Part 2: How to Predict Postseason Success in Baseball

Wouldn't it be nice to predict the next time your team will hoist the Commissioner's Trophy?

While Part 1 looked at driving in runs without hitting home runs, the second hypothesis has more to do with hitting the league's most elite pitchers in the postseason. Will this hypothesis lead to some statistically significant results?


Performance Against Top Pitchers

Hypothesis

Against top-line starters and relievers, it is very difficult to hit home runs, so my theory is that teams that have a more simplistic batting approach will have a better opportunity against these very good pitchers. Also, because a team is very likely to face great pitching in the postseason, I also hypothesize that teams that face good pitchers (I have categorized “top pitchers” as those who finish in the top 20 of ERA minus, or ERA-, as calculated by Fangraphs) more often and/or have more success against them (in terms of runs scored per nine innings) are more likely to have playoff success.

Results

By hand, I compiled the top 20 starting pitchers in terms of ERA- every year from 2003-2012, and then used Baseball Almanac to record every game these pitchers played against teams who made the playoffs that year. I compiled total innings, total runs scored, total games and runs scored (not just earned runs) per 9 innings for each team each year. The reasoning behind looking at all runs, and not just earned runs, was because runs of any kind are so hard to come by in the postseason, or when facing a top pitcher, and even if a run is unearned, most of the time the opposing team would still need to string together a couple of hits to allow that unearned run to score.

When I finished compiling data on team performances against top 20 pitchers, I ran individual regression analyses with PV being the outcome variable, and these new statistics being the predictors. However, no single statistic correlated to having a high PV. Even when using multiple predictors with the top 20 pitching stats, there was still no significant correlation.

Conclusion

Based on the results of my tests of these two hypotheses, I unfortunately did not find any significant regression models that could predict PV from any of these statistics, I was not hugely surprised by this outcome for a few reasons. Because I only looked at playoff teams in the past ten years (many of the statistics I used in these models were not compiled before then), my sample size was smaller than ideal to start with. Also, there is high multicollinearity among so many of these statistics. This means that it was it was difficult to interpret the individual coefficients.

Also, having too many predictors, or controlling for too many variables, makes it extremely difficult to find a model that is both significant, and that makes sense from a baseball perspective. There were a few interesting findings, such as how LDp is marginally correlated with playoff wins (but not correlated with playoff series wins), but for the most part, no major discoveries were made.

Possible Improvements

One of the changes I could have made included how I calculated the top 20 pitchers statistics. I chose the number 20 randomly, but I also compiled the top 20 pitchers regardless of league. In hindsight, I probably should have compiled the top 20 pitchers from both the American and National Leagues in each year. Also, maybe there is a better statistic than “runs per 9 innings” to gauge how well teams do against these top pitchers. Also, when my second hypothesis failed, I started to compile 28 new statistics from Fangraphs’s “high leverage situations” split. I originally tried this because essentially all playoff batting situations can be considered “high leverage.”

However, these statistics were compiled from late and close game situations, rather than ability to drive in runs without hitting home runs, which is what my two hypotheses were related to. My time might have been better spent looking at statistics with runners in scoring position. Those kinds of statistics would have been more relevant to my hypotheses, as driving in runners in scoring position is not only the most effective way to score off top pitchers, but it is also a skill that requires the batter to shorten his swing, and have a more simplistic batting approach. As I continue this research in the future, I will take into account all of these factors in my quest to find a formula for postseason success in Major League Baseball. 

Batting Leadoff: Extensions As A Market Efficiency

This post originally appeared on Batting Leadoff. Batting Leadoff is a website dedicated to providing readers with premium baseball content. Posts from the site will appear regularly on the Sports Business Society Blog (view the information in the sidebar for updated information).

We all know that teams are loaded with cash right now. Thanks to a large and steady stream of revenue due to new TV deals, teams have been ready to spend big at free agency. That was obvious this offseason: Robinson Cano, Shin-Soo Choo, Jacoby Ellsbury, and Brian McCann can all call themselves very rich men after their contracts were inked. But not all teams can afford that kind of commitment, and even teams that can, can’t make that the order of the day.

The two teams that are shining examples of this are the Atlanta Braves and Los Angeles Dodgers. The Braves are stuck with a horrid TV deal and poor stadium (that they are leaving), and the Dodgers are the opposite; they’re rolling in dough and are willing to pay a premium for any quality player out there. Despite their financial differences, both have decided to utilize contract extensions as a key feature of their payroll allocation.

