Basically the storyline of the book encompasses how the main character Billy Beane, General Manager of the Oakland Athletics, implemented a measurement and feedback system based on a player’s ability to get on base. This system was based on the sabermetric principles and theories first introduced by Bill James in his comprehensive Historical Baseball Abstract, a rigorous statistical analysis used to track the traits most connected to a player’s value to a team. [2]

What is Sabermetrics?

The Moneyball book implies that when sabermetrics is used to identify players with superior abilities (who aren’t noticed by competitor scouts), it allows new players to be added to a team; thus, increasing the winning percentage for the team without paying premium salaries to those players. This results in a competitive advantage for the team’s league standing. For further understanding of sabermetrics and its theory in relation to baseball, please check the paper written by Jim Albert.

DiamondView and PlayersPlan

Several detailed programs have been implemented by teams like the Cleveland Indians MLB team. The Indians have implemented two programs: DiamondView and PlayersPlan with the hopes of increasing appraisal of a player’s performance and value. These types of plans are often used by MLB team managers to facilitate selection and recruitment possibilities and help determine the optimum team salary distributions. [3]

Systems like DiamondView and PlayersPlan keep track of each player in a database that is used for recruiting and selection, training and development, appraising player’s skills, and helping evaluate compensation for the players. For example, information on a baseball pitcher would include such pitching statistics as the number of times the pitcher allows a walk, how many members of the opposite team were pitched to at the plate, the number of times the pitcher entered the game with intent to save the game but failed, number of hits allowed in a game, home runs allowed, earned run average and many more. Statistics, along with some physics theory, has also suggested that left-handed pitchers get better results against left-handed hitters. Knowing which pitchers have the best odds against hitters based on this theory, managers can stratgically use relief hitters to counter pinch hitters substituted into a game at the last minute.

Others Question Usefulness of Sabermetrics

Many consider sabermetrics a valuable and objective means to gain an effective measure of a player’s value to the team. Others question the usefulness of such statistics in the prediction of future behavior of players.

DIPS

Another measurement tool known as Defense-Independent Pitching Statistics (DIPS), introduced by Voros McCracken as early as 1999, measures a pitcher’s stats. These stats do not include plays that involve infielders or outfielders, but are based on stats that result strictly from the control of the pitcher alone, like walks and strikeouts. [4]

DICE and FIP

Others, like Tom Tippett [5], felt this DIPS evaluation tool was not entirely viable; while others have introduced new math formulae and statistics that keep track of innings pitched(IP), which measures how many outs were made while a pitcher was pitching. For instance, formulae such as Defense-Independent Component ERA (DICE) and FIP do consider factors that make them highly dependent on the defensive play of the fielders.

It appears that the focus on talent and statistics, along with the recent implementation of information technology, will continue to be implemented and will infuse team selection — including MLB pitchers — and salaries for awhile.

Patricia Deming, is a graduate of the University of Texas at Austin, with a BA in Mathematics. She enjoys writing articles and contributing to sports and education blogs, such as DegreeJungle.com. She has been a baseball fan for many years and regularly attends Seattle Seahawks games.

[1] Lewis, M. (2004). Moneyball: The art of winning an unfair game. New York: Norton.

[2] James, B. (2001). The new Bill James historical baseball abstract. New York: Free Press.

[3] http://www.cleveland.com/gameplan/index.ssf?/gameplan/more/part2.html

[4] Voros McCracken, “Pitching and Defense: How Much Control Do Hurlers Have? January 23, 2001.

[5] http://www.sloansportsconference.com/?tag=tom-tippet

This Fan Shot was contributed by Patricia. Have something you want to say about the Mets? Share your opinions with over 15 thousand Mets fans who read this site daily. Send your Fan Shot to GetMetsmerized@aol.com. Or ask us about becoming a regular contributor.

Once upon a time, baseball was a simple game. The goal is to score more runs than your opponent. Each team is given 27 outs to score as many runs as they can. In order to score runs, a team’s players have to get on base. Once a player gets on base it was the other players’ jobs to drive them home to score runs. On the other hand, the defense’s job is to get 27 outs allowing the opposition to score the fewest amount of runs. Whoever scores more runs in 9 innings of play wins – simple.

Now let’s fast forward to the 1980s. The 1980s were famous for Nintendo, big hair bands, Reaganomics, and the invention of rotisserie baseball.

Fantasy baseball exploded onto the scene in the 80s, and the men that played this game were looking for ways to build better teams. They wanted to build better teams in order to take home the lucrative prize money that came along with winning their rotisserie league. They used different combinations of stats to form equations, which in return would spew out which players they should select on their team.

Yes, the advanced stats that the game uses today were ultimately developed by men that maybe never even played the game. They were simply looking to build better fantasy teams. It leads the people with advanced knowledge of how the game is played on the field to butt heads with those that sat at their desk and computer doing all the math.

Photo Credit: bronxbanterblog.com

Bill James, the father of advanced statistics and sabermetrics, didn’t start to gather a serious following until the mid to late 1990s. Until then, he published his yearly baseball reviews and would sell 500 copies per year if he was lucky.

The game wasn’t ready for the story he was trying to tell. James was basically telling everyone in the game that they have been looking at the game improperly for nearly 100 years. Advanced statistics were born. He broke down nearly every single aspect of the game, except defense, which he was never able to develop an accurate statistical rating for.

But did the game really need the advanced statistics?

The game had survived over 100 years just fine without advanced statistics. But now, in every team’s organization, there are mathematicians working in this area. The question is, is it really necessary?

The reason why sabermetrics and advanced statistics took over the game in the 90s is because that is the when player salaries started to get to the point where some sort of projection and analysis was needed. Owners wanted to know if it was really worth it to spend the money on player X.

Baseball had officially become a full-fledged business.

