The Truth about Prospects

The Truth about Prospects

 

 

Prospects fail.  I could just write that and be done with this article but that’s the main idea.  There is a farm system that I have followed closely over the last few years and that’s the Chicago Cubs system.  I will try to give you examples of players from the system that meet the reasons of why prospects fail.  So here we go.

 

Injuries are a huge reason of why prospects fail.  Josh Vitters, in case you’re not familiar with him is the 3^rd overall pick of the 2007 draft by the Chicago Cubs.  Josh Vitters got injured and basically just went up the levels based on his prestige.  On the pitchers you see Tommy John surgery killing people’s development time lately. 

 

Tools.  You hear that word all the time when looking at prospects mostly position players.  Some players have elite speed, elite defense, but they can’t hit.  Just can’t do it.  Tools are like a box of candy that’s empty.  The box gives you promise but the inside is what ultimately determines your future.  Tools are worthless unless the player can hit a bit.

 

Strikeout rate or SO % for pitchers and hitters are why some fail.  Most pitchers that are good to elite pitchers get strikeouts.  Most hitters that are .300 hitters don’t strikeout 130+ times in a season.  You can, in my mind predict where a pitcher/hitter will land based on strikeouts.  Jacob Turner used to be a top prospect for the Detroit Tigers.  I for some reason really, really, liked him.  I thought he was destined to lead anchor the Tigers rotation for many years.  That of course didn’t happen for two reasons.

A)    He was one of the pieces traded in a deal that sent Anibal Sanchez and Omar Infante to the Tigers.  Turner went to the Marlins. 

B)      While in the minors his strikeout rate was never particularly good.  This lead to his eventual slow gradual decline into Miami.  Now he has a 6+ ERA in coming out of the Marlins bullpen at the moment.

 

 

On the hitter’s side of things for this we look at Brett Jackson, former Cubs top prospect.  Brett was a pretty decent defender and he could swing the bat pretty good too.  He had one glaring flaw however and that was he struck out.  A ton.  This prevented his Batting Average from really ever getting to high.  Eventually, he appeared in the majors in 2012 did dreadful got sent back down and is now toiling in Triple AAA likely on the verge of being out righted off the  40 man roster.  Strikeouts can help you or destroy you.

 

Aggressive promotions are also a way to make prospects fail.  Don’t really know of many examples however that had this happen.

 

Control problems are huge nowadays.  Some guys need to switch from being just throwers to pitchers.  Trevor May used to be a pretty good prospect in the Phillies organization.  I admit had a feeling about May that he would succeed.  Then he went to AA.  And that’s where his main flaw killed him.  Walks. Walks. Walks.  Even if you have huge strikeout numbers like Trevor May did, walks can kill you.  This is of course not his only flaw.  He was a fly ball pitcher that gave up a bit too many home runs. 

 

Oddly enough one flaw is that prospects don’t really care about it.  They just want money.  All they do in the winter is get fat and eat junk.  Jesus Montero quickly comes to mind as a great example.  Jesus is I believe is still in AAA and is currently just another guy.  He used to be the sixth best prospect in all of baseball, now he’s just a bad hitter.

 

Some pitchers are very highly rated (Trevor Bauer) but just can’t put it together.  One reason his is makeup, in which he thinks he doesn’t think he needs to make adjustments.  But he’s currently just a AAA/MLB guy with star potential looking good some nights and terrible some other ones.  He’s just in a circle, and there seems like no end to it.  Kevin Gausmen is another name that comes to mind in this category.  They have potential but the team has to keep them in the Majors to show what they got.  It’s a weird world to be in.

 

Players are not put in leagues/parks they can succeed in.  Mark Appel has like a crazy 10.80 ERA in High A Lancaster in a hitter friendly league and park.  It’s of course not all due to that but some of it is. Mark Appel’s upside is slowly declining because of it.  Or maybe Appel is just not a very good pitcher. 

 

Some “prospects” are just too old.  They no longer have upside because their age is slowly increasing and by the time they make it they will no longer have the upside they once had.  David Hale of the Braves is a good example born in 1987 and still in the 2014 Prospect Handbook. 

 

Thanks for reading.  Next time I will be taking a look at the Houston Astros rebuilding process and why it might not work.  Follow me on Twitter @CastroRizzo         

Total Runs for Beginners

NOTE: This is can also be found at beisbols.org which I now submit articles to.

 

About a year ago I was poking around the Fielding Bible Volume Three and I came across an interesting chapter.  It was about a stat they called Total Runs.  Basically it combines hitting, fielding, base running contributions and one positional adjustment.  I have since added other things to it but we’ll get to that later.  I created a little mini introduction to it on a Microsoft Word document and here is my original take on it. 

