Shortstops: Pirates vs. MLB (1997-2012)

Since we’ll be talking about the shortstop position for the next 24 hours in Pittsburgh, I thought I’d post a quick comparison between the offensive numbers of MLB shortstops and Pirates shortstops since 1997:

And, here is a list of the most common starting shortstop for the Pirates each year since 1997:

Link to “most common starters” Pirates from baseballreference.com

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Return on Investments: Comparing Pirates Player Salaries to the “Dollar” Metric

One of the topics on Pittsburgh sports radio this morning (“Vinnie and Cook Show”) was over-and-underpaid baseball players. They asked “which players were most over/underperforming relative to their salaries?” I looked for a statistical answer to that question, and applied it to the Pirates.

Method

  1. Gather the actual Pirates Opening Day salaries from baseballreference.
  2. Generate a report from Fangraphs.com which includes their “Dollar” metric. Dollar” is explained as follows: “the best description of the question that the valuation is answering is ‘how much would you expect to have to pay to replace this performance in free agency if you knew that you were going to get this level of value exactly?’” (Full explanation here.) It is important to note, this is NOT a salary predictor. It simply tells us what salary a player who generated X number of wins above a replacement player would likely fetch in a completely open free agent market. (Think of a replacement player as a so-called 4A guy – or Mario Mendoza, or Brian Bixler.)
  3. Prorate the actual salaries to 22% (36 games / 162 games)
  4. Subtract “Dollar” from the prorated salary to get the “Difference”

(Remember, Major League Baseball does not have a completely open labor market. High performing players with less than three years service times have their salaries controlled by their teams. After three years, players become arbitration eligible. I mention this because the “Dollar” statistic is built off the assumption of a completely open labor market that doesn’t exist. Also, it highlights the importance of drafting and developing young talent. If done well, teams should get good “value” from their younger players, which will be reflected in studies like this.)

Results

I’ve divided the roster between “Position Players” and “Pitchers.” Red means that the Pirates are “overpaying”; Black means they are getting more production than they are paying for – i.e. getting value.

Observations

The results are not very surprising (they shouldn’t be!). The Pirates are receiving a better return on their investments in pitchers than on position players.

Given current free agent market prices, the cost of 1 WAR worth of production is $4.5. Fangraphs.com estimates the number of wins for a team of replacement players (i.e. a team of Mario Mendozas or Brian Bixlers) at 48 games. So, to reach .500, a team will need about 33 additional WAR  - in the range of 148.5 DOLLARs. (Of course, luck can more or less affect a team’s actual record. So gaining 33 WAR may result in more or less actual wins.)

The challenge for small market teams is to maximize WAR/DOLLARs at the lowest possible salary. The Pirates are not paying much for position players – $2.6 so far this year – and they’re not getting many DOLLARs in return $3.5 (.7 WAR). The Pirates are paying more for Pitchers – $8.8 so far – and they’re getting a solid $14.9 DOLLARs (3.3 WAR) in return.

Another way of looking at this is as follows: For position players, the Pirates are realizing a 35% return on their investments; a 69% return on their investments in pitchers.

The numbers are much worse if you pull Andrew McCutchen out of the calculation. Without McCutchen, the Pirates would be receiving $-2.7 DOLLARs on their $2.5 salary investment, a loss of 208%

Conclusion

The Pirates did not invest much in position players for 2012. Roughly 76% of the money they are paying in salaries is going to pitchers. In other words, they are not paying for much additional offensive WAR. The money they are investing is not bringing the type of returns they will need to reach .500 (obviously).

The free agent signings are the biggest problem. The Pirates bought $13.24 worth of position players in the off season (Barajas, Barmes, McLouth, and McGehee). In a perfectly efficient market, that should result in roughly 3 WAR by the end of the season. That isn’t much additional WAR. Worse, they have already paid out $2.952 in salary to these four players this season, and received back $-4.5 DOLLARS, or -1 WAR; a loss of 252% on their investments so far.

