Author Archive

Identifying HR/FB Surgers Using Statcast

It seems that 2016 will be the year that Statcast begins to permeate Fantasy Baseball analysis. Recently there has been a wealth of articles exploring the possibilities of using these kinds of data. These pieces have provided relevant insights on how to improve our understanding of well-hit balls and launch angles. Also, they’ve facilitated access to information on exit velocity leaders and surgers, as well as provided thoughtful analyses to the possible workings behind some early-season breakouts.

However, there is still a lot we don’t know about Statcast data. For instance, we are uncertain of how consistent these skills are over time, both across seasons or within seasons. Also we don’t know what constitutes a relevant sample size or when rates are likely to stabilize. All in all, this makes using 2016 Statcast data to predict rest of season performance a potentially brash and faulty proposition. Having said that, we can’t help but to try; so here’s our attempt at using early-season 2016 Statcast data to partially predict future performance.

One of the early gospels of Statcast data analysis posits that the “sweet spot” for hitting homers comes from a combination of a launch angle in the range of 25 – 30 degrees and a 95+ MPH exit velocity. If this is indeed the ideal combination for hitting home runs, one could argue that players that have a higher share of fly balls that meet these criteria should perform better in other more traditional metrics such as HR/FB%.

Following this line of thought we dug up all the batted balls under the “sweet spot” criteria, and divided them by all balls hit at a launch angle of 25 degrees or higher (which MLB determines as fly balls) to come up with a Sweet Spot%. In an attempt to identify potential HR/FB% surgers, we compare Sweet Spot% and HR/FB% z-scores (to normalize each rate) for all qualified hitters with at least 25 fly balls and highlight the biggest gaps.  Here are the Top five gaps considering the games up to May 28th:

Name Team HR/FB  % HR/FB  %         Z-Score Sweet Spot % Sweet Spot % Z-Score Z-Score Diff
Kole Calhoun Angels 6% -1.15 26% 2.24 3.39
Stephen Piscotty Cardinals 11% -0.35 26% 2.33 2.68
Matt Carpenter Cardinals 16% 0.44 29% 2.73 2.29
Denard Span Giants 3% -1.66 15% 0.52 2.18
Yonder Alonso Athletics 3% -1.69 15% 0.43 2.12

Calhoun seems like a good candidate for a power uptick. He has the third-highest Sweet Spot% of 2016, and he has sustained similar Hard% and FB% to the previous two seasons. Yet somehow he has managed to cut his HR/FB% to less than half of what he put together in either 2014 or 2015.  More so, he has had some bad luck with balls hit in the “sweet spot”; his batting average in these kinds of balls is .500, whereas the league average is around .680. He is not killing fly balls in general, with an average exit velocity of 84.6 MPH, but if he keeps consistently hitting balls in the “sweet spot” range he should improve in the power department. Look out for a potential turnaround in the coming weeks and a return to 2015 HR/FB% levels.

Piscotty holds second place in the Sweet Spot% rankings. However, his FB% is very similar to what he did in 2015 whilst his Hard% is down from 38.5% to 32.5%. Lastly, he plays half of his games in Busch Stadium, which has a history of suppressing home runs. I would be cautious of expecting a major home-run surge, but in any case Piscotty is likely to at least sustain his performance in the power department, which would be welcome news to owners that got him at bargain prices.

Carpenter is another dweller of Busch Stadium, however his outlook might be a bit different. He is the absolute leader in Sweet Spot%. He is posting the highest Hard% and FB% marks of his career. Carpenter is also crushing his fly balls in general, with an average Exit Velocity of 93.7 MPH. Just as a point of reference Miguel Cabrera, Josh Donaldson and Giancarlo Stanton fail to reach an average of 93 MPH on their own fly balls. Lastly, he has had some tough luck with balls hit in the “sweet spot”, posting a batting average of just .420. Carpenter is already putting up the highest HR/FB% of his career, and he is a 30-year-old veteran of slap-hitting fame, but the power looks legit and perhaps there is more to come.

Denard Span and Yonder Alonso show up in this list not because of their Sweet Spot% prowess but rather due to their putrid HR/FB%. They barely crack the Top 50 in Sweet Spot%. They play half their games in two of the bottom three parks for HR Park Factor. Span is putting up his lowest FB% and Hard% rates since 2013, when he ended up with a HR/FB% of 3.4%. Meanwhile, Yonder’s rates most closely resemble those of 2012, when he had a HR/FB of 6.2%. Whilst their batting average of “sweet spot” batted balls is just .500, there is nothing to look here. In any case, their power situation looks to improve from bad to mediocre.

