contact %, etc.).
I created a series of moderator analyses (for the initiated, using Baron and Kenny’s model). The idea of a moderator is that it is a variable that changes the relationship between two other variables when it is present. I started by looking at hits on balls in play (BABIP) and coded each plate appearance as a hit on a ball in play (single, double, or triple) or an out. For obvious reasons, walks, strikeouts, HBP, and home runs were politely excused from these regressions.
In a standard binary logit regression, we might look at whether contact percentage for each batter had any impact on the odds that an individual ball in play would end up as a hit. But here we’re more interested in whether there’s something special about RISP situations that changes that relationship. Perhaps good contact skills predict a higher batter BABIP, except in RISP situations? Particularly in RISP situations? It doesn’t matter that it’s a RISP situation? Mechanically, I ran a binary logistic regression with three variables entered as predictors: each one of the series of stats calculated above (let’s use contact rate for the moment), the binary indicator of whether this was a RISP situation, and then those two multiplied together. That last term—the interaction term—is the key in a moderator analysis. If it is significant, it means that our moderator (the fact that it’s a RISP situation) actually changes the relationship between contact rate and the odds of a ball going for a hit.
For BABIP, there were very few significant effects, and when there were significant findings, the pattern was that a variable that was very correlated with BABIP, such as line drive rate, was moderated only slightly. These findings held whether I ran RISP vs. all other situations or limited the sample to cases where there was a runner on first only (to control for the stretch vs. windup effect). So, there is evidence that being in an RISP situation has some effect, but the effect sizes are very minor. You can rewrite that paragraph in exactly the same way for modeling whether the outcome was a strikeout, walk, or home run. There are, of course, relationships between certain pairs of skills (guys who hit a lot of HR also strikeout a lot), and being in an RISP situation doesn’t change those relationships all that much.
We can rule out the idea that the Cardinals might have stockpiled hitters who happen to have one particular skill (at least among the ones that I tested) that is suddenly activated in RISP situations. That is to say that guys who hit ground balls or take a lot of pitches don’t get much better (or worse) in RISP situations at getting hits on balls in play or striking out or walking or hitting home runs. Taking a lot of pitches has its own advantages and disadvantages, but no more or less so in a RISP situation. But with that said, the Cardinals did have one thing about them that was built for having a higher BABIP.
The Cardinals actually ranked fifth among teams in baseball with a 1.43 GB/FB ratio, and became slightly more ground ball happy with runners in scoring position. Here’s a table showing the hitters who had more than 100 PA with RISP (as well as overall team stats).
Player |
GB/FB Overall |
GB/FB RISP |
0.86 |
0.78 |
|
1.14 |
0.87 |
|
1.60 |
1.82 |
|
2.21 |
2.07 |
|
2.30 |
3.26 |
|
1.36 |
1.97 |
|
1.16 |
1.65 |
|
1.24 |
1.26 |
|
All Cardinals |
1.43 |
1.58 |
All MLB Hitters |
1.30 |
1.35 |
Ground balls are more likely than fly balls (that stay in the park) to go for hits. The hits that they produce are often singles (compared to doubles and triples off the wall) and it’s hard to hit a ground ball home run, but fly balls are also more likely to be caught. Here we see that the Cardinals generally maintain their ground ball happy ways (and some get more so!) even in RISP situations, which probably helps them some with BABIP.
So, we move on to Hypothesis 2, that the Cardinal hitters do things differently in RISP situations than they do in other situations, and that the things that they do result in better outcomes. This one is easier to diagnose. One thing that the Cardinals can boast is that they had the highest line-drive rate with runners in scoring position (25.3 percent) and line drives fall for hits around 70 percent of the time. That probably helps explain their high BABIP. Of course, there’s a problem: line-drive rate is not a quick stat to stabilize. Individual players need about 600 balls in play before line-drive rate becomes reliable, and few hitters put 600 balls in play in a year overall, much less in RISP situations. Still, the Cardinals had more than 1600 PAs as a team with RISP and more than a thousand balls in play.
Let’s take a closer look again at the Cardinals who had at least 100 PA with runners in scoring position.
Player |
LD% Overall |
LD% RISP |
Difference |
Carlos Beltran |
23.9% |
26.1% |
+2.2% |
Matt Carpenter |
27.3% |
32.4% |
+5.1% |
Allen Craig |
26.9% |
34.2% |
+7.3% |
Jon Jay |
26.7% |
26.5% |
-0.2% |
David Freese |
20.9% |
19.0% |
-1.9% |
Matt Holliday |
20.8% |
20.4% |
-0.4% |
Pete Kozma |
22.8% |
22.5% |
-0.3% |
Yadier Molina |
24.3% |
26.1% |
+1.8% |
All Cardinals |
23.2% |
25.3% |
+2.1% |
All MLB Hitters |
21.2% |
21.1% |
-0.1% |
It’s hard to say that this is conclusive proof that the Cardinals developed some specific talent for hitting line drives with runners at second and third. The team overall did show a bump, and a few key guys did as well, but is that cause, effect, or small sample size? Even though this isn’t direct proof, there is other evidence that they may have been doing something different.