They together have extended Julio Teheran, Freddie Freeman, Craig Kimbrel, and Clayton Kershaw, and have locked up their stars for quite a number of years. But how much did they save as opposed to market value and arbitration? Let’s take a look.

To examine this, we’ll look at some basic projections for these players against what market value and projected arbitration salaries would be. For argument’s sake, I’ll use the player’s projected arbitration salary as the projected salary for 2014, and approximately then using an approximate 40/60/80 rule (thanks for the tip, Max Fogle) to figure out an estimate of their salaries going forward.

Those are the hardest to estimate because of inflation and the fact that this rule isn’t perfect in estimation, but I just made an estimation using that rule and my only interpretation of their value. And for free agency, I’ll assume that the market value is $5.5 million per WAR with a 5% inflation rate each year.

Clayton Kershaw:

Year	Projected WAR	Arbitration/Market Value (in millions)	Actual Salary (in millions)
2014	5.8	$18.25	$4
2015	5.8	$33.5	$30
2016	5.3	$32.1	$32
2017	5.3	$33.7	$33
2018	5.3	$35.4	$33
Total	27.5	$152.95	$132

Amount of money saved: $20.95 million, worth about 3.13 WAR in 2018.

Freddie Freeman:

Year	Projected WAR	Arbitration/Market Value (in millions)	Actual Salary (in millions)
2014	4.5	$4.9	$5.1
2015	4.5	$8	$8.5
2016	5.0	$11	$12
2017	5.0	$33.4	$17
2018	5.0	$35.1	$21
2019	4.5	$33.1	$21
2020	4.0	$30.9	$22
2021	3.5	$28.4	$22
Total	36	$184.8	$135

Amount of money saved: $49.8 million, worth about 6.15 WAR in 2021.

Julio Teheran:

Year	Projected WAR	Arbitration/Market Value (in millions)	Actual Salary (in millions)
2014	3.0	$.49	$0.8
2015	3.5	$.49	$1
2016	4.0	$4.6	$5.3
2017	4.5	$6.9	$6.3
2018	4.5	$9.2	$8
2019	4.5	$33.2	$11
Total	24	$54.9	32.4

Amount of money saved: $22.5 mil, worth about 2.2 WAR in 2019.

Craig Kimbrel:

Year	Projected WAR	Arbitration/Market Value (in millions)	Actual Salary (in millions)
2014	2.0	$7.3	$7
2015	2.0	$8.5	$9
2016	2.0	$10.5	$11
2017	2.0	$13.4	$13
Total	8	$39.7	$42

Amount of money saved: -$2.3 mil, worth about 0.36 WAR in 2017

As you can see… the Dodgers and Braves will save a lot of money, unless a tragedy were to strike one of these players. My projections are pretty simplistic–just based off of the basic aging curve and estimations of arbitration–but they make a valid point. Free agency is expensive, and teams should not always have to resort to that, especially when it’s their own player.

Teams have the ability to have sole bargaining rights and players often are forced to take a “hometown discount” because–who knows if they’ll still be good by the time they hit free agency! Teams also will save the most money with starting pitchers and position players–it’s much harder to bargain down an excellent reliever. And granted, I split projections on Kimbrel due to the unpredictability of relievers, so although it is a loss, it will more likely be closer to a split-even.

It’s pretty obvious what the conclusion is. Teams are able to structure extensions in such a manner that they can: still pay the same amount during arbitration, avoid a bidding war for their prized players, and likely underpay what will be the market value by that current year. They then can take that extra capital and reinvest it into other areas of the team. It’s all part of how a team can diversify the ways in which they invest in their own team; extensions can be a nice middle ground between the draft and free agency.

Teams like the Dodgers who can afford big contracts can still avoid them, and teams that can’t afford free agency can find a way to provide some stability and retain their homegrown talent–it’s no wonder the Braves have been so good for so long. I fully expect teams to continue to implement this strategy, especially with players of elite quality.

Matthew Provenzano is a sophomore at Cornell University. Matthew is a featured blogger at Batting Leadoff, a contributor for PinstripeAlley.com, and covers Cornell Baseball for Cornell At Bat. Contact Matt at mjp294@cornell.edu or follow him on twitter at @mpro6294.

