Tuesday, December 18, 2007
Allow me to try and apply the same scenario elsewhere to demonstrate why this reasoning is fallacious.
Let's say that you work in a company of 3,000 employees. Management has been concerned for a while that there has been a large amount of theft from the company occurring by employees. To counter this, they hire a well respected investigator, Marge Gitchell, to try and uncover the culprits. Marge immediately sends a company wide email urging employees to talk to her about the large amount of thievery going on in their ranks.
You glance at the email briefly, and then move it to the trash in your email client. It's not really your concern because you don't steal from the company and you don't pay enough attention to your officemates to know if they are stealing either. You feel that you have nothing to add by talking to Marge.
A few months later, you are shocked to find that Marge has listed you on her report as a likely thief. Fellow employees and management are outraged. Heck, it's even on the local news, and everyone wants to know why you didn't defend yourself to Marge while the investigation was ongoing.
What are you going to say?
Sunday, December 16, 2007
I have only a few observations of this subject, which I should note are all going to be influenced by the fact that I personally love Andy Pettitte.
- Pettitte claims to have taken HGH while injured. Honestly, taking HGH while injured does not bother me in the slightest, provided it is taken with a doctor's approval. In this case, Pettitte does not appear to have received this approval. This is unfortunate, and certainly implies that what he was doing was at least illegal from a U.S. law standpoint, if not a MLB standpoint. Personally, I don't see the difference between taking a drug to help you recover from injury and having surgery to help you recover from injury.
- As far as actually using HGH is concerned, I will simply reiterate that we actually don't know anything about the effects of HGH on athletic performance. In fact the best evidence that we have is that it does not help athletic performance. This is a highly relevant point.
- In some circles, there has been gloating over that fact that Pettitte, a devout Christian, has been busted doing something illegal in a very public setting. Some people, it seems, like nothing more than to see publicly religious people exposed as being just like everyone else. This is a sad situation. Being Christian means holding yourself to a higher standard. It doesn't mean that you are always going to live up to that standard. That's not hypocrisy; that's humanity. Hypocrisy is holding others to a higher standard than you hold yourself. In his statement, Andy admits that he "was not comfortable" with what he was doing, and so he stopped. It sounds to me like he was holding himself to the same standard to which he professes to hold others. When violating that standard rightly disturbed his conscience, he quit engaging in the behavior that he felt was wrong. Provided that his account is sincere, which admittedly it may not be, any gloating over the public humiliation of Andy Pettitte exposes both a misunderstanding of what it means to be Christian and a bigoted view of Christianity.
Friday, December 14, 2007
If Selig chooses not to try to suspend Clemens, Clemens can use this as public talking point #1 that he is not guilty of PED use. If Selig does try to suspend Clemens on the basis of the Mitchell Report, Selig will be forced to fight the players' union. The players' union will drag lawyer after lawyer after lawyer in front of an arbitrator, each saying that the evidence against Clemens is highly suspect and does not warrant a suspension. Clemens would almost assuredly win that fight, giving him public talking point #1 that he is not guilty of PED use.
Plus, he would do this while not being suspended for drugs while he's playing yet another year. Remember, much of Clemens' late career dominance came while MLB had drug testing. If he plays in the National League, he'd probably put up very good numbers, further bolstering his case. He can even make a public show of his lack of positive test.
What does he have to lose?
I have not read it. I probably will not read it. I just don't find it that interesting. Why?
Well, what did we know before the report came out?
- There were guys in MLB using PEDs.
- There was no discernible pattern to the people who did use PEDs. That is, you cannot tell who a PED user is based on their physique, statistics, career path, etc.
- The effect that PEDs have on baseball performance is hard to quantify. We can say for sure that the players taking them thought that they helped.
- There were guys in MLB using PEDs.
- There was no discernible pattern to the people who did use PEDs. That is, you cannot tell who a PED user is based on their physique, statistics, career path, etc.
- The effect that PEDs have on baseball performance is hard to quantify. We can say for sure that the players taking them thought that they helped.
Most importantly, it must be recognized that even if all of the players on the list are guilty as charged, the list is far from complete. In fact, because it's based largely on the testimony of a few dodgy witnesses, the players tend to be clumped around certain teams with whose players the witnesses did business. The list hardly convicts anyone, but most importantly it absolves no one. The single biggest mistake one could draw from the report would be to assume that these players are the only abusers of PEDs.
Finally, I hope that the idiocy already springing up around the country about Roger Clemens' involvement will quickly cease. People are using these allegations as a way to explain ex post facto why Clemens was able to succeed so late into his career and why his career surged at the various points that it did. This is nonsense.
First, it bears repeating that if Clemens did take steroids, it would have been meaningless if not for his legendary work ethic. The work ethic is not contradicted by steroids allegations. Indeed, it is corroborated. Use of steroids requires a more intensive workout regimen. It is not a shortcut that allows one to work less hard.
Secondly, the dates that he allegedly took them do not mesh well with his career. He reportedly began taking them in 1998, his second otherworldly Cy Young season with the Toronto Blue Jays. Indeed, his 1998 was worse than his 1997. Furthermore, he was all set to retire in 2003 after two seasons being a slightly better than average pitcher when he resurfaced in the National League Central and was again a dominant pitcher. It would be very hard to separate the effects of moving from the American League East to the National League Central from the effects of alleged PED use.
Indeed, the fact that the list is so populated with marginal players is telling in Clemens' case. Rare as it may be, transcendent players do appear every so often. Given the list of PED users in Senator Mitchell's report, it is hard to make the case that Clemens owes his success to illegal drugs.
Tuesday, December 4, 2007
For all fellow Yankee fans out there, Pete's message is spot on: re-f***ing-lax. The worst thing that can happen to the Yankees, now that Andy Pettite is back, is that they replay last year with the same offense (albeit one year older) and a pitching staff fortified with real pitching prospects instead of the stopgaps that they had to use last year. Panic is not in order, even if the Sox do get Santana.
Wednesday, November 28, 2007
First, I want to summarize one more test that I ran using the Pythagorean Theorem of Baseball model of expected performance that I've used in previous posts. I started with a team with 750 runs scored and 750 runs allowed and then gave it 100 runs to add to its runs scored or subtract from its runs allowed in any combination. Then I checked to see which combination would give the highest expected performance.
I had expected beforehand (foolishly as it turns out) that somewhere around 50 additional runs scored and 50 additional runs saved would be the optimal expected winning percentage. As it turns out, you achieve the optimal result by deducting all 100 runs from runs allowed. The difference is not large, only one win over a 162 game season. This gives credence to the idea that a runs saved is more valuable than a run scored, though only marginally so.