If you are interested in the perusing the Top 50 gaps between HR/FB% and Sweet Spot%, please find them below:

Name Team HR/FB  % HR/FB  %          Z-Score Sweet Spot % Sweet Spot % Z-Score Z-Score Diff
Kole Calhoun Angels 6% -1.15 26% 2.24 3.39
Stephen Piscotty Cardinals 11% -0.35 26% 2.33 2.68
Matt Carpenter Cardinals 16% 0.44 29% 2.73 2.29
Denard Span Giants 3% -1.66 15% 0.52 2.18
Yonder Alonso Athletics 3% -1.69 15% 0.43 2.12
Kendrys Morales Royals 10% -0.61 21% 1.38 1.99
Addison Russell Cubs 12% -0.27 22% 1.67 1.94
Yadier Molina Cardinals 2% -1.72 13% 0.11 1.83
Adam Jones Orioles 11% -0.46 20% 1.29 1.75
Alcides Escobar Royals 0% -2.10 10% -0.44 1.66
Jose Abreu White Sox 11% -0.35 19% 1.11 1.46
Joe Mauer Twins 17% 0.56 24% 1.96 1.40
Chris Owings Diamondbacks 3% -1.59 11% -0.26 1.32
Jacoby Ellsbury Yankees 5% -1.28 12% -0.09 1.19
Justin Turner Dodgers 6% -1.20 12% -0.01 1.19
Victor Martinez Tigers 12% -0.19 18% 0.95 1.14
Daniel Murphy Nationals 10% -0.60 16% 0.54 1.14
Justin Upton Tigers 4% -1.43 11% -0.29 1.14
Josh Harrison Pirates 5% -1.37 11% -0.25 1.12
Anthony Rendon Nationals 6% -1.23 12% -0.11 1.12
Corey Dickerson Rays 16% 0.42 21% 1.50 1.07
Brandon Crawford Giants 11% -0.41 16% 0.66 1.07
Ian Desmond Rangers 16% 0.35 21% 1.41 1.06
Derek Norris Padres 12% -0.30 17% 0.74 1.04
Ryan Zimmerman Nationals 19% 0.78 23% 1.81 1.03
Gregory Polanco Pirates 14% 0.11 19% 1.11 1.00
Austin Jackson White Sox 0% -2.10 6% -1.13 0.97
Nick Markakis Braves 2% -1.79 7% -0.86 0.93
Corey Seager Dodgers 18% 0.66 22% 1.56 0.91
Michael Saunders Blue Jays 20% 1.00 24% 1.88 0.89
Mike Napoli Indians 23% 1.38 26% 2.27 0.88
Brandon Belt Giants 7% -0.97 11% -0.15 0.81
Matt Kemp Padres 17% 0.59 20% 1.36 0.77
Nick Ahmed Diamondbacks 8% -0.81 12% -0.05 0.77
Matt Duffy Giants 4% -1.45 8% -0.73 0.71
David Ortiz Red Sox 19% 0.90 21% 1.53 0.63
Joe Panik Giants 9% -0.69 12% -0.06 0.63
Elvis Andrus Rangers 2% -1.72 6% -1.10 0.63
Brandon Phillips Reds 11% -0.41 14% 0.21 0.62
Adam Eaton White Sox 8% -0.81 11% -0.20 0.62
Gerardo Parra Rockies 8% -0.87 11% -0.26 0.61
C.J. Cron Angels 6% -1.18 9% -0.58 0.61
Dexter Fowler Cubs 13% -0.04 16% 0.56 0.60
Jose Altuve Astros 17% 0.53 19% 1.11 0.58
Prince Fielder Rangers 4% -1.42 7% -0.90 0.51
Jose Ramirez Indians 7% -1.09 9% -0.58 0.51
Joey Rickard Orioles 8% -0.91 10% -0.42 0.48
Asdrubal Cabrera Mets 7% -1.00 9% -0.53 0.46
Mark Teixeira Yankees 10% -0.50 12% -0.05 0.46
Ben Zobrist Cubs 13% -0.12 14% 0.34 0.45

Note: This analysis is also featured in our emerging blog www.theimperfectgame.com


Estimating the Cost of Undoing the Sandoval/Hanley Mistakes

This week we will be following up on our previous piece regarding Least Valuable Players. There we identified Hanley Ramirez and Pablo Sandoval as the two worst performers of the 2015 season. We are not fans of beating the proverbial dead horse, but given that this was just the first year of their respective contracts we were interested in figuring out just how bad these deals are shaping up for the Red Sox.  The short answer? It is bad. Like, Lucas Duda throwing to home in high-pressure situations bad.