This post originally appeared on Batting Leadoff. Batting Leadoff is a website dedicated to providing readers with premium baseball content. Posts from the site will appear regularly on the Sports Business Society Blog (view the information in the sidebar for updated information).

The Weekly Rant: Starting Pitching Market Trends

 

The offseason is finally winding down, with just a few significant free agents still out there. The highest upside players available are mostly starting pitchers.  While Kendrys Morales, Stephen Drew, and Nelson Cruz are still unemployed, the real impact players left are Ubaldo Jimenez, Ervin Santana, and AJ Burnett.

Some may have anticipated the sluggers waiting on the market, but the high quality starting pitching for hire is surprising.  Burnett has always been in control of his market, so the choosy 36-year-old looking for the perfect one-year deal isn't really an indicator of the market.  But youngish, goodish, durable guys like Jimenez and Santana should have signed their lucrative deals by now, right?

I mean these were pitchers who were close to the top on most people's free agent rankings.  Among the 18 domestic pitchers in MLBTR's Top 50 Free Agent rankings, Santana and Jimenez were ranked No. 1 and No. 5 respectively.  And with older hurlers Kuroda and Burnett ahead of him, the up-and-down Jimenez was actually in-line for the third largest contract among free agent pitchers.

There's a couple reasons why they are still out there.  The obvious reason is they haven't received a contract offer they like.  The big reason why they haven't gotten that kind of offer yet (or why they never will) is because of the Masahiro Tanaka sweepstakes.  Tanaka split the market for starting pitchers into two segments. You either signed before he got posted, or you signed after he did.  No major league deals with starters went through while the Tanaka drama was unfolding. Check out the flurry of activity and then the long gap:

Dec. 3:  Ricky Nolasco signs with the Twins.
Dec. 4:  Scott Kazmir signs with the A's.
Dec: 5:  Phil Hughes signs with the Twins.
Dec. 6:  Scott Feldman signs with the Astros.
Dec. 7:  Hiroki Kuroda signs with the Yankees.
Dec. 14: Bartolo Colon signs with the Mets.
Dec. 16: Posting System Agreement is reached.
Dec. 26: Masahiro Tanaka is posted.
Jan. 22:  Tanaka signs with the Yankees.
Jan. 26:  Matt Garza signs with Brewers.

Obviously teams weren't going to keeps signing players at the rate they did leading up to the winter meetings (or else everybody would have been signed in 45 minutes), but there's no denying it held everybody up. Besides the actual process surrounding Tanaka, the uncertainty of his availability (along with Burnett's more recent drama) also had an effect on the market.

Now I can't prove that the presence of Tanaka will actually reduce the money other starters receive (I think it will a little, especially for a guy like Santana, who the Yankees may have been in on.).  But it definitely pushed the market back about a month.

I decided to take a look at the contracts starting pitchers were projected to sign, compared to the contracts they actually did sign.  I used the previously mentioned Top 50 Free Agent list from MLBTR, and used the predictions from their various free agent profiles of starting pitchers.  I left off Tanaka, Suk-Min yoon, Jason Hammel, and Roy Halladay. These are predictions made by industry experts, and while they are not perfect, they are pretty good.

Rank	Name	Projected		Actual
		Years	Total $	Years	Total $	Date
1	Santana	5	75
2	Garza	4	64	4	50	26-Jan
3	Kuroda	1	16	1	16	7-Dec
4	Burnett	1	12
5	Jimenez	3	39
6	Kazmir	2	16	2	22	4-Dec
7	Nolasco	3	36	4	49	3-Dec
8	Colon	1	10	2	20	14-Dec
9	Arroyo	2	24	2	23.5	10-Feb
10	Feldman	2	17	3	30	6-Dec
11	Johnson	1	8	1	8	20-Nov
12	Hudson	1	9	2	23	18-Nov
13	Haren	1	10	1	10	25-Nov
14	Vargas	3	28.5	4	32	21-Nov
15	Hughes	1	8	3	24	5-Dec
16	Maholm	1	7	1	1.5	8-Feb

You can see there are some notable discrepancies.  There are also a few that are right on.  Remember, some of these deals have important non-guaranteed elements, such as vesting options (Garza or Haren) or incentives (Maholm). Draft pick compensation will also be important to consider when Jimenez and Santana sign.  But there is still a lot going on in this data.