This got me thinking about why this was the case. It was only then that it occurred to me that the only way to expect to win 100% of your games was to allow zero runs. No matter how many runs a team scores, if it allows even one run over the course of a season there is a chance that it will lose a game. This is why our examination of the problem using the PToB values the run saved slightly more than the run score: it puts your team closer that the perfect scenario.
Another way of looking at it is that increasing how many runs you score acts as inflation in the run economy of baseball: it devalues all other runs. Conversely, allowing fewer runs is deflationary: each run is now worth more. Therefore, an absolute difference of 100 runs is a lot more significant when the overall run totals are lower. It's exactly the same difference as the difference between Jane making $5,000 more than Dick in a mythical two-person economy in which there are only $50,000 total and Jane making $5,000 more than Dick in a $10,000 two-person economy. The differences are identical, but the difference is worth a lot more in the $10,000 universe. Since saving more runs decreases the total amount of runs in the baseball universe, you need a larger increase in runs scored to have the same impact on winning as a given decrease in runs allowed.
This ignores, however, a key aspect of the baseball landscape: you cannot save runs beyond zero runs allowed. On the other hand, you can continue to score runs ad infinitum. In other words, the value of saving runs is offset by the fact that it will quickly become very hard to make further gains in that area. It is possible, in any given baseball game, to pitch far less than perfectly and still achieve the perfect outcome for runs allowed: zero. Shutouts are fantastically more common than perfect games. Thus, even if you continue to improve your pitching, you should reach a point of diminishing returns where even though you are pitching better, it is not reflected in your runs allowed total. With hitting, you can theoretically keep improving it until you reach the perfect offense, one that never makes an out and therefore scores an infinite number of runs.
Now, on to my second observation. (Yes, that's right. The preceding 6,000,000,000 words are only my first point.)
I was going to turn to historical data and run an experiment to see what the impact of scoring and allowing additional runs was historically. Specifically, for each trial I was going to select a real baseball team of ages past and then randomly select a game from that team's season from which to subtract one run from their opponent's run total. I would do this 25 times for each team (allowing the same game to be picked twice, resulting in further deduction) and then measure what that team's new record would be (ties counting as 0.5 wins and 0.5 losses). I would then run a sufficiently large number of trials and see what the aggregate impact was. Then, I would repeat the process for runs scored, measuring what the impact was.
Then, another thought occurred to me that saved from a lot of useless work. What if instead of picking games at random, I instead enumerated all possible combinations of 25 games (again, with multiplicity) for each trial?* In that case, each trial in the runs allowed test would have a corresponding trial in the runs scored test that had the exact same 25 games picked (and vice versa). And of course, the impact of deducting a run from an opponent's total in an given game is exactly the same as adding a run to your own. Therefore, if we enumerate every possible selection of games, the results for the runs saved test would be exactly the same as the results for the runs scored test! Right?
Sort of. There's only one problem with the above logic. We haven't decided what would happen when one of the selected games for the runs allowed test was already a shutout victory. Do we skip that game and then that team loses one of its runs saved? Or do we pick another game to preserve the runs saved total? There are good arguments both ways, but I think only two observations are important for this exercise.
First, by dropping the run saved instead of searching for another game, we preserve the exact one-to-one relationship with the runs scored test. This will cause the runs scored and runs allowed test to have exactly the same results, but we now aren't dealing with identical totals of runs scored and runs saved. Secondly, if we pick another valid game from which to save a run, we preserve the runs scored and runs saved totals, but the one-to-one relationship is destroyed and the runs saved test necessarily finishes with a higher expected win total. This must be true because the runs scored test will apply some of its runs to a set of games (shutout wins) that can never increase the win total and the runs saved test will instead apply those runs saved to games that might still be won, sometimes increasing the win total.
This brings us back to the initial point. Because of the inflationary/deflationary effect of adding and removing runs from the baseball run economy, saving a given number of runs is marginally more valuable than scoring the same additional amount because saved runs must go to games you have a chance of losing, while the additional runs scored might occur in a game you already have no chance of losing.
So what impact should this have on the question of how much of "the game" is pitching and how much is hitting (and fielding and base running)?
First, I again note that the difference between a runs scored and a run saved is not large, especially when we aren't at the extremes of the two ranges.
Second, when one sets out to acquire players one does not actually acquire a given decrease in runs allowed or increase in runs scored. Rather, the players themselves generally contribute only to the individual components of run scoring and prevention. A player doesn't simply score a run (other than by hitting a home run). Rather, he hits singles, doubles, triples, and home runs, draws walks, and steals bases. A pitcher doesn't simply save runs. Rather, he throws strikes, induces groundballs, and performs other tasks that are simply components of run prevention.
This impacts our discussion because as we have noted there is a distinct lower bound on how many runs you can allow. If I have a rotation of pitchers that throw 10 hit shutouts every time out and I replace them with a rotation of pitchers that throw 81-pitch, 27-strikeout perfect games every time out, I will win exactly zero more games despite the fact that I have drastically improved my pitching. In the baseball universe, the small edge that run prevention has over run acquisition is muted by the fact that it is far easier to hit the point of diminishing returns with pitching than it is with hitting. With hitting, you never know: that 18-run outburst just might win you a game 18-16. However, the perfect game can never improve upon the results of a seven walk, four hit shutout.
So, in the end, I stand by my original line of thinking. Even though we have demonstrated that a run saved is marginally more valuable than a run scored, this difference is muted by the diminishing returns at the extremes for run prevention. Furthermore, this difference is not enough to push pitching over 50% of "the game," as Hank Steinbrenner would have us believe.
* Math note: keep in mind that the reason we do the whole "let's pick a bunch of games at random" thing is that it allows us to approximate the result we would get if we enumerated every possibility. Enumerating all the possibilities takes a prohibitively large amount of time, but doing 1,000,000,000 random samples of those possibilities doesn't take very long at all on today's computers and should be a sufficient approximation. However, when looking at the problem theoretically, we can still consider the set of all possible combinations and avoid introducing the approximation where it isn't needed.
Saturday, November 24, 2007
I'm excited to see Torii Hunter as an Angel. K Law, as always, makes a good statistical argument which is all you can do at this point, but special teams that end up on top often supersede their statistical averages. For that we'll have to wait and see.This comment elicited a raised eyebrow from me. On the one hand, I would doubt, though I only speculate, that Mr. thoyt06 has done the research to demonstrate his claim that the teams that end up on top often exceed their expected performance. On the other hand, he's right, but not for the reason he probably thinks he is.
