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Repoz
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Thursday, November 30, 2017


Tangotiger Blog

I agree 100% with Tangotiger. The quest for one true number is foolhardy. Let’s try to get the best answers for the different questions with metrics specifically designed to answer those questions.

The true answer is ENTIRELY dependent on YOUR question.  You ask the question, then a solution will present itself.  But very few people think like that.

They want “the” number. And so, that’s what we are left with.  We are left with choosing the number.  And once we choose the number, meaning we’ve chosen a solution, a path, then we have to give the user the starting point, the question, and then we can add a provision to our WAR pages to say “only use the WAR on this page if you accept these assumptions as fact”.

And if you use it to answer a different question, then this solution, while it may give you close to the correct answer, might be wildly off in a few cases.

And that’s what Aaron Judge is.  He’s the exception to whatever question you ask.

Jim Furtado Posted: November 30, 2017 at 07:02 AM | 38 comment(s)
  Beats: sabermetrics, war

Wednesday, November 29, 2017

Aaron Judge, José Altuve, and the Next Battle in the War Over WAR - The Ringer

Maybe we should stop calling different systems by the same name. We have different abbreviations for BABIP and AVG because, although they are both measuring a player’s ability to get on base by hitting the ball, they are calculated differently and are different metrics. Fangraph’s WAR and Baseball Reference’s WAR are two different calculations. At least Baseball Prospectus calls their version WARP to differentiate their version.

James’ Win Shares is/was a decent concept but its construction was fatally flawed. As Rany mentioned in his article, we now have the ability to make a more nuanced assessment of individual player’s contributions, related to the timing of their performance.

But I think it’s time to do away with half measures, and decide fully what WAR is supposed to represent. If it’s supposed to represent value, then it needs to evolve to account for the fact that all players, not just relievers, can perform in ways that alter the relationship between runs and wins. WAR should reward a hitter who bats .400 with runners in scoring position and penalize one who hits .136 in high-leverage situations. If the day comes when we can evaluate for how a player performs defensively in high-leverage situations, we can account for that too.

Why not develop new metrics which project performance without needing to be tied to the WAR name? In scouting teams often use terms like Overall Future Potential (OFP) and Future Value (FV). Why not tie our statistical assessment to the common scouting lexicon?

We can, and should, have a “predictive” version of WAR that evaluates a player’s performance based on skills that will carry forward into the future. This would not only strip away “clutch” and situational hitting that doesn’t carry over much from one year to the next and strip away luck on batted balls in play, but as our data set improves would also account for Statcast data like launch angle and exit velocity, so that the player who hit a ton of at-’em balls or the pitcher who gave up a lot of windswept home runs into the first row would have a statistic that says, look, this guy might have sucked last year, but if a butterfly had flapped its wings last April he would have been really good. As Nate Silver suggested, maybe we can call it predictive WAR, or pWAR.

Jim Furtado Posted: November 29, 2017 at 11:20 AM | 16 comment(s)
  Beats: sabermetrics, war

Tuesday, November 21, 2017

A Discussion of WAR Wherein I Ardently Attempt to Avoid any WAR-Related Puns | Sports-Reference.com

It’s really tough to have a debate on Twitter. Comments, posts, and replies get so disjointed. I’m not sure Bill is actually as “steadfast” in the absolute certainty of his position. Now, he may have been at the beginning of this debate but, as the discussion has evolved, his comments, IMO, have softened as he’s heard/read other people’s comments. Again, my opinion.

In any event, Sean makes his case.

Now through years of arguing and debate, I have come to the conclusion that these two differing approaches, when considering how to value a season already in the books, are largely a matter of taste and worldview. Looking forward, I think the latter is better, but in looking back I’m fine with a person taking either approach to evaluating the value a player added to during a season. In interacting with Bill on Twitter, I believe that he’s steadfast that his view is correct and ours is wrong (or “nonsense”, “misleading”, “in error” to use his words). I disagree and believe each viewpoint has merit and is, on this issue, largely one of personal preference.

Jim Furtado Posted: November 21, 2017 at 01:37 PM | 73 comment(s)
  Beats: sabermetrics

Sunday, November 19, 2017

More on WAR – Joe Blogs – Medium

Bill is off base here. Bill seems to want to use WAR to answer questions that WAR is not really suited to answer. He’s not alone, of course. Other people use WAR to answer the MVP question all the time. The reason it’s done is, there really isn’t a tool out there designed to specifically answer the MVP question. Bill tried to do it with Win Shares. Unfortunately the adjustment methods he chose were too broad in nature.