I decided to look at the date the contracts were signed.  This graph has the difference between the total value of the actual contracts and the total value of the projected contracts for each player on the y axis, and the date each player signed on the x axis (It's recorded as "days after Nov. 1", so that January 1= 61 days.)

Overall, the predictions were low (the new TV contracts likely resulted in double digit salary inflation). But the graph really looks like two sets of data when organized like this.  It's pretty clear where the Tanaka sweepstakes took place.  But the difference between the early and late contracts is pretty striking.

At the beginning of the offseason players were getting the same or more in average annual value or years, or both, than they were expected to.  The three domestic starting pitchers to sign in 2014 have all gotten the same or less in all of those categories.  Now this might change a little. If Burnett is really testing the market, he will likely get more than $12 MM.  And, Jimenez should still be able to land north of $39 MM. 

But Santana will probably come in at way under $75 MM.  And you could add another data point in the early signers column if we included Tim Lincecum.  His 2-year, $35 MM contract certainly blew away expectations, and may have been what set the bar so high, at least early in the offseason.

Overall, it seems this year that if pitchers signed early in the offseason, they earned more than expected. For guys signing later in the offseason, (It's only three guys so far), things don't seem so good.  Looking at it from the team perspective, adding your rotation help early didn't generally result in any savings.  It has certainly been an interesting free agent period for starting pitching, and it's not over yet.

Batting Leadoff: Marginal Win Value and Dollars Per Win

This post originally appeared on Batting Leadoff. Batting Leadoff is a website dedicated to providing readers with premium baseball content. Posts from the site will appear regularly on the Sports Business Society Blog (view the information in the sidebar for updated information).

It is quite natural to spawn opinions on offseason moves that eventually manifest into conclusions that the general manager of Team A is a moron for signing Player B to Contract X. No matter our qualifications or level of knowledge of baseball, there are multiple times per winter us fans are left with the notion that yes, we absolutely have to be smarter than the GM of Team A.

What we do not take into consideration is that within every front office in Major League Baseball, there are dozens of bright analytical and scouting minds who are far more conversant than us. Their scouts can see how one player’s bat speed may be diminishing. Their analytical department knows how a free agent’s skill set will fit in their ballpark far better than we do. Their doctors have medical reports on players that we could only dream of seeing.

The information accessible to these bright minds is far more than we can find on MLB.TV, Fangraphs, and Baseball-Reference. Essentially, front offices make educated decisions dependent on a wealth of knowledge that the public lacks.

There are a multitude of factors that drive every transaction. The Mariners did not invest $240 million dollars in Robinson Cano because they thought he was a pretty damn good second baseman. Inside that decision came scouting insight, statistical analysis, and economic evaluation that indicated it was sensible for the Mariners to blow every single team in the market out of the water.

Of course, there are rudimentary differences in each front office’s valuation of every player. If each team valued every player equally, the market would be far different. Some teams put more weight into the scouting aspect of evaluations, while others rely on regression models to project players forward. Another large factor that is not touched on nearly enough is the marginal value that each player provides his employer.

For a number of years, analysts have looked at the contracts signed by free agents, quantified the value of the free agent, then depicted how much money the market demanded for a single Win Above Replacement ($/WAR). This number has risen annually for the past decade for reasons such as inflation and an influx of TV money among others.

The number for this off-season’s contracts was generally pegged at $6 to $7 million dollars per win. That is to say that if a team is going to sign a player who has consistently posted 2 WAR seasons (league-average), the market values him at around $13 million per season. These numbers are pretty consistent with how the market has played out so far.

However, the money per win valuation has numerous caveats that must be considered. First of all, $/WAR is not a good way to project salaries among elite players. As godly as he is, it’s unlikely that the 10-WAR man Mike Trout would be paid $70 million per year if he were on the open market. Robinson Cano posted a 6 WAR season in 2013, meaning if the market always held true, he would have found a contract that paid him an AAV of around $40 million dollars.

The second caveat is that while WAR is an extremely useful and powerful tool to evaluate players, front offices look far beyond that metric while putting a dollar sign on the value of a player. Another caveat, one which I find most interesting, is that a win is worth a different amount to every team. This in a nutshell is marginal win value.

