Archive for the ‘Graphing is Phun’ category

Is Justin Verlander’s fastball the most overrated pitch in baseball?

July 22, 2010

You asked and I’ll answer. Okay, so I asked and I’ll answer. Let’s get a crackin’!

In a recent Sports Illustrated poll, Justin Verlander’s fastball was voted the best in the game. Verlander won with 30% of the vote, while Jon Broxton was a distant second at 11%. Not only do the players who face Verlander believe that Verlander has the best fastball in baseball, but they overwhelmingly believe its the best fastball in the game. The fact that so many players thought Verlander had the best fastball made me head on over to fangraphs to see if the numbers backed up the players belief.

In terms of pure speed, Verlander has a case. His fastball velocity is 95.8 mph, which is second best among all ML starters behind Ubaldo Jiminez. Verlander was second last year as well with a velocity of 95.6 mph, and before a poor 2008 where his velocity dipped to 93.6 mph, Verlander was third in baseball in 2007 with a fastball velocity of 94.8 mph. So if best fastball means fastest fastball to big leaguers, than they accurately put Verlander at the top.

But as we all know, there is more to a fastball than speed. There is speed and movement, and even then a hard fastball can be an ineffective pitch. So I looked at the pitch value of his fastball compared to all other qualified pitchers who has a positive wFB.


I highlighted Justin Verlander’s bar in orange. As it turns out, Verlander’s fastball has been far from the best in 2010. His wFB is 6.3, which is currently 35th best in baseball, tied with Broson Arroyo. Bronson Arroyo isn’t exactly known for his fastball. Maybe looking at wFB/C would give us a little different result. Lets see.

Verlander is highlighted in orange. Again, the numbers don’t back up the players. His wFB/C is 0.50. Not exactly “the best” worthy.

This is only 2010 though. Maybe the players voted his fastball the best based on a dominant pitch in the past.

In 2009 his wFB was fifth best at 25.4, but his wFB/C was just ninth best at 0.97. In 2008 his wFB was 46th best(!) and his wFB/C was completely average at 0.02. In 2007 his wFB with thirteenth best at 13.3 and his wFB/C once again was simply alright, at 0.64.

Conclusion

It may not be the most overrated pitch in baseball, but Verlander’s fastball is clearly the most overrated fastball in the majors. Yes it’s fast and yes it still is a good pitch, but it has been anything other than the best in baseball the past four seasons. It worked really well for him in 2009, but outside that year it’s simply been an above average pitch- nothing to write home about.

For all the players praise of Justin Verlander’s fastball, hitters have fared a lot better against it then they would make out to believe.

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Random Hall of Fame post- BOBBY GRICH

July 1, 2010

Bobby Grich should be a Hall of Famer. Quite easily if you ask me.

To condense this post, I will be unoriginal and quasi-copy a format used on BtB in recent posts on Hall of Fame players.

***

Last week when I did a write up on Craig Biggio and his Hall of Fame chances, I researched other second basemen. In my research, I stumbled across Bobby Grich. I knew he was a HOF’er in my book, but I never seriously looked at his career. Until then- and I was blown away.

In 1992 Grich was eligible for the Hall of Fame for the first time. He received just 2.6% of the vote. Let me repeat: he received just 2.6% of the vote. 2.6%. 2.6%. Two point six percent. That, ladies and gents, is why the BBWAA SUCKS. So lets do the comparison game!

In today’s version, I’ll have graphs comparing him to HOF’ers Ryne Sandberg and Rod Carew. Why Sandberg? He is the most recent second baseman to be elected to the Hall, and of the HOF second basemen, he played in a closer generation to Grich than most others. Why Carew? While not a second basemen his whole career, both played during the same time period in the same league, and were even teammates of each other. So let’s get crackin’!

Offense: The best hitter of the bunch was Rod Carew, but Bobby Grich was hot on his tail. While Carew had a career 136 wRC+, Grich’s was 131. For a second baseman in the pre-Utley era, that is pretty damn impressive. Hell, a career 131 wRC+ is impressive regardless of position. Through this facet of the game, Grich is a HOF’er.

Defense: Here, Grich takes the cake. Among his two peers in the graph, Grich was the best fielder. Considering Sandberg was no slouch with the glove, that just shows how great Grich was. His TZ at second is +71. The fielding component of his WAR is +83. WOW. From 1970-1986, Grich only had three below average seasons according to TZ (-1, -4, and -1). He also had three positive double digit seasons (29, 17, and 11). So when it comes to defense, Grich passes the HOF standard with flying colors.

Position: Nothing to see here. Grich and Sandberg both benefited from being second basemen whereas Carew was hurt a bit for his time spent as a first baseman.