As you might recall, during the 2015 season Sandoval accumulated a -2 WAR whilst Hanley finished up with a -1.8 WAR.  Even after that woeful start, the Red Sox are still on the hook for 5 more years and $89.4 million for Sandoval, and 4 years and a total $90.25 million for Hanley. Just let that sink in for a minute: 9 seasons of potentially below-replacement-level performance for $180 million. That makes the Barry Zito deal sound like a real steal.

For the sake of argument, they do not have to be that bad for the rest of the contract, do they? I mean, these guys were 3-win players just two seasons ago; maybe this was just a hiccup. Well, Steamer seems to partially agree with this logic and projects them to improve substantially. More precisely, it projects Sandoval to have 1.8 WAR and Hanley 2.2 WAR during 2016. Returning to these levels of performance is something, but is it enough to salvage these deals?

We replicate the player assessment analyses we used in our piece comparing offseason splurges in pitchers, just to figure out the net value of these deals.  We use Steamer’s 2016 projections as a starting point for WAR and then apply a player aging curve that goes as follows:  WAR increases annually by +0.25 for ages 18-27, stays flat for ages 28-30, decreases annually by -0.5 for ages 31-37 and lastly decreases annually by -0.75 for ages 38 and above. With regards to the market value of wins we start off at $8 million per win and we apply a 5% yearly inflation rate.

Pablo Sandoval
Year $/WAR ($MM) Age Total Salary ($MM) Projected WAR Estimated Value ($MM) Net Value ($MM)
2016 $8.00 30 $17.60 1.80 $14.40 -$3.20
2017 $8.40 31 $17.60 1.80 $15.12 -$2.48
2018 $8.82 32 $18.60 1.30 $11.47 -$7.13
2019 $9.26 33 $18.60 0.80 $7.41 -$11,19
2020 $9.73 34 $17.00 0.30 $2.92 -$14.08
Total     $89.40 6.00 $51.31 -$38.09

 

Hanley Ramirez
Year $/WAR ($MM) Age Total Salary ($MM) Projected WAR Estimated Value ($MM) Net Value ($MM)
2016 $8.00 32 $22.75 2.20 $17.60 -$5.15
2017 $8.40 33 $22.75 1.70 $14.28 -$8.47
2018 $8.82 34 $22.75 1.20 $10.58 -$12.17
2019 $9.26 35 $22.00 0.70 $6.48 -$15.52
Total     $90.25 5.80 $48.95 -$41.30

 

Even after considering the improvements suggested by Steamer, none of the 9 seasons controlled by the Red Sox would produce a net positive value, and overall the net loss of these deals comes at $79.4 million.

We ran the numbers, and in order for the Red Sox to recoup their investments, even after letting 2015 go down as a sunk cost, Sandoval would have to accrue 10.35 WAR for the rest of the contract (73% more than the projection), whilst Hanley would have to accumulate 10.56 WAR (82% more than the projection). This seems to be rather unlikely, especially when you consider that the Steamer projection already seems bullish, implying a 4 WAR improvement between seasons.

We wanted to test just how bullish this prediction is. We set out to find the past seasons most like the ones Sandoval and Hanley just endured and tried to identify how those players fared off the year after as well as for the rest of their careers.  We searched the last 30 seasons for players between the ages of 28 and 32, that produced a -1.5 WAR or worse in at least 400 PA, after accumulating at least 5 WAR in the previous two seasons. Namely, we were searching for players that had been performing at a high level, still in their prime or early phases of decline, which suddenly plummeted in performance.

Comparable rest of career outlook

Player

Year of decline WAR two seasons before decline WAR year of decline WAR year after decline Change WAR rest of career after decline Seasons rest of career after decline

Average WAR per season rest of career

Richie Sexson

2007

6.4

-1.5 -1.1 0.4 -1.1 1

-1.10

Alvin Davis

1991

6.8

-1.6 -0.1 1.5 -0.1 1

-0.10

Allen Craig

2014

5

-1.7 -0.9 0.8

DNA

Joe Carter

1990

5

-2 4.6 6.6 6.9 8

 0.86

Brian McRae

1999

5.1

-2.5 0 0 0

Lo and behold the mother of small samples. We found just 5 players that met these requirements, 4 of them are already retired and one of them, well, one of them also plays for the Red Sox.  Out of these five players four of them improved after their decline season, the other one was out of the game. Out of the ones that improved, only one, Joe Carter, was able to meet the 4 WAR improvement inherent to the Steamer prediction, actually he was the only one that was better than replacement level after the decline season. So far Joe Carter has also been the only one able to play more than one season in the majors after the decline, with the jury still out on Allen Craig.