Let's take a step back. If we have three teams with the same level of expected performance, which team will end up "on top" at the end of any series of trials? By definition, the team with the best actual performance will also be the team that exceeds its expected performance by the largest amount. This must be so, because the teams were expected to finish at the same level. In order to finish higher or lower than the other teams, that team will need to beat or fail to meet expectations.
Of course, in real life, all teams do not have the same expected level of performance. However, it is still the case that exceeding expectations will boost your chances of being "on top." For example, if an expected 95 win team under-performs by 5 wins (not at all uncommon) and an expected 87 win team over performs by 4 wins, the expected 87 win team will be "on top," despite the fact that it is objectively not as good as the expected 95 win team.
So the question isn't whether or not teams that end up "on top" tend to exceed expectations. On the contrary, they almost have to exceed expectations. The question really is: do some teams consistently outperform their expectations? In other words, can we identify discernible qualities or strategies that "special" teams employ that cause them to exceed expectations? If so, then it is possible that the Angels are a "special" organization and that Hunter is a "special" player.
But how do you demonstrate this? You can't use past results, because as we have shown here, you will almost always find that the teams that won exceeded expectations, simply because exceeding expectations increases the likelihood of being "on top." If you create an alternate model that identifies teams that are likely to exceed expectations, then all you've really done is created a better expectation. It may change your view of a team's strategy, but it won't change the basic premise: teams that are "on top" are likely to have exceeded expectations.
No, the ultimate problem here, particularly as fans, is to look back and attribute past over-performance to something other than chance because we want to believe that our guys are "special." We make the argument that the rules of expected performance are different for "special" teams because it allows us to claim that our guys are inherently better than your guys. They didn't win because fate smiled on them. They won because they had more "heart," or "grit," or "guts," or whatever vacuous term you choose to use to explain an unexpected result in a positive light.
So should we just "wait and see" if the Angels are a "special" team? No, not really. If the Angels outperform expectation one of two things will be true. Either they just got lucky, or they are smarter than the rest of us and have a better model of expected performance. Either way, it won't be because they have a special, magical quality to their team.
Wednesday, November 14, 2007
For clarity, I do not assert that the work here is groundbreaking or particularly original. Undoubtedly, someone has already performed the task of verifying the good old PToB. Nonetheless, for those of you who have not seen this before, this should give you plenty of food for thought.
First, let's examine just how accurate the model is. To do this, I calculated the expected winning percentage of each Major League Baseball team from 1900 through 2006. I then compared this with each team's actual record to see how many wins difference there was between the actual win total and the expected win total. This resulted in a total of 2160 team-seasons for analysis. Here are the results, in histogram form:
Here we see the frequency with which deviations from expected win total were distributed. Each bar represents the total of all team-seasons whose deviation from its expected win total was within 0.5 wins of the deviation represented by the bar. This effectively puts each team-season into a bin and then counts the number of team-seasons in each bin. In this case, we see that the +1 bin contains more than 200 occurrences, indicating that from 1900 through 2006 more than 200 teams finished with 0.5 to 1.5 more wins than their expected win total.
The important thing to take away from this is the shape of the distribution: the data are quite normally distributed about zero. This indicates that the PToB evenly distributes its error on either side of the actual win total for a given team-season. This is reassuring result because it means that the PToB does not appear to be inherently biased towards over- or under-estimating win totals.
In fact, with in this sample, the mean deviation from actual win total was -0.0359 with a standard deviation of 4.04 wins. This means that 68% of team-seasons will have actual win totals within roughly 4 wins of their expected win total.
Now we know the extent to which we can trust the PToB model. However, we need to go a bit farther than that to place confidence in out previous conclusions. Specifically, we need to demonstrate that the PToB is not biased towards run scoring or run prevention. For example, if the model consistently over-estimated the win total for teams with high runs scored totals and under-estimated the win total for teams with low runs allowed totals, then this would indicate that it was not properly valuing run scoring and run prevention relative to each other.
To put it another way, if teams that allow fewer runs than other teams consistently beat their expected win total, then we would have to ask ourselves why this was the case. We would be forced to conclude that run prevention was not being properly valued in the PToB; obviously we would need to place more emphasis on run-prevention to correct for the constant under-estimation of win totals for teams that allow few runs. On the other hand, if we cannot find these patterns, then this is an excellent indication that the PToB does indeed value run scoring and run prevention correctly relative to each other. This in turn would make it an excellent tool for answering our original question: is a run scored equal to a run saved?
Let's look at some more data:
Here we see a scatter plot of runs scored versus deviation from expected win total. See a pattern? I sure don't. This is pretty much a text book example of two data sets that are not correlated: all we have is a giant blob of points with no apparent relationship. Indeed, by doing a regression on the data, we find that a team's runs scored total can explain only 0.15% (r-squared of 0.0015) of team's deviation from expected winning percentage. To say that this is not in any way significant would be an understatement.
Let's do the same for runs allowed:
Again, we see a formless blob. Regression results are also similar: runs allowed explain only 0.39% (r-squared of 0.0039) of a team's deviation from its expected win total.
One last test: let's see if the ratio of runs scored to runs allowed shows any significant trend. If it did we could theorize that the PToB was biased towards teams with significant gaps between runs scored and runs allowed.
Same result: another formless blob. RS/RA accounts for only 0.56% (r-squared of 0.0056) of a team's deviation from its expected win total.
So what can we make of all this? Essentially, the Pythagorean Theorem of Baseball model does not show a discernible bias towards teams' runs scored and runs allowed totals. In fact, a team's skill at preventing or scoring runs tells us next to nothing about how it will deviate from its expected win total. This is strong evidence in support of the conclusions that we drew from analyzing the effect of varying runs scored and runs allowed on expected winning percentage. Since the average deviation from expected win total is centered around zero and shows no bias towards runs scored or runs allowed, the expected winning percentages that the PToB provides us are a good way to measure the effects of run scoring and run prevention on real life win totals.
Monday, November 12, 2007
The simplest way to examine this question is to use a modified version of Bill James' Pythagorean Theorem of Baseball to analyze how scoring and allowing runs influences a team's expected winning percentage. The "theorem," which gets its name from its resemblance to the Pythagorean Theorem proper, relates a team's winning percentage to its runs scored and runs allowed via the formula:
W% = RS^2 / ( RS^2 + RA^2 )
where W% is the team's expected winning percentage, RS is the number of runs the team scored, and RA is the number of runs a team allowed. Naturally, the relationship is not perfect (indeed, for this exercise I am using a slightly modified exponent for increased accuracy), but it does capture the essence of the relationship between run scoring and winning. For example, in 2007 the Yankees scored 968 runs and allowed 777. We would have expected them to win 98.3 games and lose 63.7. In reality, they won 94 and lost 68. They underperformed expectations by 4.3 wins. Historically, this is a fairly standard deviation from expectations.