In every MBA program across America, students are often required to take a course dedicated to statistics and spreadsheet analysis. The students are taught how to use Excel spreadsheets and programs like Risk Solver to make business decisions. If you are under the assumption that the CEO of a big company makes decisions based on his/her gut you are mistaken.

More often than not, the decisions are made by a computer than runs simulations based on the data that the decision maker inputs. The program takes all the data and then it gives you the most logical decision after running all the simulations.

It’s actually pretty cool. You could build a model that can tell you the best location to build an ice cream shop, based on three different locations, with three different average yearly temperatures, three different traffic patterns, and three different populations in the towns they’re in. Not only will it tell you the best location to build your ice cream shop, but the expected revenue at each location.

The same thing can be done with baseball players – in theory that is.

Everyone knows that Billy Beane and Paul DePodesta’s use of advanced statistics and sabermetrics officially put them on the map. Their use was chronicled in the book Moneyball by Michael Lewis.

The book that exposed Billy Beane’s strategies.

Beane used the advanced statistics to remain competitive with a team that had the lowest payroll in the league. Once he started winning, people started to question how the heck the Athletics could be winning when they were only spending one-third of the money of the other teams. At that point, every Tom, Dick and Harry fell in love with sabermetrics.

Sabermetrics became the key to unlocking hidden baseball talent.

But here is the fundamental flaw with peoples’ understanding of what Billy Beane actually did – Beane wasn’t intentionally trying to win by spending the least amount of money he could. Beane wanted to spend money. He wasn’t trying to do his owner a favor by spending the least amount of money on building a team. He was simply in a situation where his hands were tied. He had to think outside of the box. He had to get more efficient with spending what little money he had. That’s it.

Somehow Beane’s strategy became an excuse for teams to spend less money, and try to build teams using a philosophy that Beane only developed because he had to and not because he wanted to.

Players are now investments, plain and simple. If a team is going to make an investment, the projections, spreadsheets, models and simulations have to all tell the same story – that the player is worth the investment.

However, there is a problem with advanced statistics – the game is still ultimately played on the field. You cannot remove the human element from the game, and no statistic can factor that in. And while past performance is a good indicator of future performance, there is only so much weight that advanced statistics should carry.

Advanced statistics paint an imperfect picture of the game when used improperly. Here is why:

Advanced statistics use inputs which are plugged into an equation and are determined by the person developing the statistics in order to arrive at a desired outcome. They often have to finagle with different stats until they get an answer that makes sense. What also comes into play is the developer’s bias.

If someone is playing with stats in order to make their equation work, how is that more accurate in telling me which player is better than if I used the old school statistics (OBP, AVG, ERA, etc.) which have been used for the past 100-plus years, and my eyes, used to watch the players play?

Let’s take a look at the Holy Bible. There is a show on TV that comes on one of the learning channels every once in awhile which basically alludes to the fact that the bible has a hidden code in it, which not only predicted things that happened in the past, but also can predict future events. Now on the surface, they did prove that there was a code in the bible. But is there really a code in the bible, or was it manipulation by the developer to come to a desired goal/outcome?

Odds are there isn’t a code in the bible, but this just shows how the manipulation of data can get to a desired outcome when played with long enough. One of the major issues with scientists to this day is trying to conduct scientific studies and not have their bias come into play. Bias alters outcomes.

The bottom line is that baseball is still a game where there is still a lot of luck involved. For instance, if a player is half a step to the left or right, a ball drops in that maybe shouldn’t have been a hit. Which stat factors any of these things in? The argument is the law of averages balances everything out. In the end, the math is the constant.

However, there are internal and external factors affecting the game constantly. These factors cannot be built into models. These factors cannot be accounted for statistically.

Where a card counter at the black jack table can turn the odds against the Casino by using probability and a system of advanced mathematical equations to gain an advantage, there is a set number of cards in the deck, and only a certain number of things can occur to account for. You can’t do that in baseball. In baseball, there are an infinite number of things all taking place simultaneously which affect the outcome of every pitch.

The problem at large is that the game has changed significantly since the introduction of advanced statistics. There are too many statistics which are complicating the game. They cause managers to over-manage situations.

For example, is a lefty specialist really necessary in a team’s bullpen? According to advanced statistics they are. But when it’s all said and done a bullpen pitcher is simply a pitcher who could not make it as a starting pitcher. Very few pitchers are groomed to be in the bullpen. In other words, why would I bring a pitcher into a game, and take out my better pitcher, simply because statistics show that one guy is better at getting left-handed batters out?

It doesn’t make sense. The best players should be on the field.

Statistics tell front offices they need lefty specialists. They tell the manager that they better go against their gut which tells them to leave their better pitcher in the game. It sounds crazy when you think about it. I’m going to take out my better pitcher because statistics show that over time, a pitcher of lesser quality has done a better job of getting left-handed hitters out? It doesn’t sound logical.

Now I have decided to take my best pitcher available out of the game to bring in a lefty specialist in order to get one hitter out. After he gets that batter out, I have to take him out of the game to put in an even lesser quality pitcher? Why not just leave my best pitcher in to get the lefty out. Now I have changed the odds of getting the remaining hitters out, all because stats have told me to take my best pitcher out of the game.

The entire landscape of the game changed because of a single stat.

Is there a stat that shows the odds of getting the remaining hitters out in a game after I made that decision? There is a stat that shows me that I should bring a lefty specialist into the game, but not a stat that shows the odds that I will get the remainder of hitters out now that I made that pitching change.

That is just one example of how stats have changed the game, but the question that still remains is – are all of these advanced statistics helping or hurting the game?

Cases can be made for both sides, but the truth of the matter is that all these stats are really good when looked at from the surface. It’s how the people behind the scenes use them that will ultimately determine whether they are good or bad for the game.

My daughter preparing for a front office job someday – you can never start them too early.

Advanced baseball statistics is very similar to the app market for smart phones. App developers are always looking to develop the next Angry Birds, and stat developers are looking to develop the next stat which proves that they have the secret formula to determine who the best player in the league is.