Just how good were Joe Carter’s first five seasons after the decline? Well he won back-to-back World Series with the Blue Jays, starred in one of the most memorable moments of baseball history and amassed a total of 9.4 WAR; a figure similar to what would be required for either Hanley or Sandoval to break even in their contracts. Just how bad is the alternative? Another season of negative WAR (-1 is the average for those not named Joe Carter) and 0 WAR from then on; a scenario like this would produce net value losses for the Red Sox close to $200 million or 150% more than what emanates from the Steamer scenario.

I know that we are dealing with extremely small sample sizes, but entertain this thought for a second. Let’s imagine that the above players represent the universe of possibilities and hence Pablo and Hanley each have a 20% chance of becoming Joe Carter and returning a net value of 0, that means breaking even and getting fair value for investment, and 80% of teetering off and producing a net loss of around $100 million.  Under that scenario the expected value of keeping both players comes somewhere at a net loss of $160 million over the life of the contracts. That is not necessarily crippling as it translates roughly to 3-4 lost wins per year, but these bad decisions can find a way to add up quickly.

Based on this, the Red Sox would certainly welcome another Dodger bailout, however this time around they might have to add additional value for a deal to go through. Moving forward the Red Sox might want to pursue one of three alternatives. First off, they might use that $160 million expected net loss value as an upper bound of how much they would be willing to send (in either money or player value) to another team as compensation for taking these contracts off their hands. Secondly, they could settle on the Steamer projection and set that upper bound on $80 million. Lastly, they could try to make the other team believers of the Joe Carter dream, and try to get away with not sending anything else, and even hoping to get something of value back in return, but this seems rather unlikely.  In theory by sending something (money or players) of less value than those upper bound figures to facilitate the deals they would be effectively cutting their losses.

With regards to the debate between sending some money or a player with value to make the deal work, it should be noted that $160 million in net player value over 5 years is something like Xander Bogaerts and a Top 25-50 prospect. Despite all the good will that recent deals have gained Dombrowski, there is no way Red Sox Nation would look kindly into giving up that kind of talent just to undo a mistake. The Red Sox are looking to become consistently competitive for the years to come and it does not make much sense to mortgage the team’s present and future by giving up so much controllable high-end talent. It may be time for the Red Sox to leverage their financial fortitude, bite the bullet, subsidize part of the contracts if need be, and move on.


The Least Valuable Players (LVPs) of 2015

After the announcement of the Cy Young and MVP winners, the award season is officially over and the offseason is in full stride. Most, except perhaps Royals and Mets fans, have moved on from the 2015 season and are focused on the year ahead. However, before doing so, I wanted to answer one final question about the past season: Who were the league’s Least Valuable Players (LVPs)?

Inspired by Neil Paine’s piece on Bryce Harper and the MVP I define the LVPs as position players (with at least 400 plate appearances) that not only had a bad year in terms of performance, but had an even worse performance relative to the salary they were being paid.

Why the distinction?  First off, most teams, with a few apparent exceptions (I’m looking at you Dodgers) have some sort of payroll limitation. Therefore having an expensive player stink up the place limits the opportunity that teams have to replace them via free agency or trade.

Secondly, it is my initial assumption, that underperforming players with large contracts may get disproportionally more playing time than similarly underperforming players with cheap contracts. This might be because teams hope that by giving players a chance to work things out at the plate they may salvage their initial investment or even entice another team to take a flyer with them. This, in the end, might be compounding the issue in the long-term as it robs the team the opportunity to try out existing farm-level talent at the position for instance.

It should be noted that it is possible that unlike most replacement-level players, underperforming players with big contracts were at some point actually good players and might have some other intrinsic value for their teams (i.e.: leadership, tradition, marketing, etc.) that justifies playing time; think of Ken Griffey Jr during his last few seasons or Derek Jeter’s farewell tour. However, for the intents and purposes of this article we will not be discounting player’s terribleness by any of these measures.

As far as methodology goes we will be replicating Paine’s approach from the previously mentioned article. FanGraphs calculates the monetary value of a player by estimating how much teams spent during the preceding offseason per projected WAR and then multiplying this value by accrued WAR during the season to get a sense of how much those wins above replacement would’ve cost in the “open market”. Then, from this “open market” value we subtract the actual salary (or rather salary cap hit from spotrac) of the players to get a grasp for their relative value or net value. In the case of over performing players this would turn into a value surplus for the team, whilst for underperforming players this would represent an additional cost for the team.