The Pirates did invest more in pitching, and they are getting that value back, plus 69% more. Bedard has cost $1.0 so far, and has returned $4.7 DOLLARs (1.04 WAR), a 370% gain. While Burnett has not returned a gain on the investment in him, he is breaking even. At his high salary, breaking even means 3.6 WAR over the course of the season.

In the coming days I’m going to expand on this study. I am intrigued by this approach.

Take this for what it is – i.e. a snapshot early in the year. The season is only 22% complete, so obviously a lot is going to change. I find the results interesting, and they do provide an accurate description of where things stand, but we should keep everything in context.

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Thanks for stopping by

For lots of baseball tweets, consider following me on Twitter @Highoutsideball

Also, you might be interested:Pirates Baserunnig: Update 2″ ; “Return to Average: Week 5“; “Pirates “Core Four” Defense”; “Positional Comparisons by OPS”“Pens Goals vs. Pirates Runs: Through 32 Games”; “Pirates Baserunning” and “NL Sacrifice Bunt Attempts Compared (AKA #Hurdled).” 

Pirates Baserunning: Update 2

This is an update of a study I did 10 days ago in which I put the notion of poor Pirates Pirates Baserunning to the test.

The formula is: caught stealing 2b + caught stealing 3b + caught stealing home + pick offs + Outs on Base (caught advancing on a fly ball etc) / Plate appearances with Men on Base.

So, % of Outs = the percentage of baserunning outs made divided by plate appearances with men on base.

(baseballreference.com)

The Pirates are making an above NL league rate of outs on the base paths – second worse to only the LA Dodgers.

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Thanks for stopping by

For lots of baseball tweets, consider following me on Twitter @highoutsideball

Also, you might be interested in “Return to Average: Week 5“; “Pirates “Core Four” Defense”; “Positional Comparisons by OPS”“Pens Goals vs. Pirates Runs: Through 32 Games”; “Pirates Baserunning” and “NL Sacrifice Bunt Attempts Compared (AKA #Hurdled).” 

Runs Scored in Sacrifice and Non-Sacrifice innings

Earlier today I looked at the average runs scored per inning by the Pirates when they attempt a sacrifice bunt with a runner on second. This study compares the average runs scored in innings in which the Pirates sacrifice bunt, to those innings that they don’t.

Method

  1. Using baseballreference.com, calculate how many innings the Pirates have put a runner on base with less than two outs = 126 innings.
  2. Subtract the number of innings in which the Pirates have attempted a sacrifice bunt = 24 innings.
  3. Add up the number of runs the Pirates have scored in non-sacrifice innings. So, 100 total runs scored - 17 Solo HRs – 13 runs from 2-out, no one on (not a sacrifice opportunity) – 18 runs in sacrifice innings = 52 runs in non-sacrifice innings
  4. Divide the number of runs scored in non-sacrifice innings by the total number of non-sacrifice innings . So, 126 total innings – 24 sacrifice innings = 102 non-sacrifice innings. Then 52 non-sacrifice related runs / 102 non-sacrifice innings.
  5. Divide the number of runs scored in sacrifice innings by the number of sacrifice innings. So, 18 sacrifice runs / 24 sacrifice innings (A solo

Results

The Pirates are averaging more runs in innings in which sacrifice bunt.

Caveats

This involved a lot of number crunching, and the reading of a lot box scores, so it is possible an error or two crept in. I’ve checked the numbers over a few times, so my confidence is high. I’ll recheck if someone finds an error.

Also, remember this is a small sample size. These results, alone, should not be used to defend/attack Clint Hurdle’s bunting tactics. Sacrifice bunts are undoubtedly a run-losing strategy in the long-term, but there are situations where it is warranted. It is best to take this as an intrinsically interesting result, and an issue worth paying attention to.

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Thanks for stopping by

For lots of baseball tweets, consider following me on Twitter @highoutsideball

Also, you might be interested in “Return to Average: Week 5“; “Pirates “Core Four” Defense”; “Positional Comparisons by OPS”“Pens Goals vs. Pirates Runs: Through 32 Games”; “Pirates Baserunning” and “NL Sacrifice Bunt Attempts Compared (AKA #Hurdled).” 