There is no secret formula. Baseball is played on the field, not in a laboratory, and not in a computer program. There isn’t a single stat or mathematical equation that can determine the outcomes on the field.

Nothing will ever change that.

Follow Mitch Petanick on Twitter.

It’s September 4th, and the Orioles find themselves one game out of first place in the American League East. That statement, on it’s own, isn’t too ridiculous. It’s when you start looking at the stats that make that statement look ridiculous.

The Orioles are not a good baseball team according to the stats. In fact, if you were to look at the league statistical rankings, before looking at the standings, you would think they stink. They’re currently in the bottom half of teams for offense and defense, and the pitching is in the middle of the pack. It begs fans to question how this team is winning ball games.

I decided to look further into this anomaly, so I skipped over to fangraphs.com to see if there was some sort of statistic that could explain why the Orioles were winning so many games this year. I found a statistic that, according to the sabremetric community, is supposed to provide the the most complete, and overall best analysis of both a player and the team. That statistic is Wins Above Replacement (WAR). I’m not going to go into detail about what WAR is, but if you would like an explanation of this statistical category, click here .

Finally, I thought to myself, I will find the answer I am looking for as to why the Orioles are playing so well this year. Their WAR must be off the charts, and that will explain everything. Boy was I wrong. Very, very wrong. The Orioles WAR isn’t just bad, it ranks in the bottom of the league. The only two teams with lower WAR, are the Cleveland Indians, and Houston Astros. So now the Orioles have not only defied our traditional baseball statistics, but also flipped the bird (no pun intended) to the sabermetric community.

What are we going to do about the Orioles? They’re defying baseball logic! They’re like Maximus Decimus Meridius defying the emperor in Gladiator. Something has to be done!

The Baltimore Orioles have their eyes set on the post-season. Statistics are supposed to give us a glimpse into why a team is successful or not. The Orioles laugh at that notion. Throw statistics out the window in the case of the 2012 Baltimore Orioles, they are irrelevant. However, the odds are that those statistics will catch up to them, most likely in the post-season, when playing against a superior opponent. With everything at stake, the post-season is generally the place where fairy tales end. The post-season is usually where these unlikely teams’ weaknesses get exposed. Then the baseball traditionalists smile and say I told you so.

The Orioles have the great baseball minds scratching their heads. They have fans of other MLB teams jealous that the Orioles are doing something that their team can’t – win. And the Orioles are throwing their hands up shouting are you not entertained?! Yes Baltimore, very entertaining. The baseball gods are smiling on you. There is no explanation for what the Orioles are doing this year except that’s baseball for you. The inexplicable things that happen are what makes this game great. We try to make sense of it all with statistics, but there are situations when not even statistics can help. That is the case with the 2012 Baltimore Orioles. And with the playoffs right around the corner, they better make a call to Jeffrey Maier and see if he’s available.

Before you call me crazy, sit and think about it. The strategies that Beane developed and ultimately used do exist, but moneyball doesn’t. If it did ever exist, it ended once large market teams also started to implement Beane’s strategies once they saw how successful Beane’s Oakland A’s were. The Red Sox started implementing the small market strategies made famous by Beane, and what did it lead to? They finally broke the curse of the Bambino. But that wasn’t moneyball, because moneyball doesn’t exist.

There are basically two schools of thought in baseball – the old school scout mentality, and the moneyball school of thought. The old school thinkers say “wow that guy has all the tools,” but moneyballers ask “can he play ball?” Old school thinkers look for potential, while moneyballers look for performance. The old school mentality has driven me crazy for years. Year after year I watch teams draft players based on the coveted five tools, and then pay them upwards of $1 million just for signing a contract. They don’t even know if this guy can play, and simply because the guy can hit a baseball a country mile during batting practice, they invest millions. It doesn’t make sense to pass up on a guy that has shown he can play the game at a high level, for a guy who is visually or physically more impressive. That’s a stupid strategy even if you have a lot of money to spend. I guess that means my beliefs would make me a moneyballer, that is, if moneyball existed.

Remove the word moneyball from your vocabulary. Instead, call it performance based evaluation of players. Rather than looking at what this guy might be able to do for your team, you look at what this player can do for your team. You do that through evaluation of statistics, but also based on what you see on the field. You can not evaluate a player on statistics alone. The two schools of thought really should work hand in hand, not against each other. If you combine the schools of thought, you really have a total of six tools that players should be evaluated on (not the traditional five) – running speed, arm strength, hitting ability, quickness, mental acuity (patience at the plate), and ability to get on base. I firmly believe that teams should always value proven players over guys who have an array of tools but can’t apply them in game situations. I guess that would make me a moneyballer, that is, if moneyball existed.

One team that I think has been doing this well the past few years is the San Francisco Giants. They tend to draft guys that they can get through the minor leagues as quickly as possible to start helping the big league club. You can’t do that by drafting guys based on talent alone, so there has to be skill there. If a guy has tons of talent, but has to spend six years in the minor leagues developing the skill, then what’s the point? Just draft the guys with skill, and save yourself time and money developing them in the minors. That’s why Beane focused his draft on more polished college players – there is less development needed, and they can help the team in a shorter period of time (in most cases). Then you don’t have to spend big money in free-agency to address your needs. I completely agree with Beane’s drafting strategy. I guess that would make me a moneyballer, that is, if moneyball existed.

Moneyball doesn’t exist. There isn’t some magic formula, or mathematical equations, that a team can use to evaluate players and uncover undervalued players. If that’s what you think, get it out of your head. Teams can’t expect to win without spending money, unless they have a well developed minor league factory that is spitting out skilled players like Ford spits out Mustangs. This is an area the Mets are lacking. Every team uses the same analyses now, so those days of Beane’s A’s are all but over. But the Mets have a distinct advantage over those early 2000′s Oakland A’s – they aren’t a small market team. Those small market team rules don’t apply.