In any event we don’t have to throw out WAR. It’s really useful for answering a lot of questions. I heartily agree with a Tangotiger suggestion:

I have always thought the best way to design a WAR would be to break it down into separate elements, which we later combine in the most appropriate way to best answer specific questions. The breakdown, IMO, should be: 1) offense, 2) defense (further broken down into components), 3) baserunning, 4) positional adjustment, and 5) context adjustment. (They should all also be presented with the related rate stat to help people answer other specific questions.)

Anyway, by introducing a timing/context adjustment as Tangotiger suggested, the value of the current WAR systems would increase. Our current data sets are much better than they were twenty years ago. We can now provide individual contexts, and need not rely on team ratios as Win Shares did. We should do it.

Unfortunately, though, the additions will generate more confusion as many people will still want to use one number to answer all questions.

“But because that is true, I ASSUMED that these were complex, nuanced, sophisticated systems. I never really looked; I just assumed that the details were out of my depth. But sometime in the last year I was doing some research that relied on these WAR systems, so I took a look at them, and … they’re not very impressive. They’re not well thought through; they haven’t made a convincing effort to address many of the inherent difficulties that the undertaking presents. They tend to get so far into the data, throw up their arms and make a wild guess. I don’t know if I’m going to get the time to do better of it, or if it will be left to others, but … we’re not at anything like an end point here. I assumed that these systems were a lot better than they actually are.”

Jim Furtado Posted: November 19, 2017 at 07:28 AM | 208 comment(s)
  Beats: bill james, sabermetrics, war

dWAR to end all WARs – Joe Blogs – Medium

People might not remember but I created one of the first WAR, along with G. Jay Walker. Although I leave the evaluation of real MLB players to others now, I still use an offshoot of the system to evaluate players for my simulation league. For my system I essentially agree with Mitchel Lichtman’s thoughts at the bottom of the article. (Excluding tone, of course.)

I don’t think you’re really understanding how this works. I’m not sure Sean [Forman] does either. There’s no such thing as defensive wins or runs above “replacement” because replacement is defined by offense and defense. And as it turns out (not that it really matters) replacement players on the average are around average on defense. All their deficiency is in offense.

There is also no such thing as positional adjustment offense. You CAN give an offensive value relative to other players at that position but you have to specify over what time period.

All that being said, you are 100% correct in that most people want to know how good defensively a player is compared to others at their position and presenting a position adjusted number confuses that. Bottom line is this: Defense should be presented relative to the average at that position AND serious people SHOULD know how to compare players ACROSS positions (by applying positional adjustments).

Offense should be presented compared to average of ALL positions. Most people intuitively know that different positions have different offenses because of the size of the pool of players that can play that position (and the physical characteristics necessary to play them). But it’s not at all necessary to know those differences or include them in the offensive numbers.

Finally it IS necessary to include positional adjustments in the “final comprehensive number” (like WAR) in order to be able to compare all players AND because when we want to know “how good” a player is we MUST incorporate his defensive position.

I know Sean understands how this all works. He disagrees, however, on how positional adjustments should fit into a WAR framework. He’s not wrong but his choice makes WAR answer too narrow a question.

Jim Furtado Posted: November 19, 2017 at 07:00 AM | 53 comment(s)
  Beats: sabermetrics, war

Judge and Altuve | Articles | Bill James Online

I agree with a lot of what Bill James said in this article. WAR is wonderful when it’s used to answer the right questions. “Who is the MVP?” is not one of those questions. This is not a new opinion for me. I wrote the following 18 years ago:

6.Value is context driven: ability is context neutral.

The genesis for this item is the whole MVP debate. Every season people argue about who the Most Valuable Player is. The biggest point of contention is usually whether the player was on a contender or not. Another sore point is whether situationally dependent stats, such as RBI and Runs, should be factored in. To me, people meld together two different questions: “Who is the Most Valuable Player?” and “Who is the best player?” Although sometimes the answer to both questions is the same, they ask two distinctly different things. While the MVP question is about value, the “best player” question is about ability. Value is context driven; ability is context neutral.

If I want to know who’s most valuable, context is important because the value of a player’s contribution changes with context. A home run has more value with the bases loaded than with the bases empty. A steal of second base has more value with nobody on than with two outs (you have more opportunities to drive the player in with less than two outs. A run in a 0-0 game has more value than a run in an 11-0 game.

