Who is Poised to Hit in the Postseason?

There are a several reasons why a hitter’s postseason performance can differ from their season long track record. Of course the small sample size of any 10 to 20 game stretch can generate random results around a player’s “talent level”. Perhaps the pressure of the postseason effects each player in a different way, inhibiting the performance of some, more than others. But there’s an additional factor that might contribute to a hitter’s postseason batting performance—one which can be quantified and may even have some predictive value. It starts with the question, “what’s different about the postseason” and “how does each hitter perform in the postseason environment?” One of the biggest differences about the postseason is the quality of pitching. Better pitchers take the mound in the postseason for two reasons. Playoffs teams simply have better than league average pitching, which is one of the reasons they reach the postseason. In addition, the layout of the postseason schedule allows managers to deploy their pitching very differently than the 162-game regular season. Fifth starters are dropped from the rotation. Fourth starters are used sparingly. Closers are often brought into the game in the 8th inning and top relievers are asked to pitch back-to-back-to-back days. A good example is the way in which the Yankees deployed their pitching in the 2009 postseason, on their way to a World Championship. The Yankees top 3 starting pitchers that year—Sabathia, Burnett, and Pettitte—logged 61% of the team’s regular season starts, but 100% of their postseason starts. Adding in their top two relief pitchers (Mariano Rivera and Phil Hughes) in 2009, their top 5 pitchers combined to register 54% of the team’s regular season innings, but 81% of the postseason innings. (The same is not true of hitters. The manager has virtually no flexibility to deploy batters more strategically. A top hitter will log 11% (give or take) of a team’s regular season plate appearances and do the same in the postseason.)

I analyzed the distribution of pitching over a 3-year period, with the ultimate goal of quantifying who pitches—or more accurately, what quality level pitches—in the postseason. I limited my study to starting pitchers, classifying them into 5 tiers (quintiles) of quality. Those which had the lowest opponent OPS (we’ll call it OPSa for OPS against), were in the top quintile, representing the top 20% of starting pitchers. The next 20% in OPSa were consider the 2nd quintile and so on, with the worst 20% representing the 5th quintile. The top pitchers (Q1 on the graph below) averaged a .612 OPSa, the second best quintile averaged .676 OPSa and the 5th (worst) quintile averaged .854 OPSa—that’s right, the worst 20% of starting pitchers logged an opponent OPS over .850. I controlled for the lefty-righty factor by defining a pitcher’s quintile against LHH and RHH, separately. For example, it’s not enough to say that David Price is a top quintile pitcher. We need to distinguish between his performance vs. LHH (top quintile in 2011) and vs. RHH (2nd quintile in 2011). Below is a graph that depicts the way in which a pitcher’s OPSa differs for each quintile.

I then turned my attention to postseason starting pitchers to determine how many innings came from each of the five quintiles. Over the three-year period examined, about 37% of the postseason games started came from the top quintile and another 28% came from the 2nd quintile, with only 7% coming from the worst quintile. In other words, nearly 2/3 of all postseason starts came from the top 40% of starting pitchers. News flash—the pitching is better in the postseason. We knew that, but now I’ve quantified it. If we added relievers to our analysis, I would expect we would see an even greater quality skew in the postseason as managers opportunistically find a way to put their best relievers on the mound in the many high leverage situations they face.

Now that we’ve established who pitches in the postseason, let’s turn our attention back to the question I posed—which hitters are likely to be successful in the postseason. To answer this question, I measured how each hitter fared against the 5 quality quintiles of pitchers, then translated that performance into the postseason, based on the different mix of pitchers. Some hitters do proportionately well against each quality level of pitching, others feast on poor pitching, while being stifled by top pitching—we’ll call them the “Exploiters”, because they exploit weak pitching. Finally, there are hitters who hit disproportionately well against top pitching, but only a little better against weak pitching—we’ll call them the “Money Players.” The graph below overlays the Money Players and Exploiters on the graph with the MLB average. The line for the Exploiters is steeper, while the line for the Money Players is flatter than the league average.

The data for two current Yankees makes them prime examples of the two types of hitters. Derek Jeter’s hitting pattern tends to follow the profile of the Money Player. He has a lot of success against the best pitchers and hits only marginally better against the weakest pitchers. On the other hand, Alex Rodriguez performance against various types of pitching resembles the Exploiter. A-rod tends to suffer against top pitching, while seriously outperforming the MLB average against weak pitching. Of course this is all relative, because he is a better than league-average hitter, so let me put this in perspective. A-Rod out hits the league average against top pitching by about 15%, but he beats the league average for the worst pitching by about 35%. Think of it this way: If all of MLB’s pitching was the top 2 quintiles—in other words, the bottom 60% of starting pitching evaporated—Alex might not be a star. Conversely, if that scenario played out, I would expect Jeter to be even more of a hitting star than he is today.

In fact, the scenario I just described—a league dominated by the top 2 tiers of pitching—sounds a lot like the league we call the playoffs. By profiling each hitter against different quality levels of pitching, we can create an expectation about how they might perform in the postseason. Of course in the short run, with a small sample size of any one playoff year, the results can vary widely, nor does this approach directly consider a player’s “makeup” or inform us as to how he deals with high pressure situations. Nonetheless, since pitching is better in October, we should expect every hitter to have some degradation over their regular season hitting performance. (Remember, 65% of postseason starting pitching comes from the best two quintiles of pitchers and only 7% of from the worst (5th) quintile.) But simply put, a player who hits well against really good pitching—the Money Players, like Derek Jeter—should perform relatively better than other players in the postseason. Conversely, players who struggle against top pitching—the Exploiters, like Alex Rodriguez—should perform relatively worse in the postseason.

Using this analysis, let’s project both Jeter’s and A-Rod’s postseason performance. They currently have nearly an identical OPS for this season—.800. Based on our analysis I expect Jeter would bat .775 in the postseason, while A-Rod would hit .740. In other words, Jeter would degrade only 25 percentage points from his regular season performance, but A-Rod would decline 60 points. This is certainly not a fool proof projection framework, but it is another way to evaluate a player’s likelihood of performing in the postseason, by basing it on how he fares against different quality levels of pitching, acknowledging that he will see mostly the best pitchers in October. As we get into the playoffs, we’ll take a look at some of the key players and create a projection based on this methodology.


  1. obsessivegiantscompulsive

    Great article and research, I look forward to seeing what you have to say about the Giants, and where their hitters lie along the continuum that you describe above.

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