The New York Mets should focus on what the San Francisco Giants have done the past few years. They have to find a way to get guys to the major leagues, as fast as possible, because the team is in a complete state of disarray right now. There are guys playing out of position in order to plug holes. The problem is there are more holes than plugs, and we all know what happens when there are more holes than plugs – the ship sinks. The fix is simple enough – start drafting more polished players that will be able to help the team now, rather than later. Either that, or they have to pony up some cash and address their needs.

The Mets can turn this around, but they have to get their hands dirty, and re-evaluate their organization from the ground up. They better do it fast, because this is starting to remind me of the Mets teams of the early 1990s…and I don’t know how many of us can go through that again.

Does that mean the Mets are on pace to have the success the A’s had ten years ago that was chronicled in the book and movie Moneyball? Not likely.

For those of you who haven’t read the book (or watched the movie), Moneyball is based on a form of analysis called sabermetrics. Simply stated, moneyball theorizes that in order to win games, a team has to score more runs than their opponent by getting on base more frequently. It goes further to analyze which players actually help you score more runs using a series of mathematical equations called sabermetrics. This is obviously a very rudimentary explanation of moneyball, but it inevitably goes against everything the traditional scouts have been saying for over 100 years. Scouts search far and wide for the coveted five tool players which are as rare as unicorns and leprechauns. The search takes them around the globe with one goal in mind: to build the best teams they can by seeking out the best talent.

Sabermetrics allowed Beane to take advantage of players often ignored by other teams in order to build his historic 2002 team. They were ignored since teams didn’t understand their true value. This misunderstanding was due to not using sabermetrics to evaluate players. At least that is what we are led to believe. We will return to this later.

The movie alludes to the idea that Beane was looking for a way to analyze talent that was different from the traditional scouts. This was supposedly due to the fact that he was once considered a “can’t miss” five tool player. He was selected in the first round of the 1980 MLB draft (by the Mets coincidentally), but never lived up to expectations. The Mets had three first round picks that year, and held the number one pick. They used that number one pick on Daryl Strawberry after Beane signed on to play football and baseball with Stanford, even though scouts thought Beane was as close to a “sure thing” as you can get from a prospect. No teams wanted to risk a first round pick on a kid that was going to be John Elway’s heir at Stanford. The only team who could afford to take that risk was the New York Mets since they had two other first round picks.

To this day, scouts say Beane was the most gifted athlete in the 1980 draft class. But if Beane learned anything from his playing career, it’s that there is no such thing as a “sure thing.” This has him at odds with scouts who wanted to try and put the best overall players on the field, the way big market teams do.

Back to Beane’s 2002 Oakland Athletics team which was the basis of the book and movie Moneyball. First, let me say that the movie was entertaining. Unfortunately, it paints a picture of Beane building the entire 2002 A’s from a bunch of players that no other team wanted. It reminded me of the scene in the movie Major League when they are trying to build a team bad enough that will help the Indians move out of Cleveland. Nobody was previously playing in the California Penal League, and the team was actually stacked before Beane added the final few pieces of the puzzle using sabermetrics.

The movie fails to mention the fact that the pitching staff consisted of Barry Zito (2002 Cy Young Winner), Mark Mulder, and Tim Hudson who were affectionately known as the “Big 3.” Let’s put it this way, if Beane didn’t win the division with those three guys he should’ve lost his job. By the way, the closer was Billy Koch, and it gets even better. The A’s had Miguel Tejada (2002 AL MVP), Eric Chavez, Jermaine Dye, Ray Durham, and David Justice all in their lineup. So was the success of the A’s due to sabermetrics being used to add a few players that nobody even remembers from the team, or the fact that everything came together for the A’s due to great player development? And if you thought the 2002 pitching staff was scary, the 2003 & 2004 A’s added a young Rich Harden to the mix. How did the Athletics manage to never win a World Series with those guys on their pitching staff?

Now let’s get back to the Mets. I think everyone will agree the Mets don’t have the talent the A’s had in the early 2000s. Not only that, but the A’s are a small market team, so they had to come up with creative ways to compete with big market teams. Look at it this way - when a person with a lower income goes to buy a car, they look for different attributes in that car than a person with a higher income would. The person with lower income goes to buy a Honda. It will get you back and forth to work, it’s reliable and good on gas, but you aren’t winning any races. The person with higher income goes to buy a Corvette, and the license plate reads “eat my dust.”

The Mets are a large market team. They shouldn’t be shopping for Hondas. Their license plate should read “eat my dust.” It doesn’t make sense for them to use the strategies of the small market teams. Their strategy should be to use their revenue stream to crush their opponents. The Mets can certainly learn a thing or two about player development from the Athletics of the early 2000s, but I’m still not sold on the fact that sabermetrics had anything to do with the success of those teams after looking at the players on that roster.

Can the Mets build a winning team using sabermetrics and moneyball? I know one thing for certain – no small market teams have won the World Series using sabermetrics alone in the past ten years. So if the Mets want to start winning again, they better start taking the money out of Moneyball, and start spending it.

Having explained more precisely what the central GOAL of Moneyball is (Save Money) I thought it might be good to talk about what it actually says it did and why it did what it did from the Statistical Analysis point of view.

Moneyball, as was stated previously, used Statistical analysis to find an UNDERVALUED METRIC that was then used to hunt for and create a MASTER LIST of players who exhibited that quality for consideration of acquisition.

How did they arrive at OBP as the undervalued metric and how would that work today?

Well the book leads us to believe that Sabermetrics were used to list and rank players and to determine which stat was prevalent in good players AND cheap players that was being overlooked by the rest of the league.

But did that really happen? Did it really show that OBP was the undervalued stat or did it by statistical bias automatically select OBP as the undervalued stat since Sabermetrics were used and invented to ILLUSTRATE the importance of OB in the game of baseball?