#Hurdled: Sacrifice Bunts w/ Runner on 2nd

First, a few disclaimers: Small Sample size Alert – the data below is much too small of a sample to say anything conclusive about anything. That is not the point, anyways. The results presented here are just meant to enrich the narrative of the season, and explain to us what has happened so far.

Context

Many Pirates fans are upset with Clint Hurdle’s overuse of the sacrifice bunt tactic this season. (I originally studied that topic here.) Last night the howls rose again when Hurdle had Barmes bunt, with Barajas on 2nd, in the 7th inning. Barajas ended up being forced out at third. Pat Lackey, of the very popular Pirates blog WhyGavs, expressed the anger of many Pirates fans with the overuse of the sacrifice bunt in a post that you all should read (follow him on Twitter @whygavs).

Last night’s play, and the reaction it sparked, got me interested in not only how many times Hurdle has deployed this tactic, but also how successful it’s been this season. Last night it clearly failed, but has that been the case all year?

What I did

I executed this search at Baseballreference.com - “Plate Appearances in 2012, less than 2 outs, up 2 runs, up 1 runs, score tied, down 1 runs or down 2 runs and With runners on second.”

I separated out all the innings in which a sacrifice bunt attempt was made with a runner on 2nd, less than 2 outs, and added up the total runs scored in that inning. Then, I counted up the runs scored in the innings that the tactic was not used in the same situation. Below are the results.

(Pirates have scored in four of the six innings in which they’ve used the sacrifice bunt; 11 of the 29 innings that they haven’t.)

Result

Innings in which the Pirates have employed the sacrifice bunt with a runner on 2nd, less than two outs, has yielded more runs per inning than innings in which it was not used.

Reminder

Please remember this is a small sample size. These results should not be used to defend Clint Hurdle’s bunting tactics. It is very likely a run-losing strategy in the long-term. It is best just take this as an intrinsically interesting result, and an issue worth paying attention to as you watch games.

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Thanks for stopping by

For lots of baseball tweets, consider following me on Twitter @highoutsideball

Also, you might be interested in “Return to Average: Week 5“; “Pirates “Core Four” Defense”; “Positional Comparisons by OPS”“Pens Goals vs. Pirates Runs: Through 32 Games”; “Pirates Baserunning” and “NL Sacrifice Bunt Attempts Compared (AKA #Hurdled).” 

Return to Average: Week 5

This is the fourth week I’ve tracked the Pittsburgh Pirates offense relative to NL average (herehere and here). (I started tracking after the second week.)

It is important to compare the Pirates offense to league average because it is likely that their pitching/defense is only slightly better than league average. If they hope to win 75-85 games this year, they are going to have to score something close to a league average number of runs.

This week I again compare the Pirates’ runs scored to NL Avg. However, I will now  track Runs Allowed to 90% of NL Avg. There are three reasons for tracking runs allowed, and for tracking it at this lower rate:

  1. It is becoming increasingly unlikely that the offense will come within 5% of NL average runs. If the Pirates are going to end up close to 80 wins, they’re going to have to allow (well) below NL average number of runs per game.
  2. If the offense were to have stunning turnaround, allowing only 90% of league average runs would make them a pennant contender
  3. League average runs allowed would be a disappointment at this point. Expectations are that they will remain, at least, slightly below NL Avg. To finish 90% league average would be special accomplishment for the staff, even if the offense never comes around.

This week’s numbers:

Offense

The Pirates played six games this week and scored 19 runs – an average of 3.16 RS/G. They raised their season RS/G to 2.85, from 2.80. Last week they needed to average 4.35 runs to reach NL average by the end of the season. That number has increased to 4.41. In other words, the Pirates offense will have to score at a rate of 8% above NL average for the rest of the season in order to reach a NL average number of runs.

  • Blue = The average RS/G for the week.
  • Red= The average RS/G for the season
  • Green = The number of RS/G the Pirates will have to score in order to reach league average.