 

Total Runs First Thoughts

 

A baseball player isn’t just a hitter, or a fielder, or even a base runner.

He's all of these things.  How can we measure this is in a run form.

 

Run Form?

What I mean by run form is that it is in the form of runs and not Wins like WAR attempts to do.

 

Formula?

The formula for this metric is

Runs Created+ Defensive Runs Saved+ Base running Runs+ Positional Adjustment

For the Positional Adjustment we use the following method.
Catcher:42 runs
First Base:13 runs
Second Base:32 runs
Shortstop:36 runs
Third Base:25 runs
Left Field:19 runs
Center Field:29 runs
Right Field:20 runs
DH:-7 runs


Now let's see some of the more interesting results, from 2012 stats,

Results

Based on 2012 stats, we see the following. 

Darwin Barney is an interesting case.  Barney's worth to his team in the form of Total Runs went like this.
Barney Runs Created:60
Barney DRS:28
Barney Base running runs:4.3
Barney Positional Adjustment:32 runs

Barney Total Runs: 124.3

This is actually quite a high total, mainly because of his defensive contributions.  You will be shocked to know what I figured next though.

Miguel Cabrera on 2012 stats is an interesting case also.

Cabrera RC:123
Cabrera DRS:-4
Cabrera BsR:-2.9
Cabrera Positional Adjustment:141.1 runs

The Total Runs separating them?  16.8 runs...

Barney is an extreme under rated based on this metric, or is it saying Cabrera is overrated?  No matter the reason, I think this stat is a very good one.

 

Conclusion:

 

It seems to be a decent metric, perhaps rating Barney rather high and Cabrera rather low but I like what the metric contains to it.

 

Back to July 2014 now, you can Darwin Barney is actually not really that good.  His current OPS+ for his career is 69 (100 is average) and Miguel Cabrera is pretty good. 

 

After my first thoughts had been typed out on Total Runs, I must admit the metric was just one I liked and used a bit.  Since then I have expanded to Park Factors.  Park Factors are very, very, important.  A player that plays at Coors Field should be penalized because if you do poorly there you are likely a pretty bad hitter.  Meanwhile, a player that plays at Petco should be given some extra runs because some of his outs would be gone in most other parks.  Here are 2013’s park factors. 

Total Runs, 2013 Park Factors

 

Average Park: 100

Hitter’s Park: Above 100

Pitcher’s Park: Below 100

 

Chase Field: 99

Turner Field: 100

Camden Yards: 100

Fenway Park: 101

Wrigley Field: 109

U.S. Cellular Field: 97

Great American Ballpark: 97

Progressive Field: 98

Coors Field: 110

Comerica Park: 107

Minute Maid Park: 98

Kauffman Stadium: 103

Angel Stadium of Anaheim: 100

Dodger Stadium: 98

Marlins Park: 101

Miller Park: 107

Target Field: 102

Citi Field: 89

Yankee Stadium: 106

O.co Coliseum: 96

Citizens Bank Park: 97

PNC Park: 99

PETCO Park: 90

AT&T Park: 96

Safeco Field: 99

Busch Stadium: 96

Tropicana Field: 95

Rangers Ball Park in Arlington: 102

Rodgers Centre: 101

Nationals Park: 109

 

So for example let’s say Player A put’s up 67 Total Runs with Coors Field being his home park.  Since Coors is 10 above 100 (100 being average) you would subtract ten from his score of 67 to make it 57 Total Runs.  I feel the Park Factors adjustment is necessary for the metric to be fair and be as accurate as possible. 

 

Then about a month ago I realized that an adjustment needed to be made to compare players from historical seasons.  League run environment adjustments.  Some leagues such as 1968 or 2004 are so heavily skewed in one’s favor that they need to be adjusted for it to be fair and level.  So to fix the issue I created a chart, roughly to make a minor adjustment for this.  Here it is below

    I constructed a chart to push up or push down Total Run numbers based on league run environments.  Of course the higher the RPG numbers, the lower Total Runs score they receive because it was easier to hit in. 

Runs Per Game

4.00-4.15: +7 Total Runs

4.15-4.22: +3 Total Runs

4.23-4.30: +0 Total Runs

4.30-4.40: -4 Total Runs

4.40-4.50: -7 Total Runs

4.50-5.00: -12 Total Runs

NOTE: For leagues that are so heavily skewed I mean like 3.48 Runs per Game then I make bigger adjustments.  They are not shown on this chart.