You see by using Sabermetrics as your analytical model you PRE-SELECTED OBP as valuable merely because Sabermetrics values that more than any other event and didn’t really let the analysis of numbers make the decision for you.

You would come up with OBP as the UNDERVALUED VALUE stat even in years when it was not.

If you didn’t construct the statistical model in a way that made OBP valuable before any comparison was made it would not have valued OBP in the first place and therefore you would not have come to the conclusion that OBP was UNDERVALUED!

Moneyball used an OB-centric statistical model and came up with OBP as the UNDERVALUED METRIC. WOW, What a SHOCK! They looked for something specific and then FOUND IT! Eureka moment or preselected destiny because they used a metric that favored the result before the result was even seen?

IE: If you ran a statistical analysis model that favored HRs above any other event you would come up with a list of GOOD and CHEAP HR hitters, and you might be left thinking HRs are the UNDERVALUED STAT, but would you be right? Would it mean that HRs are undervalued? No – what you did was lent value to something before any player comparison was made. You FOUND what you BIASED your search parameters to look for. HRs are a poor example granted because we all KNOW they are valued, but it does make the point that if you bias your stat model towards one event, it will only work if your biased model correctly ascertained the undervalued assets from the outset. Garbage in, Garbage out.

Now OB was undervalued at the time because OBP while well known, was not given the importance it is today thanks to the book Moneyball. Most teams all look at OBP now and it is no longer undervalued – it hasn’e been for quite a few years.

Sabermetrics were new, not widely used and therefore no majority of teams would come up with the same MASTER LIST as Oakland meaning they would not be FAVORING OBP and as a result OBP would be undervalued.

This is how MONEYBALL came to find that particular market inefficiency.

Would it work today?

What is the most UNDERVALUED STAT in today’s market?

Can Sabermetrics tell you what is undervalued these days?

Or will Sabermetrics come up with the SAME EXACT ANSWER as before because it values OB more than anything else?

It is believed that Sabermetrics actually found the UNDERVALUED stat but the truth is the guy who PICKED Sabermetrics as his statistical model picked OBP as the undervalued metric before any comparison, chart or calculation was made!

And it is for this reason none of the people who have a strong belief in Sabermetrics have been able to ascertain what the new UNDERVALUED metric is.

ASK them and they will not be able to tell you. Any of you sabers care to list a couple of undervalued metrics right now?

They will cite other metrics made BASED on the same OBP biased approach, leading to the same results.

They need to come up with a new statistical model that will not value one stat over another and not bias the results in favor of OBP. Otherwise just use OBP and trash the other stuff that doesn’t really lead you to anything undervalued assets.

Sabermetrics was primarily a form of statistical analysis that allowed OBP to be seen as underused and undervalued. That is all behind us now and what we now need is to discover that NEW undervalued Metric.

A NEW STATISTICAL APPROACH IS REQUIRED if that Moneyball UNDERVALUED approach is going to ever work again!

That can only occur by someone finding an event that is overlooked and creating a metric to find it.

If Sabermetrics is used by all teams then Sabermetrics will not be able to come up with an UNDERVALUED STAT because EVERYONE will be valuing it!

SO for MONEYBALL to succeed it has to abandon the Sabermetrics it used when no one knew about it, and it must invent a NEW Statistical model that no one else uses in order to get back its edge and find what no one else is looking for and placing VALUE on!

And if that’s not done?

R.I.P. Moneyball.

This Fan Shot was submitted by Mike (Metsie). Have something you want to say about the Mets? Share your opinions with over eleven-thousand Mets fans who read this site daily. Send your Fan Shot to GetMetsmerized@aol.com.

I think it is time to talk about what Moneyball ACTUALLY means and to show some of those who claim to have read the book what the book is all about. Apparently, reading doesn’t always lead to UNDERSTANDING.

I have read the book, it was interesting to learn about the little known “behind the scenes” process of team building and how a front office operates. It is for THAT reason the book sold so well not because it was chock-full of useful information, formulas and strategy. It did have some information which would be useful for ANY team regardless of targeted payroll ceiling, and it did help to show how Statistical Analysis can help you find some hidden value where none is actually perceived.

The book discusses quite well the methodology used but mostly because it would be a pretty short book if it just said we used statistical analysis to find cheap players. I suspect this is the main reason why people confuse Sabers with Moneyball. The book expended a great deal of effort explaining what methodology they used to find “cheap” players which was the central goal of Moneyball.

Sabermetrics or advanced statistics were one of the predominant tools used to rank and identify who had the quality that was deemed UNDERVALUED but also used to identify what quality it was that was undervalued.

Sabermetrics are based largely on Bill James’ work and his work is mostly about how important On-Base Percentage is to winning (right or wrong that’s what conclusion he came to in its most simplistic form).

By using that strategy, your initial ranking of ALL players is going to FAVOR players with high a OBP and rank them accordingly. If you use OBP alone to identify what players are undervalued many low cost players will not show up on your list of top players simply because you ignored so many other aspects of the game.

Using the Moneyball method to exploit market inefficiencies in the early 2000’s, doesn’t guarantee that you will come up with all the top low-cost players today. Markets change every year.  It worked great for a little while back in the day, but that was then and this is now.

Now onto the topic at hand, the processes which will no doubt cause much vitriol in the comments?

MONEYBALL no matter what methodology used to arrive at the goal is about NOT SPENDING MONEY or Spending as little as possible. The REASON for implementing it is varied:

• Not having the money to spend due to low fan attendance and revenues.
• Cheap Ownership who are more interested in profit than wins and force the GM to shop at Kmart.
• Blind stupidity that convinces you that minimizing your player options translates to more success. I call this the “penny wise, pound foolish” syndrome!

Sabermetrics was used in the Book as a comparative means to identify players who fit the qualities they were looking for. But it was not the decider in who to get. Sabermetrics does not INCORPORATE player salary in their metrics. Two Players judged by Sabers can be equal while one gets paid 8 Million per year while the other gets the league Minimum!