From this formula, we can examine what happens to a team's expected winning percentage when we vary runs scored and runs allowed. Let's jump into the data.
Here you can see a spreadsheet where I've calculated the expected winning percentages for all combinations of RS and RA between 500 and 1000 in increments of 25 runs. The first thing that you should notice is the line where RS is equal to RA. As it should be, this line shows us that a team that scores as much as it allows should always expect a .500 winning percentage. If you did not expect this, it may be time for a refresher on basic math.
Now then, by picking one of the cells on the spreadsheet, we can see the effect on expected winning percentage if we save an additional 25 runs by moving up one cell. We can see the effect on expected winning percentage if we score an additional 25 runs by moving right one cell.
For example, if a team scored 900 runs and allowed 800, we would expect a winning percentage of 0.553, a roughly 90 win team over the course of a season. If that team were to save 25 more runs to become a 900 RS/775 RA team, its new expected winning percentage would be 0.567, a 92 win team. If that team were to add 25 more runs to become a 925 RS/800 RA team, its new expected winning percentage would be 0.565, also a roughly 92 win team. In this case, it appears that a run scored does equal a run saved.
Let's look at it a bit differently. Here you see a similar spreadsheet, but with different data. This spreadsheet shows the ratio of 25 additional runs saved to 25 additional runs gained from the current RS/RA. Here we see that the effects of runs scored and runs saved on expected winning percentage vary depending on our baseline of RS and RA. Interestingly, teams that outscore their opponents already benefit more from saving additional runs. Teams that are outscored by their opponent benefit more from scoring additional runs.
As a caveat, I note that while the differences at the margins appear extreme (the ratio approaches 2:1 depending on which side of 0.500 you are), the largest difference between scoring or saving an additional 25 runs is only 0.008, 1.3 wins over a 162 game season. Furthermore, as with many statistical models, the extremes are where the Pythagorean model itself breaks down.
From this data, it should be safe to conclude that, at least in terms of expected winning percentage, a run scored is on average equal to a run saved. Certainly, there is variation, but that variation is centered around a ratio of 1 RS to 1 RA. It would appear that Mr. Steinbrenner is incorrect.
There are definitely problems with the method. Primarily, we have examined expected winning percentage. If our expected winning percentage model does not itself capture the relationship between RS and RA, then our results will be poor. One of the ways we can examine this is to see if there is a relationship between over- or under-performing expectations and RS or RA. If there is, then this might indicate that our predictor is doing a poor job of capturing this relationship. Hopefully, I can follow up this post with an examination of this issue at a later date.
In order to address the problems of expected winning percentage versus actual winning percentage, my next view of the problem will try to answer the run scored versus run saved question from historical data. Stay tuned!
Saturday, November 10, 2007
Let me be perfectly clear about this: good scouting is absolutely essential to a well run baseball team. Scouting provides data that raw statistics will struggle to uncover. Scouts are very important and I have no quarrel with them.
Unfortunately, a disturbing trend has developed in the mainstream presentation of scouting data. Too often, analysts that are supposed to be providing the public with a scout's view of players have instead become nothing more than poor statistical analysts, justifying their use of small sample sizes with the vague notion that they are scouting. This type of analysis is not only completely useless, adding nothing to the discussion, but also damaging to scouting as a whole. Scouting should not become a tool for giving undue weight to a small sample of performances. It is supposed to supersede the small sample by providing data that cannot be gleaned from statistics alone.
I suppose an example or two is in order. Keven Goldstein is a writer for Baseball Prospectus. In fact, he's supposed to be their scouting guru. He was brought to BPro with the hopes of expanding their coverage beyond just statistical analysis. I like Kevin's columns and I read almost everything he writes. He writes a column every Monday that offers a small blurb on ten different prospects of note. Here is an example from his latest:
It's nice to know what Arrieta is up to, but if you're looking for any useful information here, you should be sorely disappointed. There isn't any. There is not one shred of scouting data in this blurb. The only information presented to the reader is some statistical data from a sample size so absurdly small that it is totally, utterly, meaningless. Arrieta might be a good prospect, but there is 100% no reason from this paragraph to suppose that he is. If Goldstein knows what makes Arrieta great, he hasn't included that information here, and it defeats the purpose of his presence of the BPro staff.
RHP Jake Arrieta, Phoenix Desert Dogs (Orioles)
Arrieta is becoming an offseason Ten Pack regular, as the Orioles keep pitching him an inning at a time, and he keeps putting up zeroes. At this point it’s gone from “nice start” to “downright impressive,” as Arrieta had his best outing yet on Saturday, striking out all three batters he faced. So far, the Orioles fifth-round pick who got first-round money has put together 12 scoreless innings over 10 appearances, while allowing just six hits and striking out 13. It’s a little too early to call him a steal, and his disappointing final college season is still in the back of people’s minds, but his timetable is on the verge of getting accelerated.
A small sample size is a small sample size. Unless you present compelling evidence above and beyond the data itself that it should be given significance, you cannot glean any useful information from a small sample. Let's look at another example:
This paragraph is only slightly better. We hear about why Bard was highly regarded, but then Goldstein uses another small sample size to explain that Bard is in serious trouble as a prospect. There's only one problem: he gives not one single ounce of scouting evidence to suggest that Bard is struggling. Again, it doesn't matter if you say you are a scout, a small sample size is a small sample size and it adds absolutely nothing to the discussion by definition unless it can be supported by extrastatistical evidence. That is what scouting is supposed to do. Goldstein and his scouting sources may know why Bard is struggling, but until that information is presented, Goldstein's paragraph amounts to little more than saying, "Bard is in trouble. Trust me, I know because I talk to scouts." How useful is that?
RHP Daniel Bard, Honolulu Sharks (Red Sox)
Friday’s Boston prospect rankings, like any prospect list, generated a lot of email. Most of it concerned guys who didn’t make it, like Brandon Moss or Craig Hansen, but nobody asked about Daniel Bard. Twelve months ago, that wouldn’t have been the case, because last year at this time, Bard was a highly regarded first-round pick who could touch 100 mph, although he had some issues when it came to command and secondary stuff. This year, the wheels fell off. Beginning the year at High-A and then spending the majority of the year at Low-A after a demotion, Bard finished the year with a 7.08 ERA and 78 walks in 75 innings. Using the Hawaii Winter League as an opportunity to find the magic once again, the good news is that Bard has a 0.69 ERA in 13 innings while allowing just seven hits. The bad news is that he’s walked 11. It doesn’t matter how hard you throw if you have no idea where it is going.