The basic concept of marginal win value goes like this: a team filled with AAA players wins about 47 or so games in the major leagues while costing around $12 million dollars. From 47 wins on, the team is buying wins in hopes of accruing more revenue from being good. However, if the team buys one win at the market rate of $7 million dollars, the revenue added from increasing their win total from 47 to 48 is worth far less than $7 million dollars. From 47 wins on, it takes marginal analysis to decide if buying more wins is profitable for the team.

A single win carries far different value for teams who are on opposite sides of the spectrum. Several extremely smart people such as Phil Birnbaum and Nate Silver have looked at the marginal win value curve, creating the following graph to depict its true worth.

(Click to enlarge)





This graph is from 2005, so it is fairly outdated. In 2005, Silver found a win to cost around $2 million on the open market. To adjust to inflated contracts and revenue, we would simply raise the graph’s Y value to equate it to today’s contracts, keeping the shape consistent. The graph shows that it is an inefficient allocation of money to keep buying wins from around 60-85. This makes sense because barring a team slipping in one of the wildcard slots, it’s unlikely a team makes the playoffs with 85 wins.

However, the theory states that at 86 wins, the value of the revenue a team makes from extra ticket sales or whatever revenues are driven by playoff excitement begins to exceed the money you are paying for a win. Looking at the graph, you can see that you acquire surplus value buying wins from 85-95 because the marginal value is higher than the $2 million dollar cost of a win in 2005. From 95 on, the value decreases due to the fact that you likely have the division title in the bag and spending money to win upwards of 100 games is rather gluttonous.

There are uncertainties when using marginal win value to dictate your offseason. It is extremely hard to project how many wins a player is worth, especially with the volatility of pitchers or injury-risk players. That, along with other possible variations, makes it extremely difficult for a team to forecast its win totals while entering a season.

The standard deviation between true talent and performance is about six wins in the best projection models, meaning that a team with the talent of an 81 win team could win anywhere from 75 to 87 games. That being said, marginal win value is absolutely something that front offices take into account when deciding if it is profitable to keep spending on their club.

In Part 2, I am going to take a look at some of the most questionable moves that were made this offseason, and try to find each front office’s motives behind the moves. While marginal win value is going to play a large role in this exercise, I’m also going to use a number of other explanations to decipher why these transactions were made.

A lot of this piece was made possible by the fantastic work of people such as Dave Cameron, Lewie Pollis, Phil Birnbaum, and Nate Silver. These articles are fantastic reads and quite informative. Special thanks to Matt Swartz for the correspondence and help in equating Silver’s 2005 graph to the inflated contracts of this offseason. 

This post originally appeared on Batting Leadoff. Batting Leadoff is a website dedicated to providing readers with premium baseball content. Posts from the site will appear regularly on the Sports Business Society Blog (view the information in the sidebar for updated information).

Daniel Schoenfeld is a senior in high school in Evanston, Illinois. He plans on studying business economics while pitching in college next year. He is interested in scouting and statistical analysis, and hopes to use Batting Leadoff as a platform to break into the industry. He’s currently working on a large scale project detailing the indicative factors involved in injury projection of pitchers and is always willing to learn and share. Contact him at dschon711@aol.com and follow him @DanielSchoe. 

The Weekly Rant: Possible Outcomes of the Tanaka Deal

Masahiro Tanaka's contract with the Yankees has gotten a lot of attention already.  Dave Cameron at Fangraphs had a nice overview of it.  I wanted to look more in depth at the specific possible outcomes for the deal.

The contract is interesting for reasons besides being one of the largest ever for a pitcher, at 7 years, $155 MM. (There's some disagreement on how to rank the pitcher mega-deals. MLBTR's Tim Dierkes has a great read on how they should be analyzed.) The contract also includes a $20 MM "release fee" and an "opt-out" after four seasons. Here's how the contract breaks down cost-wise with and without the "opt-out":

Years Cost Cost/Year w/ opt-out 4        $108 MM $27 MM w/o opt-out 7        $175 MM $25 MM

It's a ton of money either way.  The Yankees are going to be seriously hoping Tanaka opts-out though. The reason is that it is nearly impossible to imagine a situation where Tanaka both a) does not pitch well in his first four seasons and does not exercise the opt-out and b) pitches well enough in years 5-7 to be worth $67 MM.

Even if salary inflation bumps the value of 1 WAR over $9 MM by 2020 (Year 7), Tanaka would need to put up 2.5 WAR per season over years 5-7.  If he's likely to produce at that level, he will have just opt-out.  Overall, this deal would be pretty terrible if for the Yankees if Tanaka doesn't opt out.

