Felix wins the Cy Young!

It was just announced that our very own Felix Hernandez won the AL Cy Young award this season. This is a sweet end to a season that saw the Mariners lose 101 games, and Felix receive some of the worst run support of any pitcher. This is also a victory for the push to expel wins from any conversation involving a pitcher’s ability. In comparison to the 2nd and 3rd place vote getters, David Price and C.C. Sabathia, Felix had an awful win-loss record. His 13-12 paled up against Sabathia’s 21-7 and Price’s 19-6.

Mariner and Fangraph’s blogger Dave Cameron pointed out that just 5 years ago, a tub of lard by the name of Bartolo Colon won the award based purely on his 21-8 record (3.48 ERA, 3.75 FIP, 3.90 xFIP). That same season, Johan Santana baffled hitters constantly en route to a 2.87 ERA, 2.80 FIP, 3.10 xFIP and a 16-7 record. In both 2001 and 2004, Roger Clemens and Randy Johnson were two of the top pitchers in the NL. Both years Clemens won the award, but here’s how their stats lined up:

 

Clemens 2001: 20-3, 3.51 ERA, 3.29 FIP

vs.

Johnson 2001: 21-6, 2.49 ERA, 2.13 FIP

 

Clemens 2004: 18-4, 2.98 ERA, 3.11 FIP, 3.37 xFIP

vs.

Johnson 2004: 16-14, 2.60 ERA, 2.30 FIP, 2.60 xFIP

Santana and Johnson, obviously better pitchers those seasons, were denied the award because of old school thinking from the Baseball Writer’s Association of America (BWAA). So the fact that Felix got the award this year with his 13-12 record represents a measurable change in the thinking of the BWAA as whole. And it wasn’t even close: the Mariner ace took 21 of 28 first place votes!

As a side note: a reader of Fangraphs mentioned that “[ESPN was] discussing the cy young, and they gave an explanation of xFIP and why it was a useful.” That makes me happy 🙂

Be Careful With ERA

ERA (earned run average) is computed as the average earned runs a pitcher gives up per 9 innings, and it is one of the most commonly used indicators of a pitcher’s ability. Being a rate statistic, versus an accumulating statistic like strikeouts or wins, it gives us an idea of how effective pitchers are at preventing earned runs. However, if we delve into the numbers further, we find that there are other important indicators that influence an ERA.

I have written copious amounts about BABIP, the batting average only on balls in the field of play. This is the average that opposing batters hit off the pitcher on all at bats that don’t end in a home run or a strike out. Pitcher’s have virtually no control over BABIP, and therefore high average on balls in play can show that a pitcher is getting unlucky, while low figures indicate some good fortune for the pitcher.

Another indicator is how many home runs a pitcher gives up per each fly ball. This stat also tends to level out for most pitchers, and once again, numbers above the league average (7.7%) indicate bad luck and numbers below good luck.

Then there’s Left On Base Percentage (LOB%). The percent of runners that reach base on a pitcher yet never score. Good strike out pitchers can expect figures between 75-80% while pitchers with low strike out rates and higher OBPs should see figures between 65 – 70%.

The final “luck indicator” is the percentage of total runs a pitcher allows that are earned runs. Some pitchers can actually get saved by unearned runs. Think about this: a pitcher loads up the bases with two outs. He then yields a ground ball to the shortstop, but the shortstop muffs it. An unearned run scores, but it does not hurt the pitcher’s ERA. Fair enough, but the next batter comes up and hits a grand slam. If I’m not mistaken, the pitcher’s ERA remains unchanged because the previous error should have been the end of the inning. I can understand if the three guys on base don’t count toward the ERA, but at least one run should count as earned because the pitcher gave up a homer. The run from this homer was completely stricken from his ERA record. Pitchers who allow more base runners tend to see these situations more often, where runs that should count toward their ERAs are not tallied due to quirks the definition of an earned run. Therefore, I tend to focus more on how many total runs a pitcher relinquishes and then use a common percentage – the major league average is about 92% of all runs are earned – to estimate an ERA.

During the course of a season, any one (or perhaps all) of these indicators can lean toward lucky or unlucky for a given pitcher. I have created a formula that puts all pitchers on a level playing field, almost as if they are playing in a vacuum. Though I understand that this is not physics nor economics class, and we don’t live in vacuums, this is still a better way to measure true ability than a simple ERA.

Here is a short list of some particularly fortunate and unfortunate pitchers this season based on my formula.

