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The Cardinals’ run prevention numbers should be better in 2017

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The Cardinals underperformed their FIP by a wide margin in 2016, and recent history indicates they are due for improvement.

St. Louis Cardinals v Colorado Rockies Photo by Justin Edmonds/Getty Images

The fielding independent pitching (FIP) statistic helps measure what a pitcher’s ERA might look like had he been on the receiving end of league-average defense (and luck) on balls in play. As such, if a pitcher has a bad defense behind him, his ERA will likely suffer to no fault of his own. To see this in practice, in 2016 the ten worst defensively-rated teams by FanGraphs averaged an ERA (4.50) that was 17 points higher than their FIP (4.33), and well above the league-average of 4.19.

The Cardinals’ pitching in 2016 wasn’t as bad as it may have seemed. Their team-ERA of 4.08 was better than both the 4.19 MLB average and the NL average of 4.17. However, they probably should have been better.

Their 3.88 team-FIP was the seventh best in baseball but the +.20 spread from their team-ERA was also the seventh worst in baseball. They may have been unlucky (bad defense, fluke hits, etc.), simply not that great, or some combination of both, but it was only the fifth time since 2000 that Cardinals pitchers didn’t outperform their FIP, and the .20 difference was the worst spread for the team since 1994.

If you’re curious what that looks like in fancy graph-form, here’s the Cardinals staff’s ERA and FIP dating back to 2000.

As you can see, the last two seasons have deviated (albeit in different directions) from what had been six straight years of rather stable and impressive run prevention. From 2009 to 2014, the Cardinals’ ERA was 3.61, which was fourth best in all of baseball. True to form after 8,700+ innings pitched, their FIP (3.68) stayed pretty close to their ERA and was third best in the league during this stretch.

The last two seasons were different though - at least on the ERA front. The good news, now that the 2016 season has been over and done with for nearly four months, lies in the hope that Cardinals pitching will be luckier, better, or again, some combination of both in 2017. Following 2015, the common refrain was that the Cardinals’ elite pitching was sure to regress in 2016 and that proved to be correct. That wasn’t a big surprise and the same is likely to happen to the Cubs this year, although to what extent remains to be seen. But based on this same principle, is it likely that the Cardinals’ run prevention numbers will be noticeably better in 2017?

To get an idea of what often happens the year after for teams who similarly underperformed their FIP like the 2016 Cardinals, I looked at a ten-season stretch from 2006 to 2015 for teams with an ERA higher than their FIP by 0.15 to 0.25, and then looked at their pitching stats for the following season (e.g., The 2011 Orioles had a team 4.92 ERA and 4.67 FIP, and were compared to their 2012 season.). This search, via FanGraphs Leaderboards, returned 39 samples, which resulted in the chart being pretty bulky so I put it at the end of this post in the event you want to scroll down, but here are some of the relevant results.

In the 2006 to 2015 stretch in which the 39 teams underperformed their FIP by 0.15 to 0.25 (sample 1), they averaged an ERA of 4.29. The following year (sample 2) these 39 teams’ average ERA dropped to 4.15, with 62% of the teams in sample 2 seeing an improvement in ERA. The average FIP for sample 1 and sample 2 was exactly 4.11 for both.

Teams from sample 1 won an average of 76.1 games per season and improved to 77.4 wins the following season. (Is now a good time to remind you for the 999th time that the Cardinals missed extra baseball in 2016 by one game?) Those numbers are probably a bit skewed though. Only 46% of the teams in sample 2 actually won more games than the previous season. The 1.3 game difference was a product of a few outliers, such as, to use the example from earlier, the 2011 Orioles who only won 69 games and then jumped to 93 wins in 2012.

This is not a perfect nor scientific study and is not meant to be interpreted as such. Pitching rosters change from year to year, and if a team had particularly underwhelming pitching one year, it makes sense that they might seek to improve it before the next year. The Cardinals, for instance, traded Jaime Garcia this offseason, and Michael Wacha is possibly set for a bullpen role. As for the pen, Zach Duke, Tyler Lyons, Seth Maness amongst others won’t carry over into 2017.

Looking at the returnees though, Adam Wainwright, Mike Leake, Wacha, Matt Bowman, Jonathan Broxton, and Trevor Rosenthal threw a combined 682 innings for the Cardinals in 2016, and each underperformed their FIP by at least .15. Wacha was at the high end with an ERA that was 1.18 over his FIP. Only three other pitchers (Aaron Nola, Tyler Duffey, Shelby Miller) threw at least 100 innings and had a worse difference between the two metrics. Then there’s the return of Lance Lynn, an innings-horse who’s coming off a missed season due to Tommy John (so take that into account), but who was also a much better than league average pitcher from 2012 to 2015 by almost any metric, including run prevention (3.38 ERA and 3.39 FIP compared to NL average of 3.82 and 3.81, respectively, during that stretch).