With the changing value of events, it’s very important to establish the context of the player’s action to properly valuate his performance. Say a player batted with lots of runners on base and drove in an average number of those runners. What would the result be? You guessed it, a lot of RBIs. Say another player batted with relatively few runners on base, but drove in a high percentage of them. What would the result be? Again, a lot of RBIs. Which player’s performance has more value? Well, that depends on the context of the production. We need to factor in team context to properly determine the value.

Wins are the currency of value for teams. Therefore, the team with the most wins has the most value. Since team wins are produced by the combined accomplishments of its players, the players’ value equal the team’s value. This means that two players who make exactly the same contribution do not necessarily have the same value. This greatly complicates answering the whole MVP question.

To illustrate, here’s a word problem for you. Two gentlemen (let’s call them Player A and Player B) play on two nearly identical teams. Each team scored 800 runs. Each team possessed fielders of exactly the same quality. The difference between the two ball clubs is the quality of the pitching staffs. Team A’s pitchers allowed 650 runs, while Team B’s pitchers allowed 700 runs. All this resulted in 96 wins for Team A and 91 wins for Team B. If I tell you both players generated 80 runs for their respective teams, does this mean they were equally valuable players?

Considering this is a baseball book rather than a math test, I’ll just give you the answer: no, Player A was more valuable. Why? Because in the context he operated in, his runs were more valuable–they bought more wins. Using a modified version of Pete Palmers runs to wins formula, I determine it cost 9.97 runs per win in Team As context [(10/3)*SQRT((800+650)/162)] and 10.14 runs per win in Team Bs context [(10/3)*SQRT((800+700)/162)]. Player A’s 80 runs purchased 8.02 wins while Player B’s 80 runs purchased 7.89 wins. Therefore, Player A was more valuable.

Ability, on the other hand, is context neutral. The ability to hit a ball 500 feet is the same whether a player is at Coors Field or at the Astrodome. The fact that the same ball might travel 540 feet at Coors is irrelevant. The change in conditions causes the ball to travel 40 feet farther, not a change in ability. (A non-baseball example of the same concept is weight. Take a 200 pound item on Earth and weigh it on the Moon. What does it weigh? About 32 pounds. The item doesn’t change, the conditions do. The change in conditions, gravity in this example, accounts for the difference.)

Since the best player is the player with the most ability, ability is what we should measure to answer the “best player” question. To measure ability, we must first filter out context. Once that’s done we can directly compare player in a neutral context–we can compare their ability.

To answer the MVP question, we need to incorporate context. Not having context, however, doesn’t prevent WAR from being an extremely valuable statistic. (It’s still great for answering a myriad of other important questions.) Its use just needs to be restricted to the tasks where it’s the appropriate tool. As Lee Panas said to me on Twitter, “I think there is a lot of confusion as to how and when to use it.  I see too many people using it as a hammer.” I certainly agree. We don’t need to get rid of the hammer; we just need to better differentiate between nails, screws, and fasteners so we choose the right tool to compete the task at hand.

Jim Furtado Posted: November 19, 2017 at 06:14 AM | 68 comment(s)
  Beats: sabermetrics

Tuesday, October 24, 2017

Dodgers vs. Astros is a World Series for baseball’s Information Age – Orange County Register

It’s not your daddy’s Moneyball.

The Dodgers and Houston Astros are playing in the World Series this week. But this is also the Proprietary Information Super Bowl.

Fifteen years into the post-Moneyball era, an analytics department is as essential to a major-league team as fungo bats and sunflower seeds. In the early 2000s, the disparity between the sophisticated and the unsophisticated was wide. Not anymore, every team now searches for advantages in algorithms and metrics, taking the data available from sources like StatCast, PITCHf/x and Trackman and squeezing it for all its worth.

“You should know there are at least a half a dozen, maybe 10 teams that are all in on analytics,” says Dodgers team president and CEO Stan Kasten. “Most of the teams in the playoffs were those kind of teams.”

Jim Furtado Posted: October 24, 2017 at 01:44 PM | 0 comment(s)
  Beats: analytics, astros, dodgers, sabermetrics

Friday, October 06, 2017

Astros at leading edge of analytics and their success is proof positive

A lot of good stuff in this one.

“You’ve always got to be questioning what you’re doing well and working on the things you do poorly,” said Hinch. “If you’re on the back end, following these massive trends, whether the use of technology or the use of analytics, imagine how far out in front the other teams are. I think that intellectual curiosity and fear is what drives you to get better faster.”

Jim Furtado Posted: October 06, 2017 at 06:36 PM | 2 comment(s)
  Beats: astros, red sox, sabermetrics

Saturday, September 09, 2017

Twitter: Brian Kenny: Is a consistent player more valuable than a volatile player?