So while the Sabers may have identified the players and created the initial MASTER LIST of candidates it did not DECIDE which one the team was going to get because there are probably a lot of HIGHLY PAID players on that list as well.

Look at the 2011 Top OBP leaders:

• Joey Votto
• Prince Fielder
• Lance Berkman
• Matt Kemp
• Ryan Braun
• Matt Holliday
• Carlos Beltran
• Troy Tulowitzki

Do you see any hidden gems or $1 million dollar a year players?

So you used OBP to identify all the players that you deemed were GOOD, but then eliminated all the players who were being paid accordingly for their talents, in this case all of them.

You see MONEYBALL is about REMOVING high salary players from the candidate list…

Sabermetrics are not the central driver of the Philosophy in Moneyball. MONEY is!

The Red Sox who are most often used as an example of a Moneyball team use advanced stats, but they SKIP the most important step needed for Moneyball… The removal of any players or options that command a high salary!

The Red Sox never removed those higher priced options from their list of targeted players… Oakland DID!

This is why the Red Sox actually won a WS and have the third highest Payroll in baseball while Oakland has never won a championship since they implemented Moneyball.

The Red Sox never limited their options based on Money.

Yes they both used sabermetrics, in fact most teams do, but the Red Sox did not ignore quality players because of money! They did not discard a better option merely because he made more than a cheaper and more inferior player!

Oakland did!

Even if a player had a superior OBP or SLG,Oakland would ignore those sabermetrics and that better player in favor of the lesser player and $$$$$.

Red Sox did no such thing! THEY ARE NOT A MONEYBALL TEAM! You can say they are a Sabermetric team as many teams are these days in some respect or another.

SABERMETRICS DOES NOT EQUAL MONEYBALL!

SABERMETRICS = A Limited Form of Statistical Analysis!

Statistical Analysis DOES NOT EQUAL SABERMETRICS! There are many ways to analyze stats and they don’t all subscribe to the theories put forth by Bill James and all those profiting in his footsteps.

Statistical Analysis is a means of calculating stats and placing importance on some stats over others but they do not show you the cheapest player nor compare price per performance in any way shape or form.

Now we COULD debate Sabermetrics in and of itself, but it really isn’t relevant to this conversation. Yes Sabers seem to be good at comparing players but Sabers themselves and the philosophy of Bill James is not required, important, or the be-all and end-all of Statistical Analysis!

Bill didn’t really INVENT statistical analysis we have ALWAYS looked at stats as a comparator. Bill James’ contribution was to create a few metrics that placed importance where he saw fit. I’m not going to debate if he’s right or wrong here, it is not the focus.

You do not need to read MONEYBALL nor any of Bill James books to create or use good metrics. Anyone can do it and if you work hard to ensure you are not biasing the data to show what you want, you will also come up with the right answers.

No single stat will ever give you the complete picture of any player. To say that OBP is a better metric than BA because it takes all PA into consideration doesn’t make it better. An even better metric can be achieved than the ones Bill James came up with.

How about a metric that takes into account moving the runner over or driving in a run regardless of an out being made? It would tell you a lot more about a player than either BA and OBP.

The thing that Moneyball SUCCESSFULLY showed was not that saving money is the way to go, but that DEEP STATISTICAL ANALYSIS is the key to making good decisions because you are making an EDUCATED Guess – an informed decision.

But MONEYBALL discards much of that information and the end result is as old as the game of baseball itself, how much they get paid!

Moneyball uses Sabermetrics to come up with answers, and then IGNORES the answers given based on COST!

Moneyball is not about Sabers or statistical analysis it is about NOT SPENDING MONEY!

The Braves have been used as an example of a team that did it the right way and they did it without the benefits of Moneyball. (They were pretty much done winning championships by the time Moneyball was invented!) They built a good team that was cheap because they developed it from scratch. Fine to do provided you have the patience to wait as long as it took them – decades of losing and a bit of good luck and timing and Greg Maddux. They finally built a team that carried them to five league championships and their one World Series title.

If they had spent some additional payroll to maintain their edge they might have won a few more WS and Titles.

The notion that spending less means winning more does not hold true. Building BETTER (regardless of methodology and COST) leads to better teams.

And by handcuffing and limiting your choices based on money means you make it that much harder to succeed. Because when you place limits on yourself that preclude you from many options,  you helped give the opposition who did not limit their choices an ADVANTAGE OVER YOU!

While Oakland might seem to have done well despite limiting themselves via implementing Moneyball, the bottom-line is Moneyball didn’t get the job done!

And while it might seem wise to a Moneyballer to point out how many playoffs Oakland went to while spending peanuts, you still have that little issue that the Yankees won more titles and World Series spending money.

1998 – 2011

Oakland A’s – AL League Championships 0, World Series Titles 0

NY Yankees – AL League Championships: 6, World Series Titles: 4

The great equalizer, Moneyball was not!

And what COULD/WOULD the story be if they had just spent a little to keep the cheap players they had worked so hard to find from walking away?

Or to compliment the team with players who would cost a little more, but would have increased profits due to WS ticket sales and victories?

How far might they have gone if they simply signed rather than ignored the best players they themselves calculated based on their UNDERVALUED Metrics?

When you LIMIT your choices based on self imposed financial limitations, you will not have the same success as those teams who use the same statistical analysis to pluck all the productive players that are out of YOUR price range!

Cheaper isn’t ALWAYS BETTER… You GET what you pay for!  Not in every circumstance but more often than not.

MONEYBALL is Penny Wise and POUND FOOLISH…

Especially now when all teams use advanced metrics everyday, but are willing to pay for the best available talent.

R.I.P. Moneyball

This Fan Shot was submitted by Mike (Metsie). Have something you want to say about the Mets? Share your opinions with over eleven-thousand Mets fans who read this site daily. Send your Fan Shot to GetMetsmerized@aol.com.

