David Price Is About to Go Off

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On June 25, this was David Price’s tweet to family, friends and fans.  It was a clear signal that he knew the patience of the Boston fans and media was wearing thin.

Fast forward to the All-Star break and his “Made for TV” stats (those that casual fans know best) are underwhelming: a 9-6 record with a 4.34 ERA, which is worse than the MLB average of 4.23.  It’s not so much his ERA that’s the problem to fans, but more his inability to be consistent from start to start.  Price has three starts of six-plus innings allowing two or fewer runs, but also has four starts of allowing six or more runs.  With the rest of the rotation producing an atrocious 4.86 ERA, the Sox desperately needed Price to be the one to stop the bleeding, something he hasn’t been able to do.  But that doesn’t mean his underlying skills have deteriorated and all of a sudden he’s become a league-average pitcher.  In fact, the advanced metrics say he’s been extremely unlucky and that he’s due for a big second half. 

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* Rank is solely being used to establish a baseline for Price as a top 10 pitcher.

In 2014 and 2015 combined, Price was ranked in the top 10 of all pitchers in four of the skill-based statistics: K%, BB%, xFIP and SIERA (the latter two being ERA estimators with a weighting towards more pitcher-controlled outcomes).  Through the 2016 All-Star break, Price has maintained or improved his top-10 rank in K%, xFIP and SIERA but dropped a few spots in walk rate.  Despite the move from 9th to 10th in K% rank, his K rate is actually up from 26.2% to 27.1%.  The reason for the drop in rank is that 2016 newcomers to the list Jose Fernandez, Noah Syndergaard and Drew Pomeranz did not meet the minimum innings qualifier for the 2014/2015 combined list.  On the flip side, Price’s xFIP and SIERA are higher than they were the past two years, but he has improved his ranking versus his peers.  This is because xFIPs and SIERAs are both up 10% league-wide versus last year (due to all the home runs being hit) while Price’s increases are smaller.

So what is happening?  If his base skills are fine, why is his ERA so high and his performance so inconsistent?

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So everyone is familiar with ERA and can easily infer that 4.34 is no bueno for a $217-million pitcher.  But there is a reason these stats are labeled “Non Skill-Based” — that’s because these stats are influenced by factors outside of the pitcher’s direct control (defense, luck, sequencing, variance, etc…) and therefore have wide variability over small samples.  Three of these stats (HR/FB%, BABIP and LOB%) explain why David Price is a great rebound candidate for the second half.

HR/FB%

Price’s current HR/FB (home runs per fly ball) rate is 15.2% — which is good for being ranked 76th out of 97 qualified starting pitchers.  The past two years combined he ranked 19th.  To put this in context, Price’s career average is 9.4% while the 2016 league average is 12.9%.  Price has never recorded a full season (>150 IP) HR/FB rate higher than 10.5%.  Also, on balls hit into play against Price this year, 31.3% of them are fly balls, the second-lowest rate of his career.  The only season in which he allowed a lower fly ball rate was in 2012 when he won the AL Cy Young award.  Price is giving up fewer fly balls this year, but of the fly balls he is allowing, they are going over the fence at the highest rate of his career.  Those that remember Price giving up a HR in 10 consecutive starts this year are nodding violently right now.  His HR/FB% will regress towards his career norm (9.4%) and this should be the main reason for a big second half.

BABIP

Price is also suffering from an unsustainable BABIP (batting average on balls in play).  His current mark of .321 is well above his career rate (.289) and even above his highest full-season rate (.306).  Once a ball is put into play it is out of the pitcher’s control what happens from there.  This is why defense and luck influence this stat more than skill.  And with that said, statistical outliers here tend to regress towards career norms.  Even though Price is allowing ground balls at a higher rate than the past two years, his 2016 GB% is still lower than his career average.  BABIP can be influenced by the number of ground balls a pitcher allows, but he’s not allowing vastly more than his career average.  His BABIP should have some positive regression in it, which is another predictor of improved second-half performance.

LOB%

Price’s Left-On-Base% (percentage of runners a pitcher strands over the course of a season) is currently 70.9%, which is also below his career rate (74.7%) and would be his second worst full-season rate (70.0%) if the season ended today.  Similar to HR/FB%, he is ranked 73rd out of 97 qualified starting pitchers.  The past two years he ranked 22nd.  A pitcher with a higher than average strikeout rate should be able to sustain a slightly higher than average LOB%, but it’s playing out the exact opposite way for Price.  This is partly due to his inflated BABIP and HR/FB%; as these statistics continue to regress towards his career norms, the LOB% will creep up to expected levels.

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Much has been made of Price’s velocity being down this year compared to any point in his career.  At the start of the season, his velocity was over 2.0 MPH lower than his career average (94.1).  He has since closed this gap almost entirely.  Here is his average fastball velocity by month (with number of starts):

April: 92.0 (5)

May: 92.5 (6)

June: 92.9 (6)

July: 94.0 (2)

If this upward trend in velocity stabilizes somewhere at or above 93.5, then nearly all the performance metrics within his control — velocity, K%, BB%, xFIP and SIERA — will be at or near his career norms.

Let’s dive a little deeper into that early-season velocity issue.  Below are two charts.  The first shows combined performance of 2014 and 2015 for ERA-qualifying starters while the second chart is the same data for the 2016 season through the All-Star break.  The orange circle is David Price.  The red circle (if shown) represents Price’s career average.  The blue circles are a hand selected peer group of the top 10 pitchers in the game (Kershaw, Sale, Arrieta, Scherzer, Bumgarner, Greinke, Strasburg, Syndergaard, Salazar and Fernandez).  Remember those rankings where Price was right around the top 10 — these are the guys usually outperforming him.  The gray circles represent everyone else.  Note: For these first two charts the top-right quadrant is Good, and the bottom-left quadrant is Bad (unless you’re a knuckleballer).

2014-2015 K/9 vs FBv

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2016 K/9 vs FBv

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The first graph shows David Price clustered where you would expect him — right at the middle-to-bottom of his top-10 peer group, with a healthy average fastball velocity and K/9.  The second graph (2016) shows Price in a similar relationship to his peers, but with slightly lower velocity and a higher K/9.  Note the gap between the orange (Price’s 2016) and red (Price’s career average) dots depicting his improved strikeout numbers this year despite the slightly lower velocity.  This graph also shows what freaks Noah Syndergaard, Jose Fernandez and (to a lesser degree) Jered Weaver are.

The final two graphs show the relationship between ERA and xFIP where xFIP is the more predictive estimator of a pitcher’s skill.  The bottom-left quadrant is Good (think Kershaw) and the upper-right quadrant is Bad (think Buchholz).  Anyone in the upper-left quadrant (Price in 2016) is a candidate for positive regression.

2014-2015 ERA vs xFIP

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2016 ERA vs xFIP

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The first graph again shows Price in his usual place — at the tail end of the top 10.  In 2014 and 2015 combined he had a very similar ERA (2.88) and xFIP (2.98).  The second graph (2016) shows the disparity between his ERA (4.34) and xFIP (3.16).  Pitchers with this large of a gap between ERA and xFIP are great candidates for regression.  The important takeaway is that his xFIP, relative to his peers, has stayed in that top-10 range.  This supports the point that some bad luck is the main element depressing his ERA.

David Price can easily be the best pitcher in the American League over the next two and a half months.  He already owns the lowest xFIP in the AL at 3.16 — the next-closest is Corey Kluber, at 3.34.  The skills above show he can sustain the xFIP level, but with some change in luck and maintaining his improved velocity, he doesn’t need to “pitch better”; he just needs to keep pitching — and the results will follow.