Total Runs Above Average: Again, Grich comes out on top compared to two HOF’ers. His 420.2 RAA betters Carew (389) by a little and Sandberg (289) by a lot. If A and B are HOF’ers, but C>A and C>B, then shouldn’t C be enshrined as well? So far all indicators are saying , “YES! YES! YES!”

Wins Above Replacement: Carew is the leader among the three, but lets look deeper. Lets look at WAR/700 PA, which come to think of it, I should have graphed. I’ll add that in later. When it comes to WAR/700 Grich has a 6.3. AMAZING. A WAR over 6 is considered an MVP type season. That means Grich AVERAGED an MVP season per season. Wowowowowow. As for Carew and Sandberg, respectively their WAR/700 are 5.3 and 4.7.

Wins Above Excellence: An excellent season is one where a players WAR is 3.0 or better. On the graph for this and WAM, I labeled it as RAE and RAM. Ignore that and just pretend its WAE or WAM.

Grich kills Carew and Sandberg once again. Grich’s total WAE is 48.2, which just about doubles Sandberg’s mark of 24.2. This should come as no surprise considering we already know that Grich’s average season was an MVP season according to WAR. From 1971-1983, which the exception of 1977 when he played just 52 games, Grich posted an excellent season or better every year. In fact, he did so every season that he played 100+ games.

Wins Above MVP: Here, Grich comes in last with just 4.3 WAM, compared to 4.8 for Carew and 5.2 for Sandberg. But this is a little misleading. Grich had six seasons of 6+ WAR, whereas Sandberg and Carew had five. However, in two of those seasons for Grich, his WAR was 6.0, so when I added it up, obviously a 0 isn’t going to add much. The best single season WAR mark for Grich was 8.1, which was tied for second best (along with Sandberg) among the three. Carew posted an 8.6 WAR in 1977.

***

What else does Grich have to do to prove he is a legitimate HOF’er? Compared to two fellow HOF second basemen, he not only matches them, but BETTERS them. He was a fantastic hitter and an amazing defender. He never had a down year and played at an AS and MVP caliber level almost every season. It’s quite pathetic that his only year on the ballot he received just 2.6% of the vote. I never thought this before, but Grich might just be the most unappreciated and unrecognized great player in baseball history.

And here are two graphs (nth best season and cumulative WAR by age) to visualize, conclude, and drive home the point that Bobby Grich was an all-time player who needs to be recognized by the Hall of Fame for his great play on the diamond.

Final two graphs and all stats are from fangraphs.

EDIT:

Here is the WAR/700 graph. Graphing is PHUN!

FANGRAPHS!

October 8, 2009

Hello there. Remember awhile back when we looked at WAR correlated to W% and pytgag W%? Well, Dave Cameron of FG essentially did the same. His data and results were a little bit different, but the conclusion is the same. WAR correlates well to W% and pythag W%.

Read our original piece here.

Pointless picture/caption

Pointless picture/caption

Graphing is Phun; 08/28/09 Predictive Nature of WAR

August 28, 2009

Winning% V Pythag %

The baseball Pythagren Therom (located below) is one of the first formula or statistical measures that any bright eyed, new SABR’ist is bound to found their way too.  As almost any one reading this blog would know the formula predicts team winning percentage based on the runs allowed and runs scored by a given team. By studying the things the team as a whole can control, runs scored and allowed it allows almost any analyst with a calculator to quickly decide which teams have been lucky and unlucky in a simplistic sense based on their predicted winning percentage and their actual winning percentage.

(Runs Scored)^2 / [(Runs Scored)^2 + (Runs Allowed)^2] = Predicted Win %

The graph above compares those two things (Wins %/Predicted Win%) in a basic scatter chart of every team over the course of the last 7 full seasons (2002-2008). As expected the square of the correlation coefficent .8778 provides us with assurance that the pythagreon formula of baseball is in fact a useful and well formed predictive tool for team success.

At the present time WAR is considered the most telling statistic of individual performance available to the general public. However it seems as SABR guided baseball fans we typically only use WAR to discuss individual performance, compare one player to another, debate post season awards, argue who was greater Clemente or Robinson, etc. etc. Yet WAR in its truest sense is a measure of wins above a replacement player and wins as we know are a team accomplishment. So it would seem plausible that by studying the total WAR of every team over the course a season we whould be able to accurately predict the Win/Loss record and the Run Differential of said team. The following graphs are an attempt at doing just that. As was the case above the final Winning percentage of all 30 teams over the course of 7 seasons (2002-2008) will be plotted against the corresponding total team WAR in that season for that team, also we will look at total team WAR against the predicted winning percentage through the baseball pythagreon formula.

Correlation_02_08

WAR V PYTHAG

As you will notice when studying the first chart the square of the correlation coefficent does not come in at the same level as on the Winning percentage V Predicted Winning percentage plot, however the square of the correlation coefficent coming out to .77 still gives satisfactory assurances of the predictive nature of WAR in terms of team winning percentage. The second chart produces an R^2 of .8325 an even better indicator that team WAR can predict run differential of a team over the course of a season.