(Click to Enlarge)

Pitching/Defense

The Pirates played six games this week and allowed 15 runs – an average of 2.50 RA/G. They decreased their season RA/G to 3.50, from 3.71. Last week they needed to average 3.81 runs allowed to remain below 90% NL average by the end of the season. That number has increased to 3.86. In other words, the Pirates pitching/defense will have to give up 5% less runs than NL average for the rest of the season remain below 90% league average RA/G.

Pythagorean Record

Each week I’m going to update the Pythagorean record of the Pirates based on two scenarios:

  1. Pirates offense scoring NL average runs; and the defense allowing its actual average runs
  2. Pirates defense allowing NL average runs; and the offense scoring its actual average runs.

This really gives you a sense how much pitching/defense is sustaining this team.

Weekly Observation

The Pirates only scored 19 runs, and yet won four out of six games this week. They could very easily have won five games if they had cashed in one of their many scoring opportunities Friday night.

The pitching/defense had a bounce back week – having allowed 5.85 RA/G last week. McDonald and Burnett put together two excellent starts, 14 IP 2 Runs and 16 IP 4 Runs respectively. But perhaps the most significant performance of the week was Wednesday night – after Bedard got injured, the bullpen carried the team to a win by giving up only 2 runs in 8 IP.

Finally, I think something should be said about Pedro Alvarez’s play at 3B. He made some errors again this week, but he also showed good range – making a series of difficult plays. While his offense fell off a bit this week, he saved a few hits with his glove. (For a look at the defensive evolution of the Pirates’ “Core Four”, go here)

That’s it for this week. We’ll see where things stand next Sunday after the Pirates visit Miami, Washington and Detroit. (Actually, more likely Monday, as I’ll be in Detroit for that series and driving home Sunday evening.)

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Thanks for stopping by.

For lots of baseball tweets, consider following me on Twitter @highoutsideball

Also, you might be interested in “Pirates “Core Four” Defense”; “Positional Comparisons by OPS”“Pens Goals vs. Pirates Runs: Through 32 Games”; “Pirates Baserunning” and “NL Sacrifice Bunt Attempts Compared (AKA #Hurdled).” 

Pirates’ “Core Four” Defense

I started to think a lot about defense last night after watching Pedro Alvarez make some nice, “rangy” plays in the last two games. In particular, I became interested in the defensive development of the so-called “Core Four” – i.e. McCutchen, Walker, Tabata, and Alvarez.

While it is way too early for this season’s defensive numbers to be taken too seriously in terms of predictive value, they do give us a snapshot of how well they’ve performed so far. In other words, they confirm what we’re seeing with our eyes, but they shouldn’t be taken as stable or predictive yet.

Three years of defensive data are usually needed to make strong statements about a player’s “true” fielding talent. For three of the “Core Four” we’re approaching that three year mark (McCutchen is at four years), so I thought I’d take a quick peek at their evolution so far.

Below are two sets of data: UZR/150 and RngRRoughly, UZR/150 looks at total defense (range, errors, arm) and expresses its results in total runs saved/allowed. It is weighted to 150 games played so that each player is placed on a similar scale. RngR just looks at “range” – the ability to get to balls hit into a defender’s zone. It too is expressed in runs saved/allowed. (Negative numbers = runs given up above average; positive runs = runs saved above average.)

UZR/150

Four observations:

McCutchen is worth watching this year. After two years of below average performance in CF, he saved runs last year. This year, perhaps due to the flu that has bothered him, he is performing below average again.

Walker is showing steady improvement at 2b

Pedro’s defense has dipped so far this season, but as we’ll see in a moment, that is due largely to errors – throwing errors in particular. He has the most throwing errors in the league.

Tabata is proving to be average, to slightly below average defender

Range

Three Observations:

What interests me most here is Pedro’s range. We’ve all seen him show some impressive mobility the last few nights, and the numbers reflect his overall improved play in that regard this season. Errors still haunt him, but he is proving to have much better instincts and quicker body control than I thought he’d have. If he smooths over his rough edges in terms of errors, he may be just fine at 3b.