Scouting analysis can be done. Let's rewrite the Bard paragraph with some fictitious, though plausible, scouting analysis. The italicized part indicates my rewrite.
Now, I can't really write like a scout, but that is essentially what scouting information should look like. We aren't relying on any statistics at all. There is no small sample size.
RHP Daniel Bard, Honolulu Sharks (Red Sox)
Friday’s Boston prospect rankings, like any prospect list, generated a lot of email. Most of it concerned guys who didn’t make it, like Brandon Moss or Craig Hansen, but nobody asked about Daniel Bard. Twelve months ago, that wouldn’t have been the case, because last year at this time, Bard was a highly regarded first-round pick who could touch 100 mph, although he had some issues when it came to command and secondary stuff. This year, the wheels fell off. Beginning the year at High-A and then spending the majority of the year at Low-A after a demotion, Bard's mechanics deteriorated. He began shortening his stride, causing a drop in his velocity. To compensate for this, he began to "muscle up" when throwing ball, exerting greater effort with his upper body. His left shoulder was no longer positioned properly when the ball was released, causing him to lose any semblance of command or control. It doesn’t matter how hard you throw if you have no idea where it is going.
Scouting analysis can work, but it must be disciplined. The moment it deteriorates into a parade of small sample sizes, it loses all of its value. I sincerely hope that Mr. Goldstein recognizes this so that we can reap the full benefit of his scouting connections.
There is hope. The one absolutely essential scouting columnist on the Internet is The Hardball Times' Carlos Gomez. Gomez provides a true scout's view of players, including some excellent takes on Joba Chamberlain versus Phil Hughes and Ian Kennedy versus Clay Buchholz. Gomez's analysis breaks down each player physically, analyzing how they do what they do and how what they do leads to results. Assuming that Mr. Gomez just isn't talking out of his ass, every writer who wants to write about scouting should aspire to his level of work. If that happens, we'll finally start reaping the benefits of beer and tacos.
**EDIT** Fixed minor spelling mistake.
Thursday, November 8, 2007
“This game is 70 percent pitching, and even more in the postseason.”I'm pretty sure that this is not just false, but provably false. In fact, it's so false that Hank is probably off by a factor of two.
Here's how it breaks down. To win a baseball game, one must outscore one's opponent. It doesn't matter what the score is, so winning 12-11 is as good as winning 1-0. From this, we will assume that a run scored is as valuable as a run prevented.*
From this, it follows that run prevention as a whole is as important as run acquisition (doesn't that sound cool) as a whole. Run prevention is divided neatly into two parts: action before a batting event (pitching) and action after a batting event (fielding). Since run prevention and run acquisition are equal with respect to winning ballgames, if we assume that fielding has any importance at all, then pitching must be less than 50% of "the game."
So that's my reasoning. If we assume that preventing a run increases your chances of winning by roughly the same amount as scoring a run, then this logic is nigh infallible. I really hope Hank doesn't have as much influence as his Dad did.**
* Due to the fact that you cannot fall below zero runs scored, this will not be quite true, but it is a safe assumption that the difference is negligible for this exercise. For example, if you have a game that would otherwise be tied 4-4, you can win by either preventing a run or by scoring another run. The events have equal value. Perhaps I shall test this assumption in the near future.
** I will note in Hank's defense that if he means that pitching is more valuable than the other aspects of the game, then he could be correct, if good/great pitching were appreciably more scarce than hitting, base running, and fielding. This is unlikely to be the case, and it's hard to see that this is his meaning from his choice of words.
Tuesday, October 23, 2007
Let's do this bullet point style!
- I was surprised at how close the two outcomes were with respect to multi-run innings, about a 2-4% difference historically. One of the great things about studying baseball is that you are surprised by the results and you learn things. That's part of why I write this blog. If I wasn't leaning anything, I would just be up here pontificating. In this case, I found that I was guilty of attributing more import to the home run than it deserved. Obviously, the home run is far more valuable because it is one guaranteed run, but with respect to multi-run innings its value is marginalized relative to the walk. I did not recognize this, and thus my initial approach to the problem was incorrect.
- We can definitely conclude that Tim McCarver is totally wrong. Whether we examine the problem from the perspective of history or probability, both correct ways of examining the problem, the weight of evidence is greatly against him. Even thought the difference in probabilities is seemingly small, it's over such a large set of samples that it takes on much significance. It's nearly impossible to conceive of a scenario in which the walk is more valuable than the home run, which was McCarver's basic assertion.
- We reaffirmed a basic baseball truth: outs are your most precious commodity. The difference between the two events with respect to multi-run innings has nothing to do with their relative value to each other from a run expectancy point of view. The home run is more valuable with respect to multi-run innings not because it scores a run, but rather because it precludes the possibility of an out.
- Finally, we provided a tad more evidence for the Markov property in baseball. The conjecture about the walk being more likely to lead to big innings is largely based on the assumption that indicates more about the game state than it actually does. Baseball is largely dependent only on the current state of the game, not on how each state was reached.
Monday, October 22, 2007
3. Think about how much money it could cost the Yankees to retain Jorge Posada, Mariano Rivera and Alex Rodriguez. Over the lifetime of their contracts, you could be talking an investment of at least $250 million. That’s a lot for a 36-year-old catcher, a 38-year-old pitcher and a guy who never played in the World Series.That's what A-Rod is to you, Pete? Go to hell.
Tuesday, October 16, 2007
Here's how it works. In the game state with no one on base and no one out (hereafter abbreviated 0-000), you have a probability of scoring exactly zero runs from then on (P0), a probability of scoring exactly one run from then on (P1), and the probability of scoring more than one run from then on (P2+ = 1 - P0 - P1). Conversely, the probability of no multi-run inning is P0 + P1 = 1 - P2+.
After a lead off home run, you return to the 0-000 game state. Only now, in order for there to be a multi-run inning, you only need to score one more run. Therefore, the probability of no multi-run inning is now just P0. The probability of a multi-run inning has become P1 + P2+.
After a lead off walk, you enter the game state 0-100 (man on first, no one out). You still need to score two more runs. As before, you have a probability of scoring zero runs P0', one run P1', and two or more runs P2+'.
In order for the lead off walk to be more valuable, P0 would have to exceed P0' + P1'.