What exactly does comparing the sum of all individual achievements in comparison to overall team success actually tell us? To be honest, I do not know exactly. However, it seems to reassure those baseball analysts that adhere to the fact that baseball is an individual sport parading itself as a team sport. As the statistical noise (especially in the defensive metrics) is refined and hopefully someday removed this type of analysis should continue to grow in strength.

Like I said in here, the results aren’t great but with the RD way of looking at a teams success being a pretty widely accepted way of doing things and the WAR V winning % having a pretty close R^2 over 7 years worth of data, I think its safe to say that teams with the guys doing to most individually are going to succeed more often then not then over those teams that play as a “team”. So to sum it up in a few words. Screw comradery, give me talent and production in baseball. In the end this might seem like a very basic concept, that good individual performance ends in good team results. But is it really? Further work needs to be done on this subject, weighting pitching andposition player WAR, figuring out which plays a larger role in overall team success could be incredibly useful in deducing what teams are bound to florish or fail going forward.


Graphing is Phun 7/18/09

July 18, 2009

WAR per 150 Games Played

WAR_150_Top10

Nothing too special here. Simply just a look at the WAR values of some of the greatest players of all-time on a per 150 game scale. It should not surprise anyone to see Ruth dominating the field. Some might not like to see how far down the totem pole the great Ken Griffey Jr is, but this is just one of those things reassuring myself that Griffey albeit an all-time great isn’t of the same ilk of Mays, Mantle, and Cobb in center field.

Time to play Player A or Player B (with graphs!)

July 14, 2009

This edition of Player A or Player B features two centerfielders who played in the 1990’s and 2000’s. Although I prefer UZR/150 to Total Zone, I’ll be using TZ simply because there is no UZR/150 data available to us prior to 2002.

Player A: .284/.377/.528 with a .384 wOBA, .303 EqA, 45 TZ

Player B: .286/.372/.543 with a .388 wOBA, .308 EqA, -63 TZ

Now, who would you take? The stats are close and an argument can be made for either one. Knowing who they are, I would take Player B. But based on consistency and their overall career, I would take A. So, who are they?

Player A is Jim Edmonds and Player B is Ken Griffey Jr. One player is considered good, the other is called an all-time great. A legend if you will. Yet the career statistics of these two are pretty similar. Granted, Griffey’s peak was better than Edmond’s peak, and Griffey declined greatly due to injuries, but that doesn’t change the fact that Edmonds is another underrated and unappreciated baseball player.

The point basically is that it’s about time that Jim Edmonds gets the respect he deserves. His stats are comaparable to a player who most certainly will be voted into the HOF on the first ballot, while Jimmy may not even get in at all.

Pujols Vs. the Field

July 13, 2009

It seems like common place for baseball fans to be cynics when it comes to any player performing in modern times at the level beyond greatness. Writers, bloggers, fans, and those people who don’t know anything about the game love to question every home run hit because of the mistakes of a few (well actually a whole lot of people) but it is 2009 there is a drug testing system in place in the minor and major leagues and I think it’s high time we begin appreciating some of the players we get to currently watch.

Most specifically in the charge above is accepting and delighting in the awesome ability that resides in one Albert Pujols. The following graphs are a comparison to the other ‘great’ first baseman. By no means is it a complete list of players at the position who were of the Hall of Fame caliber but it is a short list of what I have come to deem a consensus of the upper echelon of first baseman.

Pujols Vs. The Field Nth Best Seasons

Pujols V the Field _ nth season

Pujols Vs. The Field WAR/150 Games

Pujols V the Field _ War_150

You will take note that the data on the graphs comes from Baseball Projections War database and also that Pujols has an extra dot on his line which indicates the 2009 season (Zips projections for the rest of the season and a little simple math were used to project that number of 10.2 WAR, which could easily be an underestimation of where Pujols finishes this season). The first graph is WAR total in their nth best season (it is not in order of when the seasons were played), the second in a comparison of each players value per 150 games played.

I could go on and write a thesis citing every number from OBP to SLG and Homeruns about how Pujols stacks up against the very best of his positional counterparts but the visuals should do the job just as well. Lou Gehrig is rightfully considered one of the 10 greatest MLB players ever; Jimmie Foxx is often times considered in the next 10. But with this data it’s pretty reasonable to consider Albert Pujols as Foxx’s equal already and in many cases his superior. I am of the opinion that Pujols will someday become the greatest first baseman of all time, how long that takes I’m not sure (that Gehrig guy set a pretty high bar). For the sake of baseball fans, I really hope those cynics are wrong about Albert because watching someone of his talent level is a once a generation proposition.