Let's say he averages 2 WAR per year over the entire 7 seasons.  Maybe a little above 2 WAR for his 4 younger seasons and a little below for his 3 older seasons.  That's not great production, and not what the Yankees are expecting, but it's also not a complete bust. And let's assume some significant salary inflation, so that the overall $/WAR rate over the contract's duration is $8 MM/WAR. Here's how the contract would look:

Total	Total	Total	Surplus	$/WAR
WAR	Value	Cost	Value
14	$104 MM	$175 MM	­-$71 MM	$12.5MM

I guess that wouldn't crippling (for the Yankees), but its pretty bad.  Now lets see what would happen if Tanaka is a 3 WAR pitcher through his 4 seasons.  He would likely opt-out if this is the case.  If the going $/WAR rate is at just say $7 MM, he should be able to find a deal with more years and similar average annual value to what amounts to a 3-year, $67 MM option.  He would be entering his age-29 season at that point, so he'd be in line for a nice payday if healthy.  So I think as long as he's about 3 WAR pitcher through year 4, he'll opt-out. Now let's say $7 MM is the market rate over those four years and see what the contract looks like:

Total	Total	Total	Surplus	$/WAR
WAR	Value	Cost	Value
12	$84 MM	$108 MM	-$24 MM	$9 MM

Now it looks at least reasonable.  Since the "release fee" is getting spread around 4 years as opposed to 7, the average annual value goes up a couple million.  And remember this is guessing that Tanaka is about about as good as Hiroki Kuroda.  That would be a pretty nice projection for Tanaka, and he still doesn't provide positive return on that contract.  What does he have to pitch like for this deal to break even?

Total	Total	Total	Surplus	$/WAR
WAR	Value	Cost	Value
16	$112 MM	$108 MM	$4 MM	$6.75 MM

Basically, assuming some inflation, the Yankees are betting on Tanaka being a 4 WAR pitcher. He doesn't have to pitch like Yu Darvish to make this work, but he does have to very good.  And if he's only pretty good, the deal doesn't look good at all. And if he's not that good, this deal will be a 7-year disaster.  Tanaka is set-up exceptionally well to optimize his earnings no matter how he pitches.  But the Yankees are taking a big risk, knowing that Tanaka will have to pitch like an ace for this deal to be a winner.  

Batting Leadoff- Man On First: Should I Steal?

This post originally appeared on Batting Leadoff. Batting Leadoff is a website dedicated to providing readers with premium baseball content. Posts from the site will appear regularly on the Sports Business Society Blog (view the information in the sidebar for updated information.)

By Matthew Provenzano 

Suppose you are a manager. It is the beginning of an inning (does not matter which one) and your first hitter gets on first base. The score is tied and it may be in the team’s best interest to try to swipe second base. Using Run Expectancy Matrices and Stolen Base/Caught Stealing Data from 1993-2010, courtesy of the Lahman Database, we can determine whether the runner should be sent.


Using the Lahman Database, it is easily determined that the average SB% is 69.9%, so we shall assume that the runner in question has a SB% of 69.9%, for the sake of argument. To determine whether it would be beneficial or not to steal, all that needs to be done is to calculate the expected payoff of a steal vs. the payoff if one does not steal. If the difference is positive, then one should steal, and vice-versa. The payoff of a steal can be represented as the following:

.699536 * SB + .300464 * CS, where SB and CS are the payoffs for a stolen base and a caught stealing, respectively. These payoffs can be put into a neat table, one row showing the probability of scoring one run when stealing, and the other column showing the average number of runs scored when stealing.

	0 outs	1 out	2 outs
Prob. 1 run scores	.497	.315	.161
Avg. # runs scored	.906	.538	.243

This doesn’t mean anything when standing by itself, so this next chart will show the difference between stealing payoff vs. non-stealing payoff:

	0 outs	1 out	2 outs
Prob. 1 run scores	+.056	+.031	+.026
Avg. # runs scored	-.035	-.024	-.002

So, what does this all mean? This would really only make sense given the context. This chart basically shows that stealing will increase the probability of scoring a single run in an inning, but will hurt the chance of a multi-run inning. If a manager is facing Clayton Kershaw, then it would be in their best interest to score a run in any way, especially if the possibility of scoring a run in the future is bleak. This can work similarly in the playoffs, where the run differentials are often smaller and opportunities for run scoring can dwindle quickly. But in a regular season match-up against an average to below-average team, it may be beneficial to shoot for multi-run innings to pad leads.