Now, P0 is roughly 0.72. P0' is roughly 0.58. P1' is roughly 0.25. Therefore, P0' + P1' is equal to roughly 0.83. Therefore, the probability of scoring one run or more from state 0-000 is 0.28. The probability of scoring two or more runs from state 0-100 is 0.17. (All of these numbers are based on Keith Woolner's "An Analytical Framework for Win Expectancy" from Baseball Prospectus 2005.)
The difference is roughly 11%. Most (all?) of this will be accounted for by the fact that the man on first can be doubled off and the man who hit the lead off home run can't.
So that's the math. But do you really need it? A home run is one guaranteed whole run that no one can take away. The lead off walk increases your odds of scoring exactly one run by roughly 14%. The lead off home run increases those odds by ONE HUNDRED FREAKING PERCENT.
**EDIT** As pointed out in comment number one, referencing the probability of scoring one run is misleading, as scoring one run and scoring zero runs both count for nothing for the purposes of counting multi-run innings. The ninth-inning analogy is apt: it's the second runner scoring that is important and neither the lead off walk nor the lead off home run will have a great affect on what that second runner does. What is important is that the lead off home run eliminates the probability of the double play and the lead off walk does not. In other words, it is the out that is important, not the run. Point well taken. **END EDIT**
Tim, do us a favor and stop bringing this up as if it's surprising. You will sound a whole lot more intelligent and
Tuesday, October 2, 2007
"I can't believe it," Helton said. "Can you believe it? We were down. We battled back. We did it against the best closer of all time."Umm, Todd? Mariano Rivera says "Hi."
Monday, October 1, 2007
The Marlins will consider all options this offseason, perhaps even the trade of Miguel Cabrera. Marlins executives should know Cabrera and his habits better than anyone, and they have to ask themselves this question: Do they think that the 24-year-old Cabrera will get a handle on his physical condition and expanding waistline?Let me begin by saying that I do not mean to quibble with Olney's chief assertion. It is entirely possible, more so than with most Major League Baseball players, that Miguel Cabrera will eat himself out of the Hall of Fame. Furthermore, it may indeed be the right idea for the Marlins to trade him, because he would certainly fetch a ginormous bounty. I don't believe either of these events are likely, but they certainly should be scenarios of which the Marlins should be aware.
If they don't believe he will, they should look to move him ASAP, while his trade value is still extraordinary. If he arrives in spring training appearing heavy and has any kind of physical breakdown in 2008, his trade value will plummet, because rival talent evaluators will attribute his problems to his conditioning.
The Marlins' working model for this situation should be Kevin Mitchell, a staggering talent who hit 47 homers and drove in 125 runs at age 27, and then was basically finished as an everyday player within two years because of his condition. Cabrera could be one of the greatest hitters of his generation, but at some point, he will need to make an adjustment.
No, my quibble is with the astonishing choice of comparison for Mr. Cabrera: Kevin Mitchell. This is a very bizarre and inaccurate selection. Kevin Mitchell is nearly the poster child for an above average baseball player's career path: breaks into the majors in his mid twenties, peaks at age 27, and then slowly declines for 5 or 6 years. I will admit that I do not know the details of Mitchell's career and that the chief reason for his decline is not a decrease in his rate of production, but in his playing time.
However, to compare him to Cabrera is astonishingly foolish. Let's look at Cabrera and Mitchell year by year using WARP3:
Age: 20 21 22 23 24 25 26 27 28
Cabrera: 2.5 6.7 9.4 11.5 10.9 ??? ??? ??? ???
Mitchell: N/A N/A -0.1 N/A 4.1 5.7 6.7 12.8 8.6
29 30 31 32 33 34 35 36
Cabrera: ??? ??? ??? ??? ??? ??? ??? ???
Mitchell: 5.3 3.8 4.8 8.0 0.3 2.2 -0.1 -0.1
Folks, Miguel Cabrera has had one of the best starts to a career ever. He broke in as a rookie for the Marlins' World Series run in 2003, serving as a huge lift and a big threat for the latter half the year. He then made himself a perennial MVP candidate by the age of 22. Simply great baseball players do not do that. Alex Rodriguez does that. Ken Griffey Jr. does that. Barry Bonds does that. Inner circle Hall of Famers do that.
Kevin Mitchell wasn't a regular until he was 24, and even then didn't play in 140 games until he was 26. Miggy has played in 150+ games since his first full season. Heading into his age 25 season, Miggy has roughly 40 WARP3. Mitchell had 4 WARP3 at that point. He had only 61.9 for his whole career.
Essentially, Kevin Mitchell is a bad comp for Miguel Cabrera. In fact, just about every ballplayer ever is a bad comp for Miggy (those named Mantle, Mays, and Rodriguez excepted). Miguel Cabrera is on track to be one of the greatest baseball players who ever lived. Kevin Mitchell was never even close to that. Ever. Busting out at age 27 is just far too common to serve as the basis for comparison to a man who put up MVP numbers at ages 22, 23 and 24.
Miggy may eat his way out of greatness, but the Marlins should absolutely not proceed like Miguel Cabrera is Kevin Mitchell. Indeed, they would be much wiser to treat him as if he were Frank Robinson, Ernie Banks, Eddie Mathews, or Lou Gehrig. Each of these players is more comparable to Cabrera than Mitchell.
Saturday, September 29, 2007
Perhaps you think that what they say is probably somewhat or even mostly true. Perhaps you think that I ought to defer to their experience as players and their lifetime in baseball instead of insisting that I am right and they are wrong. Perhaps you think I am arrogant for not really caring what these people think. Perhaps I do think I know more than I really know.
However, I have never been more convinced of their complete and total uselessness as analysts of baseball on the macro level than I am right now.
Ladies and Gentlemen, Boys and Girls, I give you, from the World Wide Web's leading critics of baseball analysis, Exhibit 1A as to why you never, ever need to pay attention to what the men in the booth think about baseball strategy, roster construction, and valuable baseball skills ever again.
From the mouth of Mr. Tim McCarver:
We had our friends at Stats, Inc. check and see whether more multi-run innings came with a lead off homer or a lead off walk. You would think that a lead off walk would lead to more big innings than a lead off home run. Not true. A lead off home run, this year, has lead to more multi-run innings than lead off walks. It's against conventional thinking.This is stupidity of the higher order, and you can't even say that it was spontaneous or ill-thought out. Tim McCarver actually did research to see if this was true and then was surprised at the results, so much so that he brought it up on the air because he thought his viewers would also be surprised.