Gone are the days when having a different opinion was acceptable. Today, Mets fans who disagree with the front office are labeled haters and trolls. They are singled out and attacked on sites like this one or social mediums like Twitter.

I know there are Mets fans who like me don’t believe that Sandy Alderson was the right choice to be general manager. Some of us feel his moneyball ways are simply wrong and not cut out for a large market team like the Mets. The over-reliance on sabermetrics seems foolish and short-sighted to me. The game got along just fine for over 100 years without using sabermetrics to build a solid roster and a championship level team. I know I’m not the only one who feels that way, in fact most ballplayers – former and current – scoff at it.

Every team has a fanbase that likes certain players on the team and dislikes other players. I know there is a good number of fans who like myself dislike Carlos Beltran. Like me, they think he’s selfish, overrated and overpaid. Those fans are also bashed and called names that I can’t repeat on a site like this. There are also many who dislike Jose Reyes and/or David Wright too. Reyes and Wright are my two  favorite players. I believe they are the most important players on the team. Some of you would probably disagree with that and that’s just fine, you are entitled to your opinions. We don’t have to agree on everything and anything. However there’s a civil way to do it without resorting to name calling or worse.

The bottom line is we are all Mets fans, we all love our team, and we all want to see them win. We buy their merchandise, we buy their tickets and we watch them regularly. We are entitled to have different views and that’s what makes sports fun and worth debating. Let’s get back to having civil, adult discussions instead of acting like children and calling people names and making fun of them simply because they have different opinions on what’s right for the team and what isn’t.

Moneyball

Michael Lewis’ masterpiece begins with five high school kids performing  multiple drills for scouts with the hope of being drafted. One of them stands out significantly over the other four; his name is Billy Beane. Beane was so unbelievably talented in the eyes of baseball’s scouts that the hype for him to make it to the majors was comparable to what we experienced with Stephen Strasburg. Beane was the poster child of a five-tool player. His fatal flaw though, was himself. Beane could not learn plate discipline, but even more importantly, his anger destroyed his playing ability. Beane would have been the first overall pick if he had not been torn on whether to go to college or to sign on with the team that drafts him, making him a risky draft choice. After being picked first round, 23rd overall, Beane ultimately decided to take the money and sign with the Mets, commencing his career in professional baseball. Unfortunately, Beane could not find any success in the majors; his numbers, especially sabermetric stats, were terrible. As a result,  nine years after being drafted in the 1st round, at the age of 27, Beane was no longer a player, but beginning instead his new career in the Oakland A’s front office.

Beane began working under Oakland’s GM Sandy Alderson, who turns him onto the idea of sabermetrics. Alderson, a military man and an ivy league graduate, got into baseball because of a man by the name of Bill James, the founder of sabermetrics. Alderson kept a stack of his books on his desk and when Beane came to Alderson, he gave him those books to read and learn from. Needless to say, Beane was hooked.

Fast forwarding to Beane as the GM of the A’s, Moneyball sheds light on his secret weapon behind his genius methods, Paul DePodesta. DePodesta, now scouting director of the Mets under new GM Sandy Alderson, used OBP and whatever other statistics his computer could generate in order to find the players most likely to have success in the majors, the A’s were not looking to “sell jeans”.

In one excerpt, DePodesta tries to get a word in to the scouts, who could care less what he had to say. They probably should have listened:

“Paul said the scouts ought to go have a look at a college kid named Kevin Youkilis. Youkilis was a fat third baseman who couldn’t run, throw or field. What was the point of going to see that? (Because, Paul would be able to say three months later, Kevin Youkilis has the second highest on-base percentage in all of professional baseball, after Barry Bonds.)”

As clearly shown in Moneyball, Billy Beane’s Oakland A’s were not just a few signings that he got lucky on, but carefully orchestrated acquisitions that not only benefited the current ballclub, but the A’s of the future. The idea of drafting carefully to produce star players, retaining them until the end of their contracts and then getting more high draft picks to produce even more stars has kept Oakland in contention while retaining their small market status. Any player the A’s lost to free agency could be easily replaced with a no-names like Scott Hatteberg, Chad Bradford or John Mabry and have the same measure of success, in most cases even more success, than with a marquee name like Barry Zito or Jason Isringhausen.

Even when the A’s lost Jason Isringhausen, Johnny Damon and Jason Giambi following their 102-win season in 2001 and were written off as a guaranteed last place team by any and every baseball analyst out there, they managed to outdo themselves the following season, winning 103 games, just as many as the Yankees had won, except the A’s did it with one fourth of the payroll the Yankees had. He proved they weren’t just some miracle fluke team, but that they were a team that could show perennial success without spending hand over fist.

Bud Selig was trying to get support for the idea of revenue sharing to help poorer, smaller market teams compete with the rich, successful teams. Selig’s biggest argument was that small market teams simply could not have the same year-after-year dominance that teams like the Yankees had. Beane blew his theory out of the water with the Oakland A’s. The second smallest budget in the big leagues had won 100+ games two straight seasons with a no-name lineup and a few starting pitchers. Beane made the baseball world stop and re-think everything that they thought they already about the game. He shattered many of the old ideas.

Beane’s method of Moneyball, very similar but somewhat different than sabermetrics, was to eliminate the concepts of ERA, RBIs, runs, etc, and to build the A’s around who were the best run producers and the best out-makers. As it turns out, these ballplayers tended to be very affordable and extremely undervalued. Beane was looking to eliminate from his club the free swingers and the players without plate discipline. He was looking to get rid of the exact type of ballplayer he once was.

 Not only did he succeed in creating his lineup of eight OBP-centered players, but he overcame the disbelief from other clubs and reporters to show that he had something, something big, something that could change the way the rest of the league and its fans looked at baseball.