 

Ok, now that is the final thing I have added to Total Runs.  The results of this are most fun of course, comparing players and such.  I wanted to introduce the stat first though so I didn’t just show you numbers and you having no idea what they mean or how I got them.  In the next post we will compare some players using Total Runs, such as Barry Bonds, Nap Lajoie, and more from a lot of eras.  I would also like to thank the owner of this website for giving me a chance to write articles on this pretty good looking blog.  I understand this can be a dull read but promise next few will be better.  Thanks for reading.  

Follow me on Twitter @CastroRizzo for a lot more baseball. 

The Hard Part

My Fielding Linear Weights metric is flawed.  The unfortunate part about the flaws on the metric are that they are hard to fix.  By hard, I mean I don’t exactly understand how to fix them.  Bill James sums it up best in my mind.  He said something along the lines of the fielding stats from a poor team are not that much different from a good team.  I believe I can relate to that on a player level.  My stat does not understand how to separate performances from good and bad.  It usually just comes up with random numbers in which one should have little confidence in.  The numbers seem to close together, bad fielders rate the same as good fielders.  That was my goal to fix, to determine good fielders from bad fielders before I even began work on the metric.  I don’t know if my formula just wasn’t in depth enough or not.  It seems to me that’s part of the problem.  Not enough weights, not enough in the formula to make it different. 

Then the flawed nature didn’t stop there however.  I put too much stock into Range Factor being a great metric.  Without adjustments for groundball staffs or fly ball staffs, plus more issues that need to be adjusted for on Range Factor.

 

The reason we need to get this fixed is because as of now for historical Total Runs counts for players I do not have and will never have Defensive Runs Saved data.  So, I have to rely on something nobody can rely on.  Fielding Runs.  Fielding Runs, being criticized by a lot of people is not too accurate.  My goal is simply to create a metric that has more accuracy then Fielding Runs.  My estimated Runs Created formula took me like ten minutes to create and I find it pretty good indication of how good a player batted in a season.  But fielding, with Fielding Runs is shaky at best.  So that’s our goal create a reliable Fielding Linear Weights metric then apply to make our Total Runs metric the best out there. 

Thanks for reading.   

Total Runs for Great Seasons

Total Runs for player’s top seasons

Bonds 2004: 230 Total Runs

Lajoie 1901: 150 Total Runs

In defense of my Lajoie rating, I know many of you will think this is awfully low.

A)    Lajoie only walked twenty four times in his best season 1901.  He was the best hitter in the league but it doesn’t offset his terrible walking.  His Secondary Average which takes into account walking skills, stealing bases, and total bases is a dreadful .219.   I know there was not a lot of people who supported walking in those years, instead opting to try to win the batting title.  Still, I think he was one of the most overrated players in MLB history. 

B)    Don’t get me started on his fielding.  In his 150 Total Runs score from me included Fielding Runs which thinks he is one of the best fielders ever scoring him at +22 runs.  So consider that 118 score generous to say the least.

 

Maris 1961: 127 Total Runs

A)    This number has been modified for one reason.  My metric did not know how to handle the impact of big power seasons.  So I added a bit of a twist to it.  If you hit 40+ bombs you’re score will go up thirty Total Runs.  There is no adjustment for 30+ homeruns has to be above 40+ homeruns.  So, yes I admit before I added that twist this number was 90 which I thought was absolutely ridiculous.  There has to be a human element to your stat, it has to make sense that people rate where they do.

 

 

Gwynn 1987: 154 Total Runs

Wagner 1908: 174 Total Runs

 

A)    Wagner’s Total Runs before the League Run Environment adjustment were not all that impressive.  Now after the adjustment because of the extreme pitcher friendly league Wagner’s Total Runs boost by about +30.  I mean even after the League Adjustments it might still be a bit low for how bad Wagner’s fellow teammates did compared today’s standards.  His league that year had a .299 OBP, pitchers in his league pitched to a 2.35 ERA and somehow in between all of that Wagner found a .415 OBP.

 

Morgan 1975: 164 Total Runs

 

A)    Joe Morgan used to be embraced as one of the players sabermetrics made look better.  That had been true until advanced defensive metrics have been released, many of which aren’t big fans of his fielding.  Morgan’s season compares well to Wagner’s and Gywnn’s seasons too.

 

Giambi 2000: 153 Total Runs

A)     Giambi could really walk, and it shows in his Total Runs score. 

 

Just to sum up what I’ve done in this post I’ll make a chart.

Name	Year	Total Runs
Barry Bonds	2004	230
Nap Lajoie	1901	150
Roger Maris	1961	127
Tony Gywnn	1987	154
Honus Wagner	1908	174
Joe Morgan	1975	164
Jason Giambi	2000	153

 

I will do more of these in the future, thanks for reading. 

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