This is why I do not respect what these men say about strategy. This is why I don't care on iota what they have to say about the stolen base and the sacrifice bunt. This is why I don't give a flying f*** about their theories on pitching and defense. If this result surprises you, you don't know the first thing about baseball strategy and the value of baseball events.
Mainstream baseball analysts, especially ex-players, are nothing more than men who have spent their entire lives learning baseball clichés that have no basis at all in any sort of objective truth. Until they can demonstrate that their knowledge is actually valuable, we need not pay attention.
Tuesday, September 25, 2007
All that being said, this is exactly the type of quote that will get a reaction out of me, courtesy of Mr. Peter Abraham's usually excellent blog:
What a travesty. Edwar Ramirez and Brian Bruney – the darlings of the stat geeks – walk four and give up two hits to lose the lead in one inning. Well, they were each released before. They won’t be surprised when it happens again after the season. The Yankees would be crazy to put either of them on the postseason roster.I pick on Pete a lot, because as good as his site is for information, he has the absolutely infuriating habit of dropping throwaway lines like this into his posts. This is, once again, a classic anti-statistics straw man.
Brian Bruney is not a stat geek darling. He walks way, way too many people and then gets hit hard. His best attribute, his velocity, is muted by the fact that he doesn't get any results. Absolutely no right-minded objective analyst will tell you that Brian Bruney is an underrated, misvalued diamond in the rough. He isn't.
Edwar Ramirez is exactly like Bruney, in an exactly opposite kind of way. He strikes a lot of guys out, but he walks too many guys and he then proceeds to get hit hard. Unlike Bruney, Edwar has no fastball to speak of, but possesses a devastating change-up. Abraham is probably hammering the stat geeks over Edwar because we were calling for his promotion on the basis of his minor league numbers. Edwar had proven that he could dominate the minors. At that point, you see if he can contribute in the majors. So far, he has not. I still like Edwar, but he has obvious flaws in his game. Naturally, Abraham's solution is to cut bait. What happened to player development?
Stat geeks wanted to see Edwar (and Chris Britton) precisely because the Yank's current pen (including Bruney) was so ineffective. Edwar isn't being asked to be Mariano Rivera or even Luis Vizcaino. He's being asked to be the 5th or 6th option in the pen. If he turns out to be great, then you win. If he turns out to be a turkey, there are a million and one guys out there who can be a bullpen's 5th option.
Here's the thing: both of these guys cost absolutely nothing for the Yankees to acquire. Edwar was a guy picked up to fill out a minor league roster. Bruney was released by Arizona and the Yanks picked him up because he throws really hard. Anything they provide is gravy. Both have pitched well at times. Both have sucked a lot at times. But no statistical analyst would be under the illusion that they've been effective. They haven't.
Friday, September 7, 2007
Currently, Rick Ankiel is being accused of taking Human Growth Hormone a few years ago. Critically, HGH was not a banned substance at the time, not that this will stop the crisis-driven media from working itself into a mind-numbingly shrill torrent of condescending, sensational, half-assed, self-righteous pontificating.
But let's ignore that and instead just look at one even more critical piece of information: HGH apparently does not help athletes perform better.
Yes, folks, that's right. We have no evidence that HGH makes you a better athlete. Why does the media not care about this? Why won't this single fact stop them from going crazy to protect children, baseball, truth, justice, the American way, and baby seals from a substance that is apparently innocuous?
Because the truth about HGH doesn't sell papers or boost ratings! So much for journalistic integrity. I am already dreading watching the post season on Fox, where if Joe Buck can go more than fifteen minutes into the broadcast of every game without mentioning a baseball scandal, it will be a fucking miracle. (Pardon my French, Mom.)
Now can we please, please, please, please, for the love of God, please return to covering just plain, old baseball?
Wednesday, August 22, 2007
Unfortunately, we're talking about a different kind of confidence than they are.
When one deals in the realm of probability, which is to say, when one analyzes anything with unknowable information, one can never predict anything with 100% accuracy.
For example, let's say I have 1,000,000 consecutively numbered balls in a very large hopper. I draw a ball from the hopper and predict that the value on the ball I have drawn will not be exactly one. This is not a very dangerous prediction. In fact, I will be right 99.9999% of the time. However, I will also be wrong 0.0001% of the time. No matter how many balls I stick in the hopper, I will always have some chance of selecting that one ball that breaks my prediction.
The same is true in baseball. As the old adage goes, even a .300 hitter fails 70% of the time. Ignoring the banality of the adage, what it implies is important: we can never be 100% certain of a particular outcome in baseball.
Baseball involves two elements: skill and chance. Some prefer the term "luck" to "chance." I do not, because luck implies some moral element: "good" luck or "bad" luck. Rather, "chance" simply implies that there are things that are beyond a player's control.
Thus, whenever we are examining a player's performance record, we have to take care to account for the fact that some of that player's performance could be due to chance. So how much is due to chance and how much is due to skill? Again, we can never say for certain. However, we can leverage probability to tell us how much uncertainty there is in our estimate.
Let me illustrate what this looks like without any rigorous math, of which I assure you, Dear Reader, there is plenty. Suppose I have an apple sitting on my head and a bow and arrow with someone must attempt to shoot the apple. Having studied this subject repeatedly, I know that an average person can hit the apple without killing me (success!) only 25% of the time. I am in quite a fix.
However, the evil sadist that has put me in the gruesome predicament has given me a way out: I can pick who will be the shooter from a list of anonymous citizens, who have all provided me with their career attempts and successes in the common practice of shooting an apple off of one's head. How should I make my choice? Should I simply choose the person with the best ratio of success to failure?
Of course not! I'll end up choosing someone who shot one apple off of one head. This person will have taken one attempt in their entire life and just happened to succeed. Now, not knowing anything else about this person, should I conclude that they are a 100% apple-shooter? Only if I'm suicidal!
The odds are that this anonymous shooter is actually an average Joe: he probably hits the apple one out of every four tries and happened to get lucky this one time. To be sure, he could be the greatest apple shooter who ever lived. However, I cannot have any confidence in this conclusion based on only one trial.
Let's say I have another anonymous archer who has made 5,000 apple-shooting attempts and succeeded at 4,500 of them. The odds of this guy being a normal 25% shooter are close to zero. Amazingly, it is not guaranteed that this guy is not an average shooter. After all, in a universe of infinite possibilities, some average shooter will hit 4,500 of 5,000 shots. However, I can say with much, much more confidence that this man has a real skill at shooting apples of off heads.
Naturally, given a choice between the two, I'll pick the guy who's almost guaranteed to give me a 90% chance over the guy who has a ominously low chance of being 100% accurate.