I’m going to have to think about it because I can’t remember off the top of my head but…haven’t there been studies which looked at this? If there haven’t, this can be simulated. As a proxy, looking at injured players with replacement players would give us an answer. It’s essentially a question about peak vs. average.

On the other part of the question related to the Jeter hitting good pitching versus a guy who feasts on bad pitchers but is overmatched against better hurlers, I also believe someone has looked at this.

Anyone remember? I’ll try to look through my stuff at a later time. I have family stuff the rest of the weekend.

Edit: A quick Google search led me to some work by Bill Petti.
Dave Levine has looked at streakiness. (PDF)

Jim Furtado Posted: September 09, 2017 at 01:10 PM | 8 comment(s)
  Beats: sabermetrics

Thursday, September 07, 2017

Sabermetrics Starter Cards | Banished to the Pen

Get your sabermetrics cards.

Jim Furtado Posted: September 07, 2017 at 09:21 AM | 0 comment(s)
  Beats: sabermetrics

Tuesday, August 29, 2017

Why Are Some New Statistics Embraced and Not Others? - The New York Times

Tango and company get some kudos for the stuff they are doing at MLB.com.

‘‘Bill James had a great line,’’ Tom Tango, the senior database architect of stats for MLB Advanced Media, told me. (If James is largely considered the godfather of sabermetrics, Tango could be its Michael Corleone.) ‘‘If you have a metric that never matches up with the eye test, it’s probably wrong. And if it never surprises you, it’s probably useless. But if four out of five times it tells you what you know, and one of out five it surprises you, you might have something.’’

Jim Furtado Posted: August 29, 2017 at 12:41 PM | 39 comment(s)
  Beats: sabermetrics, statistics

A Visual Case for the DH – The Hardball Times

Just think of all the strategy there would be if we just randomly pulled a fan out of the stands to play first base.

Jim Furtado Posted: August 29, 2017 at 06:28 AM | 0 comment(s)
  Beats: designated hitters, sabermetrics

Wednesday, August 23, 2017

How Promotions and Demotions Affect Relief Performance – The Hardball Times

I am struck by the fact that all groups outperform their projections on average. I suspect this fact has more to do with the projections themselves and doesn’t mean there’s a hidden pattern here we’re not seeing. If anyone has suggestions for other projection mechanisms that would be suitable, let me know in the comments.

The conclusion here seems straightforward. I can find only the most tenuous connection between a role change for a reliever and his subsequent performance on the field. If a reliever does struggle or suddenly become lights out, look for other factors besides his recent promotion or demotion.

Jim Furtado Posted: August 23, 2017 at 10:15 AM | 0 comment(s)
  Beats: relievers, sabermetrics

Wednesday, August 16, 2017

On the risks of categorizing a continuous variable (with an application to baseball data)

Don’t be so quick to discard the bunt into the dustbin of history.

From a statistical perspective, hopefully you can recognize both the dangers of categorizing continuous data, as well as the attractive features offered by a GAM (and if you want to try a GAM yourself – the code is up here).

From a baseball perspective, the hardest hit balls do increase error rates. Additionally, with my intuition being that errors are often discarded from the perspective of analyzing hitter talent, this type of error creation could be worth thinking more about. In addition to a side benefit of someone who hits the ball as hard as Aaron Judge or Giancarlo Stanton, having good, capable bunters could actually be undervalued. Putting down a sacrifice is generally not considered worth it (trading an out for moving up a base), but with error rates as high as 14%, there may be more to the story.

Jim Furtado Posted: August 16, 2017 at 08:50 AM | 17 comment(s)
  Beats: sabermetrics

Applying Asset Pricing Theory to MLB – The Hardball Times

Interesting. She doesn’t quite get what replacement level is, however.

Jim Furtado Posted: August 16, 2017 at 07:54 AM | 4 comment(s)
  Beats: sabermetrics

Monday, August 14, 2017

Benetti: We can learn a lot from baseball’s numbers game

The high point before Jeter returns the numbers back from whence they came.

Jim Furtado Posted: August 14, 2017 at 09:40 AM | 0 comment(s)
  Beats: sabermetrics

Wednesday, July 26, 2017

The Man Who Brought Sabermetrics to Japanese Baseball

An interesting look at Japan’s version of Bill James.

Jim Furtado Posted: July 26, 2017 at 08:24 AM | 1 comment(s)
  Beats: japanese baseball, sabermetrics

Wednesday, July 12, 2017

Midseason 2017 Strike Zone Review – The Hardball Times

Great stuff on the strike zone.