Pitcher                          ERA          Projected ERA     Difference

Jarrod Washburn              2.93             3.90                       +0.97

Edwin Jackson                  2.64             3.62                       +0.98

Cole Hamels                    4.68              3.75                       -0.93

Randy Johnson                 4.81              3.67                       -1.14

These are just some examples of players whose ERAs have been especially influenced by the luck factors. While their current ERAs, or total runs per 9 allowed, are probably a better indication of how much they have actually helped their teams thus far, the projected ERAs are a much improved way of predicting how they might do the rest of the season. As a general manager or fantasy player, one should not be as concerned with the past as with the future. While Edwin Jackson and Jarrod Washburn are still above-average pitchers, even this season they are not phenomenally better (or better at all) than Randy Johnson or Cole Hamels, despite the ERA discrepancy.

Run Expectancy and Reliever’s ERAs

The lowest ERAs in the league every year are turned in by relievers, and in 2009 relievers as a whole have allowed 0.4 less runs per nine innings that the starters (4.8 vs. 4.4). Most would agree that starters are generally better pitchers, so why is it that runs are scored at a higher rate on their watch? Bill James had the answer years ago.

We can talk about batters not being able to adjust to a relief pitcher – adjusting to the new release, arm angle, movement and velocity is hard – but there’s something much more fundamental that separates starters and relievers: when they enter a game. Starters always start every inning from the beginning with none out, whereas relievers often come in with one or two outs, and their runs allowed stats are treated as though the bases were empty when they entered.

Taking a hypothetical league-average pitcher, we can see the difference between starters and relievers. The league average starter will enter every inning with no runners and no outs. His run expectancy (2009 stats) is 0.51 runs for that inning, or about 4.65 runs per nine. If a reliever enters with 1 out, assuming he performs at the league average, his run expectancy is about 0.28 runs for that inning, equating to 3.8 runs per nine. If he enters with 2 outs, his run expectancy is 0.1 runs for the inning and 2.76 runs per nine. So basically, the very same pitcher has a huge advantage if he enters the game with 1 or 2 outs.

Given an average middle reliever who gets 1/3 of his appearances in each situation – 0 outs, 1 out and 2 outs – his expected runs allowed is about 4.00, even though his true figure would be 4.65 if he started. By virtue of occasionally entering games mid-inning, relief pitchers are given an advantage in ERA and runs allowed stats.

What Correlates to Winning League Championships?

In sports, we often hear the phrase, “defense wins championships,” and specifically in baseball, “pitching wins championships.”  The other night on an ESPN baseball telecast, analyst Steve Phillips was taking that very argument even further, asserting that low ERAs are more important that high offensive production when it comes to winning championships. While there is no doubt that lower team ERAs help win games and playoff series, I am skeptical of much of what comes out of Phillips’ mouth, so I set out to check his hunch.

First off, to get into the playoffs and have a shot at the League Championship Series, teams have to win in the regular season. Taking a quick look at some regular season stats from the last 20 seasons and how they correlate to regular-season wins, season run differential (average runs scored minus average runs allowed) comes out on top. If you’re concerned about the differences between the AL and the NL, the only noticeable difference is that offensive runs per game tend to be slightly more important in the AL than in the NL.

*Coefficients closer to 1 represent stronger correlations

Stat                                              Coefficient                  Wins+/Run

Run Differential                             0.92                                        16

ERA                                               0.63                                        13.5

Total runs scored per game          0.56                                        13

This tells us that, of these three team stats, it’s the run differential that best explains teams winning games, and making it to the playoffs. Also, ERA tends to explain total wins slightly better than run scoring. Hey Steve, you might be on to something here. Winning championships, though, is a different story. The unpredictability of five or seven-game series does not often distinguish teams that have only marginally better ERAs or run differentials.

Observing the logistic correlation between just the playoff teams’ season stats versus winning league championships exhibited some interesting results over the last 20 years—not counting 1994, obviously, because of the strike.

In the American League, the best correlation to which team won the ALCS was total season wins, followed closely by run differential and ERA. Each of these was an excellent indicator of which team won, all being significant at the 5% level. However, runs per game did not have any predictive power over which team won the ALCS.

In the National League, none of the correlations were particularly strong, but again season wins came out on top, followed this time by ERA then run differential.  However, no correlation was significant at even the 30% level. Runs per game stayed consistent, showing almost no correlation to NLCS winners.

There are some important things we can take from this study. Teams that make the playoffs and give themselves a shot at the championship are likely to be teams with healthy, positive run differentials. Because run differential implies both high run-scoring and low ERAs, these stats also logically correlate to winning.

Once we get to the playoffs, the best predictors for League Championship Series Winners are—aside from total season wins—ERA and run differential, which both are much more important than offensive production. Basically, teams that win the regular season win in the playoffs, and teams with low ERAs and good run differentials win championships more consistently than teams with greater run production.

When building a team to win a championship, the past has shown that healthy run differentials, when driven by lower ERAs, are the keys to winning the League Championship Series. I would like to give Steve Phillips a gold star for his always on-target gut instinct. Please sense the sarcasm.