Let’s look at strikeout rates.
Player |
K% Overall |
K% RISP |
Difference |
Carlos Beltran |
15.0% |
12.7% |
-2.3% |
Matt Carpenter |
13.7% |
12.4% |
-1.3% |
Allen Craig |
17.8% |
9.9% |
-7.9% |
Jon Jay |
16.4% |
13.6% |
-2.8% |
David Freese |
20.3% |
21.2% |
+0.9% |
Matt Holliday |
14.3% |
12.5% |
-1.8% |
Pete Kozma |
20.3% |
19.0% |
-1.3% |
Yadier Molina |
10.2% |
6.9% |
-3.3% |
All Cardinals |
17.9% |
15.8% |
-2.1% |
All MLB Hitters |
19.9% |
19.4% |
-0.5% |
Now, strikeout rates are nice because they need a mere 60 PA to stabilize, so we can have some confidence in these split numbers. In general, we know that strikeouts are associated with contact skills. The better you are at hitting the ball, the less you strike out. We see that most of the Cardinals are outperforming the league in cutting down on their strikeout totals in RISP situations. This is a well-known strategy, called “shortening your swing.” For the record, the Cardinals also increased their walk totals in RISP situations, by about 2.8 percent, but that matched the league’s overall pattern. Pitchers, in general, seem to get more careful when they have less margin for error, and potentially have first base open.
I think we have evidence that the Cardinals are clearly taking a different approach during their RISP plate appearances. And yes, it’s circumstantial evidence, but maybe the bump up in line drives is a result. Maybe some of that is luck, but if you show better plate discipline and aren’t trying to hit everything out of the park, maybe you’ve got a better chance of finding a good pitch to barrel up.
And for what it’s worth, the ground ball tendencies actually work well within RISP situations. The ground balls might not be more effective at getting through, but in an RISP situation, there’s a certain bonus to hitting a lot of singles. We often think of a single as just being a single in terms of run values, but in an RISP situation, things are a bit different. The runners are, by definition, ready to score. Let’s take a situation where there are runners at second and third. A single knocks in that runner at third and has maybe an even-up chance of knocking in the runner from second (at least it gets him to third). A home run would be nice (three runs!) and three runs is better than 1.5, but if you cut down on your swing, while you give up some chance at that home run, you can perhaps buy some extra chances at a single through the hole. With the bases empty, that tradeoff might not be worth as much, but with the value of a single being so high in this situation, you don’t have to gain too much chance of a single before the tradeoff starts to make sense.
Yes, maybe some of that Cardinal magic this year was magic elves, but I’d put forth that not all of their good fortune with RISP was entirely made of lucky bounces.
Re-thinking clutch
I’d argue that what we might have here is a lesson in what we’ve commonly referred to as clutch. The dominant way of thinking about clutch has been based on the idea of leverage. Higher leverage, so goes the argument, means more pressure, and the pressure makes some guys crack while others do not. In general, studies using this framework have found little support that the signal is much greater than the noise that surrounds it. But the point is that we’ve thought of clutch in reactive terms. Players have to fight off their own nerves imposed by the situation.
Instead, the Cardinal example gives us a different way to think about clutch. Instead of fighting something back, the Cardinals appear to execute a strategy, whether coordinated/pre-meditated or not, that is better suited to the needs of the situation. Not everybody commonly does this (the league-wide numbers show that clearly), and maybe it’s that hitters don’t think to do this or that hitters don’t want to do this. It takes initiative to do something that you don’t normally do, and if there’s something that the past few years of “clutch” research shows, it’s that most hitters seem to do what they would normally do in the clutch and that it’s all too small a sample size to really draw any conclusions.
I’d fully grant that this is all a speculative conclusion. Maybe the fact that all these red birds flocked together is a coincidence and that the Cardinals are just a lucky team. Then again, maybe it’s something that they specifically worked on. But it’s food for thought. What if the Cardinals, as a team, have actively been trying to do something new recently? Then the magic of their clutch hitting wouldn’t be magic, so much as good solid logic and a good plan that’s well-executed. Nothing magic there. If it’s a team-level plan, it bunches enough signal together to where we can detect it.
Or maybe it is all just elves.
Thank you for reading
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Are there hidden costs to that? For example, does shortening their swing and avoiding strikeouts result in reduced pitches per plate appearance? That is likely a good trade in a RISP situation, but applied all the time, it would reduce opposing pitchers' fatigue.
Is the effect muted during double-play situations, vs. other RISP situations? If the Cardinals are warding off strikeouts by slapping ground balls, that strategy is less appealing with 0/1 outs and a runner on 1st. (Obvious warning: Even smaller sample size.)
In a bases empty situation, a single doesn't have a lot of value, compared to a HR. In RISP situations, it has more value.
Only other thought was that there might be some evidence that in higher leverage situations you see more righties facing righties and lefties facing lefties due to bullpen platoon match ups. If so, I know the Cards had a very righty heavy lineup for most of the year, and happened to hit righties fairly well. Maybe that contributes to the edge.