As for the defensive side of the ball, it’s no secret that the Cardinal did not excel in the field last year, which led to John Mozeliak explicitly stating that an improved defense would be a priority for 2017. Earlier this month, VEB’s Ben Markham outlined how the pieces are already there for that to happen. I might be getting ahead of myself and maybe what we saw last year was only the beginning of a staff in decline, but there are a lot of reasons to believe that the Cardinals’ run prevention will be better in 2017.

Per earlier, here’s the 2006-2015 chart, starting with teams with an ERA at .25 over their FIP and working down to .15.

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Team ERA FIP E-F Wins
Team ERA FIP E-F Wins
2011 BAL 4.92 4.67 0.25 69
2012 BAL 3.9 4.2 -0.3 93
2009 ARI 4.44 4.2 0.24 70
2010 ARI 4.81 4.76 0.05 65
2010 LAD 4 3.76 0.23 80
2011 LAD 3.56 3.61 -0.05 82
2014 MIA 3.79 3.56 0.23 77
2015 MIA 4.04 3.98 0.05 71
2011 CHC 4.34 4.11 0.23 71
2012 CHC 4.51 4.46 0.05 61
2007 MIL 4.44 4.22 0.22 83
2008 MIL 3.87 4.34 -0.47 90
2014 HOU 4.14 3.93 0.22 70
2015 HOU 3.57 3.66 -0.09 86
2007 CHW 4.77 4.56 0.21 72
2008 CHW 4.11 4 0.11 89
2012 MIA 4.1 3.89 0.21 69
2013 MIA 3.71 3.69 0.02 62
2009 BOS 4.35 4.14 0.21 95
2010 BOS 4.19 4.08 0.11 89
2010 HOU 4.09 3.89 0.2 76
2011 HOU 4.51 4.35 0.16 56
2013 SFG 4 3.8 0.2 76
2014 SFG 3.5 3.58 -0.07 88
2014 CHW 4.3 4.1 0.2 73
2015 CHW 3.98 3.82 0.16 76
2009 HOU 4.54 4.35 0.2 74
2010 HOU 4.09 3.89 0.2 76
2011 COL 4.44 4.24 0.2 73
2012 COL 5.22 4.59 0.63 64
2009 WAS 5.02 4.82 0.19 59
2010 WAS 4.13 4.12 0.01 69
2010 TOR 4.23 4.04 0.19 85
2011 TOR 4.33 4.29 0.04 81
2011 NYM 4.19 4 0.19 77
2012 NYM 4.09 3.93 0.16 74
2009 OAK 4.29 4.1 0.19 75
2010 OAK 3.58 4.13 -0.54 81
2015 DET 4.64 4.46 0.18 74
2016 DET 4.24 4.16 0.09 86
2007 MIA 4.96 4.77 0.18 71
2008 MIA 4.44 4.37 0.07 84
2011 KCR 4.45 4.27 0.18 71
2012 KCR 4.3 4.18 0.12 72
2011 CLE 4.24 4.06 0.18 80
2012 CLE 4.79 4.4 0.39 68
2010 MIA 4.09 3.92 0.18 80
2011 MIA 3.95 3.79 0.17 72
2006 TEX 4.61 4.44 0.17 80
2007 TEX 4.76 4.83 -0.07 75
2009 MIA 4.32 4.15 0.17 87
2010 MIA 4.09 3.92 0.18 80
2015 BOS 4.34 4.17 0.17 78
2016 BOS 4 4 0 93
2015 WAS 3.62 3.45 0.17 83
2016 WAS 3.52 3.58 -0.06 95
2011 MIA 3.95 3.79 0.17 72
2012 MIA 4.1 3.89 0.21 69
2015 CHW 3.98 3.82 0.16 76
2016 CHW 4.12 4.27 -0.16 78
2012 NYM 4.09 3.93 0.16 74
2013 NYM 3.78 3.79 0 74
2015 SDP 4.09 3.93 0.16 74
2016 SDP 4.44 4.4 0.05 68
2013 LAA 4.24 4.08 0.16 78
2014 LAA 3.58 3.57 0.01 98
2011 HOU 4.51 4.35 0.16 56
2012 HOU 4.57 4.27 0.3 55
2014 CLE 3.57 3.42 0.15 85
2015 CLE 3.68 3.62 0.06 81
2008 ARI 3.99 3.84 0.15 82
2009 ARI 4.44 4.2 0.24 70
2006 COL 4.66 4.51 0.15 76
2007 COL 4.32 4.52 -0.2 90
2011 BOS 4.2 4.05 0.15 90
2012 BOS 4.72 4.41 0.31 69
2006 ARI 4.49 4.34 0.15 76
2007 ARI 4.13 4.52 -0.38 90