Walker again is showing steady improvement in terms of range. It is early, but if his UZR and RngR numbers hold steady, we are going to be able to say that he is becoming a very serviceable defensive second baseman. That is very important, because offensively he looks to be just about league average. If the Pirates end up with an absolute league average second basemen, I think they’ll be happy.

Keep an eye on McCutchen: We all think he is going to be an elite defender, but the numbers just aren’t there yet. I’m really interested in watching his defense season.

Tabata is going to need to become an above-average offensive player. His defense is probably not going to be anything special.

(All data from fangraphs.com)

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Thanks for stopping by.

For lots of baseball tweets, consider following me on Twitter @highoutsideball

Also, you might be interested in “Positional Comparisons by OPS”“Pens Goals vs. Pirates Runs: Through 32 Games”; “Pirates Baserunning” and “NL Sacrifice Bunt Attempts Compared (AKA #Hurdled).” 

Finally make sure to check back later tonight for Update 4 in the series “Pirates: Return to Average”

Positional Comparisons by OPS / Clutch Hitting

Quick comparison between Pirates positional players and the rest of the MLB, by OPS.

Same thing in bar graph form:

Finally, there as been a lot of talk over the last 12 hours about the Pirates lack of “clutch” hitting last night. Here is a quick look of all NL teams clutch hitting this year.   The data is from Fangraphs.com, and they define their “clutch” stat as follows: “Clutch: A measurement of how much better or worse a player does in high leverage situations than he would have done in a context neutral environment.” (rest of post here)

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Thanks for stopping by.

For lots of baseball tweets, consider following me on Twitter @highoutsideball

Earlier post from today “Pens Goals vs. Pirates Runs: Through 32 Games” 

Also, you might be interested in “Pirates: Return to Average”, “Pirates Baserunning” and “NL Sacrifice Bunt Attempts Compared (AKA #Hurdled).” 

For the historical minded, you might be enjoy an ongoing project I’m working on that looks at the positional history of the Pirates via the WAR statistic. Here is the latest post on Pirates’ first basemen – “War of Positions: Pirates’ First Basemen” (note: there is a methodological issues with this study that I’m going to work out. It doesn’t affect the results too much, but I’m still going to have to clean it up.)

Finally, my Team Defense Tool (TDT): The Total Defense Tool (TDT) estimates AL and NL standings based purely on different aspects of team defense. For example, it can be used to estimate what the league standings would look like if every team was league average, in every respect, except for the total fielding performance of its position players (range + errors).

Pens Goals vs. Pirates Runs: Through 32 games

The Pirates offense is THE topic of baseball conversation around Pittsburgh. It has been awful, and it is threatening to become truly historically awful.

The ineptitude of the offense has been concealed by good pitching. If Pirate pitchers were allowing a NL average number of runs per game, the Pirates Pythagorean Win-Loss record would be 10-22.

There will be plenty of comparisons between the 2012 Pirates and other historically terrible offenses in the coming weeks. Rather than add to those, I thought I’d look outside of baseball, to a sport in which scoring is decidedly more rare, i.e. hockey. (Silly comparison I know, but silly times call for silly analysis.)

The Pirates are scoring less runs/per game (2.78) than the Penguins averaged goals/game all season (3.33). In fact, The Pirates are averaging less runs than nine hockey teams averaged goals this season.

The last time the Penguins averaged more goals in a season than the Pirates averaged runs was 1995-1996. That season the Pens averaged 4.41 G/Gm and the ’95 Pirates averaged 3.88 R/Gm.

Every Pens team since 2004-2005 averaged more goals in a season, than the 2012 Pirates have averaged runs.

Finally, over their first 32 games than the Pens averaged more goals (3.09) than the Pirates have averaged runs. (click to enlarge)

Still the best park in the land, though.

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Thanks for stopping by.

For lots of baseball tweets, consider following me on Twitter @highoutsideball

Also, you might be interested in “Pirates: Return to Average”, “Pirates Baserunning” and “NL Sacrifice Bunt Attempts Compared (AKA #Hurdled).” 