What this also shows is that baserunning, while important, is not the most crucial aspect of the game. Rickey Henderson, even during his prime, only generated approximately 3 WAR from his 100+ steals in a season. To illustrate this, let’s look at the chart of differences one more time, but instead I will use the SB% of Rickey Henderson–80.76%.

	0 outs	1 out	2 outs
Prob. 1 run scores	+.107	+.068	+.051
Avg. # runs scored	+.060	+.042	+.03

This pretty much works in the same fashion as the previous table in that the probability of a single run scoring is obviously higher than that of the average number of runs scored in an inning. But this shows that with even one of the best base-stealers in the history, on average he could only increase the probability of one run scoring by ~10%. Now, that is pretty good. And because every box is positive, it would behoove a manager to send Henderson in most cases. But, if this is only for one of the best, how consequential of a strategy could base stealing really be? And in effect, it’s mostly inconsequential. It provides a possibly small advantage depending on the scenario. Given all of this: should the runner from first be sent? It may sound unsatisfying, but the answer is: it depends, and it may not make a difference.

Matthew Provenzano is a sophomore at Cornell University in the College of Arts and Sciences, majoring in Information Science and with a minor in Law and Society. Matt is a member of Cornell At Bat where he is a journalist, broadcaster, and content manager and is also the Technical Director of the Big Red Sports Network and founded http://bigredsportsnetwork.org. He is from Seaford, NY, and has been a die-hard Yankee fan since the age of 6. Contact Matt at mjp294@cornell.edu or follow him on twitter at @mpro6294.

Batting Leadoff: Is Making Offseason Headlines a Good Thing?

This post originally appeared on Batting Leadoff. Batting Leadoff is a website dedicated to providing readers with premium baseball content. Posts from the site will appear regularly on the Sports Business Society Blog (view the information in the sidebar for updated information.)

-By Alex Smith

As we enter the 2013 offseason, we’re going to hear a lot about the free agent activities of Robinson Cano, Jacoby Ellsbury, and Shin-Soo Choo, as well as possible trades involving David Price and Troy Tulowitzki. However, it’s likely that the signings and trades of other lesser-known players will have a bigger impact on the outcome of the 2014 season than the signings and possible trades of these superstars.

If you look at recent history, it’s the teams who have made shrewd value driven acquisitions rather than a lot of noise that have made the largest jumps in the standings on a year-to-year basis. If we compare the standings from 2012 to 2013, the Red Sox made the grandest jump in wins at 28, the Cleveland Indians made the second largest leap at 24, the Royals the third highest at 18, and the Pirates the fourth greatest leap at 15 wins.

In case you didn’t notice, the Toronto Blue Jays and the Los Angeles Angels, despite being last winter’s biggest headliners, failed to make this list. In fact, the Blue Jays only won 1 more game in 2013 than they did in 2012 and the Angels actually lost 11 more games. The Los Angeles Dodgers and Cincinnati Reds also made a lot of news around the blogosphere last winter, but the Dodgers broke the bank to make sure that spending was worth it and the Reds simply added an established outfielder in Choo to an already playoff-bound core.

So what does this all teach us? First, let’s analyze how the Red Sox, Indians, Royals, and Pirates made their jumps to the top of the standings. Red Sox fans were frustrated last offseason with the lack of a notable moves after getting rid of the contracts of Adrian Gonzalez, Josh Beckett, and Carl Crawford. However, they received fantastic value in the signings of Shane Victorino, Koji Uehara, and Mike Napoli. This value, combined with healthier seasons from Dustin Pedroia and Jacoby Ellsbury, the reemergence of Jon Lester and Clay Buchholz, and David Ortiz’s ability to fend off father time, led them to a championship.

The Indians made some headlines last winter by signing outfielders Nick Swisher and Michael Bourn, yet it wasn’t just these signings that led the Tribe to earn one of the wildcard births. Between them, they only posted a WAR of 4.4 in 2013, 1.8 WAR below Michael Bourn’s personal 2012 WAR. The Indians were successful because Jason Kipnis broke out, Yan Gomes and Ryan Raburn far exceeded expectations, and Justin Masterson, Ubaldo Jimenez, and Scott Kazmir all turned their careers around. In essence, rather than the noteworthy signings of Swisher and Bourn making the quintessential difference, it was the less noteworthy acquisitions of Kazmir, Gomes, and Raburn along with improvements from players they already had, that led Cleveland’s turnaround.