For example, per FanGraphs, the cost of a win in the 2015 offseason was approximately $8 million. Mike Trout accumulated WAR of 9.0 during the year, which means that the value his 2015 season was around $72 million. Meanwhile, his salary was a “mere” $6.1 million, which makes the surplus for the Angels somewhere around $66 million. In other words, the Angels paid $6.1 million in salary to get $72 million worth in production, which is a bargain of historic proportions.  Conversely, during the 2015 season Ryan Howard accumulated a WAR of -0.4, which translates into a -$3.2 million value. Not only that, but Howard was paid a cool $25 million for his services, which means that the true cost to the Phillies was of $28.2 million. In other words Philadelphia invested $25 million to get -$3.2 million in production, which over time is the kind of decision that leads to this.

So without further ado here are our Top 50 LVPs from the 2015 season:

Player Team WAR “Open market” value (MM USD) Salary cap hit (MM USD) Net value (MM USD)
Hanley Ramirez Red Sox -1.8 -$14.40 $19.75 -$34.15
Pablo Sandoval Red Sox -2 -$15.70 $17.60 -$33.30
Victor Martinez Tigers -2 -$15.80 $14.00 -$29.80
Ryan Howard Phillies -0.4 -$3.40 $25.00 -$28.40
Adam LaRoche White Sox -1.4 -$11.30 $12.00 -$23.30
Joe Mauer Twins 0.3 $2.20 $23.00 -$20.80
Matt Kemp Padres 0.4 $3.50 $21.25 -$17.75
Yasmany Tomas Diamondbacks -1.3 -$10.70 $5.38 -$16.08
Melky Cabrera White Sox -0.3 -$2.50 $13.00 -$15.50
Angel Pagan Giants -0.5 -$4.40 $10.25 -$14.65
Omar Infante Royals -0.9 -$7.00 $7.50 -$14.50
Jacoby Ellsbury Yankees 0.9 $6.90 $21.14 -$14.24
Alexei Ramirez White Sox -0.5 -$3.70 $10.00 -$13.70
Billy Butler Athletics -0.7 -$5.70 $6.67 -$12.37
Chris Owings Diamondbacks -1.4 -$11.20 $0.51 -$11.71
J.J. Hardy Orioles 0 -$0.20 $11.50 -$11.70
Jay Bruce Reds 0.1 $0.60 $12.04 -$11.44
Prince Fielder Rangers 1.6 $12.90 $24.00 -$11.10
Cody Asche Phillies -1.1 -$9.00 $0.47 -$9.47
Jimmy Rollins Dodgers 0.2 $1.70 $11.00 -$9.30
Avisail Garcia White Sox -1.1 -$8.60 $0.52 -$9.12
Michael Cuddyer Mets 0 -$0.30 $8.50 -$8.80
Alex Rios Royals 0.2 $1.30 $9.50 -$8.20
Ichiro Suzuki Marlins -0.8 -$6.20 $2.00 -$8.20
Albert Pujols Angels 2 $16.00 $24.00 -$8.00
Robinson Cano Mariners 2.1 $16.90 $24.00 -$7.10
Kurt Suzuki Twins -0.1 -$0.70 $6.00 -$6.70
Torii Hunter Twins 0.5 $3.90 $10.50 -$6.60
Yadier Molina Cardinals 1.3 $10.80 $15.20 -$4.40
Logan Morrison Mariners -0.2 -$1.50 $2.73 -$4.23

 

The American League LVP is a tight race between two teammates in which Hanley Ramirez narrowly beats out Pablo Sandoval, even after failing to accumulate enough plate appearances to qualify for the batting title. Meanwhile, Ryan Howard stands head and shoulders above the competition in the National League specially after considering that the Dodgers heavily subsidized Matt Kemp’s salary.

When considering teams most affected by this subset of underperforming stars we can highlight the Red Sox and White Sox leading the way with over $60 million of net value lost each seriously shooting themselves in the foot as both had aspired to contend in 2015.  This was particularly damning for Boston; had they not had these terrible contracts on hand, and holding all else constant, the Red Sox would have finished with the 6th best positional net value in the AL, ahead of playoff teams like the Astros, Rangers and Yankees and with sufficient cash to spend to shore up their well-documented starting rotation deficiencies.

Lastly, it’s worth noting the vast number of players on the list that were signed as free agents, extended or traded for during the past year. All in all roughly half of the players on this list fit that description, which is something to keep in mind when your team announces its next big move during the coming offseason (uh-oh).

Note: This analysis is also featured in our emerging blog www.theimperfectgame.com