For the historical minded, you might be enjoy an ongoing project I’m working on that looks at the positional history of the Pirates via the WAR statistic. Here is the latest post on Pirates’ first basemen – “War of Positions: Pirates’ First Basemen” (note: there is a methodological issues with this study that I’m going to work out. It doesn’t affect the results too much, but I’m still going to have to clean it up.)

Finally, my Team Defense Tool (TDT): The Total Defense Tool (TDT) estimates AL and NL standings based purely on different aspects of team defense. For example, it can be used to estimate what the league standings would look like if every team was league average, in every respect, except for the total fielding performance of its position players (range + errors).

(Work in Progress) Expected Wins based on Strength of Schedule

I came up with this late last night, and I don’t know what to make of it. I’m posting it here to let you decide its value, and whether it is worth continuing to work on. I apologize if it is a little sloppy – remember this is a first draft.

I want to know how how a team’s record should be judged in light of the strength of the schedule they’ve played. The idea was inspired by the fact that the Pirates have played the toughest schedule in the MLB so far this season (see baseballref.com). I want to get an idea if the Pirates’ record is above or below what we could expect from average team playing the same schedule.

Here is what I did: Table 1 (below)

  1. Compile a list of the Pirates’ opponents, and input their record against the Pirates. (first two columns)
  2. Calculate each team’s record against teams other than the Pirates.(columns 3 and 4.)
  3. Calculate aggregate Win% for each team against teams other than the Pirates. (column 5.)
  4. Weight the Win% of Non-Pirates wins so that teams that have played the Pirates more, count for more.((Games against Pirates/total Pirates games)*Win% against Non-Pirates)) (column 6.)

Table 2 (below)

  1. Take the “Weighted Non-Pirates Win%” of the teams the Pirates have played, and transform into the “Weighted League Win %” for teams that have played against the Pirates’ opponents. It sounds much more confusing than it is. Simply, how often have teams beaten the teams the Pirates have played, weighted. (second column)
  2. Take the “Weighted League Win%” of teams that have played against the teams the Pirates have played, and multiply it by the number of games played by the Pirates. This gets us “Expected League Wins” against teams the Pirates have played. (Opp of opp wWin%*30) (3rd column)
  3. Compare the “Expected League Win%” and “Expected League Wins” with Pirates actual Win% and total Wins. (columns 6 and 7)

Interpretation

If the Pirates winning percentage is higher than the “Expected League Win%”, then the Pirates are playing above average league expectations, based on the strength of their schedule. If below, they are below the average league expectation. (I’m not sure about the terminology yet.)

So, If we look at the table above, once we do the proper rounding up, the Pirates are right at league average expectation.

Now, this method of calculating expected wins will likely work better over longer stretches (I tested the 2011 Blue Jays and got interesting results). When I used it on the 2012 Tigers, I found them to be right at league average too; which, given their expectations for the season, is probably not where they want to be.

Like I mentioned in the opening paragraph, I came up with this just last night and I haven’t thought through it completely. If you have any suggestions please send them my way. If I decide that this approach is not of much use, it may disappear.

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Thanks for stopping by.

For lots of baseball tweets, consider following me on Twitter @highoutsideball

Also, you might be interested in “Pirates: Return to Average”, “Pirates Baserunning” and “NL Sacrifice Bunt Attempts Compared (AKA #Hurdled).” 

For the historical minded, you might be enjoy an ongoing project I’m working on that looks at the positional history of the Pirates via the WAR statistic. Here is the latest post on Pirates’ first basemen – “War of Positions: Pirates’ First Basemen” (note: there is a methodological issues with this study that I’m going to work out. It doesn’t affect the results too much, but I’m still going to have to clean it up.)

Finally, my Team Defense Tool (TDT): The Total Defense Tool (TDT) estimates AL and NL standings based purely on different aspects of team defense. For example, it can be used to estimate what the league standings would look like if every team was league average, in every respect, except for the total fielding performance of its position players (range + errors).