Of the four teams that made the biggest leaps in wins, the Royals are, in a way, the outlier. Their “big” trade last winter actually did pay off, at least in the context of 2013. By acquiring James Shields, the Royals were able to shore up what otherwise would have been a questionable pitching staff and win 90 games. The down-side to this, though, is the consequences that will come with the short-sightedness of the Shields trade.

Even though the Royals won 90 games, they gave up Wil Myers in the process. Myers could be a top five player in baseball in a few years and the Royals would have had six years of team control. Instead, they received two years of James Shields and they failed to make the postseason in year one. Yet, just stating that the Royals improvements can be attributed to Shields would be foolish. Like the Indians and Red Sox, the Royals also benefitted significantly from unheralded signings such as Ervin Santana and Jeremy Guthrie.

The Pittsburgh Pirates are the best example of how value-driven acquisitions can turn a franchise around. Without making too many national news outlets last year, the Pirates smartly picked up Russell Martin and Francisco Liriano via free agency and then traded for Marlon Byrd and Justin Morneau at mid-season to help fill holes in their lineup. It’s also important to note the chance Pittsburgh took on A.J. Burnett the year before that has paid off mightily. It is through these moves that the Pirates have been able to find effective supporting players for their home-grown superstars like NL MVP Andrew McCutchen and Pedro Alvarez.

Now that we’ve analyzed where it went right for the aforementioned four teams, let’s look at where it went wrong for the Blue Jays and Angels. The Blue Jays pitching staff was a wreck all year with no consistency behind Dickey and Buehrle, both of whom were only mediocre. Offensively, Reyes only played in 93 games and their lineup simply had too many holes around him. It’s hard to go anywhere when you only have two players in your lineup who played in more than 110 games and posted positive WARs.

The Los Angeles Angels were supposed to have one of the best lineups in baseball in 2013 after the addition of Josh Hamilton. All winter, fans were giddy about getting to see a top of the lineup featuring Mike Trout, Albert Pujols, Josh Hamilton, and Mark Trumbo. Yet, Pujols’ injury problems caused him to struggle until he eventually was forced to have season-ending surgery and Hamilton never lived up to expectations. However, the Angels would have needed both of these players to be absolutely spectacular if they were going to overcome their pitching deficiencies. The Angels had the fourth highest xFIP in the league and the 7th highest ERA, and only C.J. Wilson pitched more than 155 innings for the year.

After analyzing what went right and what went wrong in terms of 2012-13 offseason acquisitions, a major theme becomes clear: star players are nice and are good for building excitement going into a season, but filling holes is more important. These players, who can often be acquired cheaply and fly under the radar, serve as the glue for any team with the intentions of contending in the postseason.

The Oakland A’s, who built a team around such undervalued assets (they made their jump from 2011 to 2012 so it’s not chronicled in this article), are a perfect example of how having no holes can be more effective than trying to compensate for holes with star players. If you’re going to make a headline move, however, you must be adding to an existing core (see Cincinnati Reds) or you must be willing to spend like the current Los Angeles Dodgers or 2000s New York Yankees. If your team’s not doing this, they’re either selling out on their future to succeed (see Kansas City Royals) or only trying to sell tickets without caring about winning.

Knowing this trend, I encourage all fans to follow where players like Bronson Arroyo, Dan Haren, and David Murphy end up. Because while it will be fun seeing where Robinson Cano, Jacoby Ellsbury, Shin-Soo Choo, David Price, and Troy Tulowitzki land (and they will all definitely impact the 2014 season) it is the signings that go barely noticed that could be making the biggest difference next fall.

Alex Smith is a junior in the School of Industrial and Labor Relations at Cornell University. In addition to being the founder of Batting Leadoff, he works as a scout/field manager for Perfect Game USA and sits on the planning committee for the 2013 Ivy Sports Symposium. He is a relief pitcher on the Cornell varsity baseball team and hopes to one day pursue a career in baseball operations, player development, or amateur scouting. Contact him at aws77@cornell.edu or follow him on twitter @RealAlexSmith19.

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