Jim Furtado Posted: July 12, 2017 at 09:18 AM | 0 comment(s)
  Beats: sabermetrics, strike zone, umpiring

Tuesday, July 11, 2017

Baseball Prospectus | Prospectus Feature: Measuring Pitcher Similarity

Some interesting work on pitch similarity.

Jim Furtado Posted: July 11, 2017 at 08:51 AM | 0 comment(s)
  Beats: pitching, sabermetrics

Thursday, July 06, 2017

Sprint Speed Helps Tell Us Who’s Good At Baserunning And Who’s Just Fast

As you might suspect, I have been searching for stuff comparing Sprint Spead to Baserunning Runs. Here’s a pretty interesting look from a week ago.

Jim Furtado Posted: July 06, 2017 at 06:54 AM | 57 comment(s)
  Beats: sabermetrics, statcast

Evaluating the St. Louis Cardinals baserunning with Statcast – THE INTREPID STL

Just stumbled onto this. Here’s an interesting look at the Cardinals baserunning using advanced metrics.

Jim Furtado Posted: July 06, 2017 at 06:33 AM | 2 comment(s)
  Beats: cardinals, sabermetrics, statcast

Wednesday, June 21, 2017

How the wonks won baseball coverage

“It’s a ball now. It’s my favorite period in the business — by far,” says Tom Boswell of The Washington Post, a great baseball writer who straddles sharply different eras.

“I wish it had always been like this. You have all the old approaches to coverage still available — profiles, human interest, humor, etc. But so much more, too. For people who love to analyze (me), there’s nothing as good as real data, plus tons of unmined data where you can discover patterns that others haven’t spotted. FanGraphs, MLB.com/Statcast and baseball-reference are just an addictive gold mine. You have to restrain yourself.”...

It wasn’t long ago that baseball statisticians like Bill James were a curiosity, with the rise of the species even spotlighted in a Hollywood movie, “Moneyball,” about the Oakland A’s and based on the Michael Lewis book that chronicled Billy Beane, its idiosyncratic general manager.

Now, metrics rule baseball. As put by Keith Law, a baseball expert at ESPN who once worked for the Toronto Blue Jays, the revolution is over. People aren’t slaves to data but it plays a central role, with many basic assumptions of the past undermined. Thus, even the casual fan may view a player’s on-base percentage as more important than his batting average.

RoyalsRetro (AG#1F) Posted: June 21, 2017 at 04:05 PM | 19 comment(s)
  Beats: bill james, reporters, sabermetrics

Saturday, January 21, 2012

NYT: Q. & A. With Tom Seaver

Q. Ryan has campaigned against pitch counts. Do you agree?

A. There’s nothing wrong with pitch counts. But there’s an addendum to that. I presume Nolan thinks the same way. But it isn’t a blanket pitch count. People say, “I bet the pitch count drives you nuts.” Heck no. I had a pitch count. My pitch count as a general rule was 135. And I knew how many pitches I had when I went to the mound for the last three innings. And I wasn’t going to spend eight pitches on the No. 8 hitter. On the second or third pitch, he should be hitting a ground ball to shortstop. It might not work like that all the time. But theoretically, you have an approach about how you’re spending your bullets.

There’s nothing wrong with pitch counts. But not when it’s spit out by a computer and the computer does not look at an individual’s mechanics. And you can’t look at his genes. It should come from the individual and the pitching coach and the manager.

Q. Will your former manager Gil Hodges, a former Dodger, ever get into the Hall of Fame?

A. I don’t know. Everybody in the New York area wonders why he’s not in. His numbers are high middle. But what else did he do? He was the leader on that ball club that went to the World Series and beat the Yankees. He was the leader of a ball club and franchise that went to the World Series. If you look at his body of work I say yes. Absolutely.

Q. Should steroid users be allowed into the Hall of Fame?

A. The commissioner and baseball has to figure that out. They’re going to have guys that have great numbers not in the Hall of Fame. They have to figure that out.

Thanks to Wrecki.

Repoz Posted: January 21, 2012 at 05:36 PM | 3 comment(s)
  Beats: history, mets, sabermetrics

Friday, January 20, 2012

Grantland: Bill James: The 100 Best Pitchers’ Duels of 2011

Bill James sez it all!

My list of the 100 best pitchers’ duels of 2011 is better than your list, for one reason and one reason only.

You don’t have any list.

 

 

Repoz Posted: January 20, 2012 at 10:06 AM | 69 comment(s)
  Beats: history, reviews, sabermetrics

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