Moneyball is one of the greatest baseball books ever written, if not the greatest. It is Michael Lewis’ crowning achievement, hands down. Combining not only baseball stats and analysis, but the stories and reasoning behind it. Perfectly blending the facts, his and others’ opinions, stats, and even some humor thrown in Lewis has created a genuine timeless masterpiece.

Moneyball is more than just sabermetrics, the Oakland A’s or even baseball. Moneyball is the story of one man with an amazing, astounding new way that comes face-to-face with an entire social order, unchanged for over 150 years, facing countless critics and doubters along the way, and ultimately emerges on top. Whether you are a Moneyball supporter or the opposition, we can all appreciate someone who stands up for what they truly believe and continue to work at it, and emerge victorious.

The best way to sum up this book in one sentence is from a review done by Nat Newell:

“Open this book…and your mind.”

Moneyball: The Art of Winning an Unfair Game

No matter how accurately you valued past performance, it was still an uncertain guide to future performance. If it were perfect by design then the players would be digital representations of themselves and seasons would be played out on a computer, with Las Vegas putting Johnny’s college fund on the line as to whether David Ortiz would ever regain his pre-performance enhanced game or not. But the game is played on the field and not in some cyberspace vacuum.

Actually I feel sorry for guys like Podesta and Beane. The purest of the Sabermetricians seem to take no joy from the game, for that is subjective emotion and clouds ones’ judgment. I suppose in their positions I can understand their reluctance, but I still find that to be a profoundly sad and lonely place to be. To not allow yourself to enjoy what you want to enjoy so badly is borderline Greek tragedy.

I happen to be someone who appreciates the value of finding…value, especially where it is least apparent. For years I would argue with friends and family about why the mid to late 90′s Yankees were better then any of their later teams.

To me it was obvious that players like Scott Brosius, Paul O’Neill, Tino Martinez and even Chuck Knoblauch shared a similar trait among them; plate patience with the ability to get on base. They would work the count deeper and battle the opposing pitcher so much that in little time their opponent’s weakness was exposed – their bullpens.

Lets face it if relievers were all that great they’d be starters so to me, it made sense to wear the starter down. Those particular Yankee teams embodied that premise. That’s part of the core of Saber and never once did that dawn on me at the time.

I don’t fully agree with all of Sabermetrics rationale, such as the idea that there is no such thing as a “clutch hitter”, that luck is simply the answer. Some players do well under pressure. Some don’t. Is it any different to see someone like Derek Jeter elevate his game in the postseason as it was when Michael Jordan would at times will the Chicago Bulls into dominance during the NBA Finals or perhaps Joe Montana in the Super Bowl?

Now can it be scientifically dissected and explained? Of course not, if it could I’m sure Alex Rodriguez would be one of the first to feast on the knowledge. Luck certainly plays a part in every game as I’m sure a player like Bucky Dent would admit, but talent tends to rise when need be, exceptional talent that is.

To quantify a player who excels in the spotlight – consistently – by saying his success is pure luck does a disservice to the game. Just like trying to prove the existence of God; in the end you either have faith or you don’t. And to those who argue that it’s simply luck – who would you rather have hitting with two outs, the bases loaded and down by a run in the post season – Derek Jeter or A-Rod?

When you look at the 2010 New York Mets and do a comparison to Team X – we’ll call them Team X for now – you may be surprised to say the least. First off the Mets scored 656 runs, 13th in the NL. Team X scored 697 9th in the NL. The Mets had a .314 OBP raking 14th in the NL and Team X had a .321 OBP for 9th in the NL. The Mets walked 502 times with Team X walking 487 times. Ranking both 12th and 13th in the NL.  Comparitively, their pitching were both outstanding.  The Mets allowed 652 runs, 11th best in the NL while Team X just 583 which was second best in the NL.  Considering the Mets pitching staff from 2010, it’s remarkable.

Which leads me back to the glaring difference being the 41 runs scored differential between the two. If you don’t know by now Team X happens to be the World Champion San Francisco Giants. Just take into account if the Mets had full, average seasons from Beltran, Reyes and Bay, that run differential might be a bit different, no?

The need going into the 2011 season for the Mets will be to acquire a starting pitcher, especially since Johan Santana will be out optimistically until the All Star break. How much are the Mets willing to spend and on whom happens to be the key question. We’ve seen Jon Garland go the Dodgers for a one year $5 million dollar deal and Javier Vasquez go the Marlins for a one year $7 million dollar deal.

I just don’t see the Mets spending that kind of money, period. One of the hallmarks of Saber is finding hidden value in players that others cannot or have not seen. I wouldn’t be surprised to see Alderson go after a player like Justin Duchscherer.

The former Oakland Athletic has had a barrage of injuries the past few years and has dealt with clinical depression. When healthy he’s one of the better arms in the game – when healthy – and since he’s coming off of an injury he may be willing to accept a lower end deal that’s incentive laden.

Another pitcher coming off an injury that may be affordable is Chris Young formerly of the Padres. Sandy Alderson certainly knows everything there is to know about Young and as long as he’s healthy, he too may be of interest. The bottom line, the Mets are not going to spend their way to a championship, at least not in a flashy Omar Minaya-esque kind of way.

The Mets are going to be in the market for Rick Reed type pitchers and that is more than fine with me. I’m sure we’ll hear names that we’ve hardly heard of before being bantered around to fill out the rotation. That’s where having a front office of executives schooled in the art of finding value in players becomes irreplaceable.

I know MMO has touched on Sabermetrics a few weeks back so many of you might think I’m a bit late on the subject. Maybe so but in all honesty I wanted to read Moneyball for myself before going on the record. Sabermetrics isn’t some new age alchemy, it’s taking existing statistics but looking at them in a different way.

Do I believe that a team of Scott Hattebergs would be good for the Mets? Probably not. But, plate discipline is the foundation to greater success offensively. I wonder what Ted Williams would’ve said about Sabermetrics? I have a feeling he’d actually agree on many of the principles especially when it comes to hitting as I have come to as well.