So, how do we quantify this?
Well, that's where confidence comes into play. Confidence is the likelihood that our measured value is within a given range. For example, after that one trial, I can say with 99% confidence that our shooter falls withing the accuracy range of 100% ± 90%. Or I can say with 90% confidence that our shooter falls into the range of 100% ± 75%. Or I can say that 50% confidence that our shooter falls into the range of 100% ± 40%.
These numbers are made up, but they reflect the way confidence works: for any given sample we can increase our confidence in the range of values by increasing the size of the range. We can decrease the size of the range by decreasing our confidence level.
In the case of our apple shooters, because we only have one trial on which to base our conclusions about the man with 100% success, we will not be able to get a range of values useful enough to make a decision without destroying our confidence level. This ought to make intuitive sense to you. The more you increase the range, the more likely you are to be right, but the less useful the range is. The more you decrease the range, the more likely you are to be wrong, but the more useful the range is. With so little data, this guy is hardly more valuable than a shooter who's never taken a shot in his life. Without knowing anything else, it's very hard to conclude anything but that he's an average guy who got lucky once.
What of our man with 5,000 attempts? In his case, I might be able to say with 99% confidence that his skill is 90% ± 5%. Or I can say with 90% confidence that his skill falls into the range of 90% ± 2%. Or I can say that 50% confidence that his skill falls into the range of 90% ± 0.1%.
Why do we have more confidence with this guy? Because we have so many more attempts on which to base our conclusions. Again, it makes intuitive sense: the more data we have, the more confident we are.
Here is the important point: the only way to both increase confidence and decrease the range is to add more data points. Period.
Normally, when presenting statistics researchers will choose a confidence level and let the range fall where it is. A 50% confidence level just isn't that useful. Ninety-nine or ninety-five percent are probably the most common.
So why have I spent so many words belaboring this point? Because we're about to explore some bona fide objective analysis and confidence is a foundational concept. Confidence is why it means so little when a guy is 5 for 7 lifetime off of a given pitcher. Confidence is why analysts are so skeptical about a clutch hitting skill. Confidence is why it's so hard to judge how good a reliever is statistically.
So if you don't get confidence, you may want to reread the post (or find a better teacher), because if you don't, you may be the next guy to do this. Or at least, you won't get my upcoming posts.
Wednesday, August 15, 2007
You should not need anymore evidence than this to reject the player ratings wholesale. The idea that a left fielder who isn't slugging .500 or getting on base at a rate of 40% (or even close) is more valuable than a guy with 164 innings of 3.79 ERA in the American League East is just crazy.
Monday, August 13, 2007
One of the things that always strikes me about statistical analysis is that it usually involves talking about baseball in the realm of the infinite. While this practice is theoretically correct, the thing that makes baseball interesting is that it is played in a finite series of events. A team does not have an infinite amount of time to allow its true talent to come through. It has only 162 games.
The result of this is that as soon as we start playing games, teams start accumulating "error" in terms of their actual performance versus their true talent or expected performance. In turn, the result of this is that it is actually quite easy for teams to vary wildly in their deviations from their expected performance.
(Keep in mind that when I talk about expected performance the assumption is that the expectation is accurate. I know
For example, let's say I have a coin that I will be flipping 10,000 times. We expect that this coin, if it is a fair coin, will come up heads 5000 times and tails 5000 times. Why? Because a fair coin is expected to come up heads half of the time and tails half of the time and I have 10,000 remaining flips.
So I make the first flip and it's heads. Two things happen immediately. First, and least consequential, is that I know have the world's smallest sliver of a fraction of a shadow of a glimmer of a doubt that the coin is biased towards heads. Naturally, this evidence would have a confidence level bordering on zero.
Secondly, and more importantly, my expectations have changed. Previously, I was expecting 5000 heads and 5000 tails. Now, I'm expecting 5000.5 heads and 4999.5 tails. Why? Because a fair coin is expected to come up heads half of the time and tails half of the time and I have 9,999 remaining flips.
Remember, the coin had to come up either tails or heads, and it is by no means surprising that it came up heads. Nevertheless, our expectation now must be different. Probability is only useful in discussing unknown outcomes. It has no role in discussing known outcomes. Information is highly influential, and therefore valuable, in probability.
This happens a lot in baseball too. The Yankees have grossly underperformed this year. We would expect them, base on runs scored and runs allowed, to be ahead of the Red Sox, not behind them. However, they don't get those "flips" back. That error from their true talent level has accumulated and now we have to adjust our prediction of their overall record downward, even though the team might not be at all worse than our original expectation. Crazy, huh? I think so.
Look at it in terms of a three game series against Baltimore. We would expect the Yankees to win about 1.8 of the games in that series (number derived from the patented "pulling a number out of my ass" technique). There's only one problem: you can't win 1.8 games. So after that series, the Yanks will be guaranteed to have overperformed or underperformed. If they underperformed, they can't expect to recoup that loss. If they have overperformed, that's money in the bank.
As with the coin flip, it's also true that the results of the team's games will influence our determination of their true talent. However, the sample needed before this starts having a noticeable effect is really, really large.
Anyways, the corollary to all of this is my (only?) favorite John Sterling cliché: you're never as good as you look when you're winning and you're never as bad as you look when you're losing.
So true. In fact, we've just proven it.
(The more theoretically minded will note that, other than perhaps having to adjust our "true talent," these results are still meaningless when we are making an infinite number of flips or playing an infinite number of games. No matter how many heads in a row I get, if the coin is known to be fair, the expected ratio of heads to tails after an infinite number of flips is always exactly 50/50.)
**EDIT** Fixed a really dumb typo.
Friday, August 10, 2007
Essentially, I want to cover two topics. First, what can we say about the offensive era we live in and how much if it is driven by steroids? Second, what do I think about steroids and steroid users on a personal level.
As many of you are no doubt aware, from about 1995 through the current year, baseball has been on somewhat of an offensive kick. What you may not know is that the current offensive levels aren't entirely unprecedented. Baseball is always going through transitions between eras of more or less scoring. I expect this trend will lessen some as baseball tries to regulate its product more heavily. However, historically, the current level of offense is not highly unusual.
So what is the cause of this offensive boom? Good question. Let's examine the possible reasons and their likelihood of significance.
You know all about this one, so let's get it out of the way. Essentially, the argument goes that athletes are bigger and stronger than they once were because of steroid use and therefore they are hitting better than ever.
I have no doubt that some baseball players have done steroids. I have no doubt that steroids make you stronger and that this will help you hit ball hard. I have great doubts that this effect is significant, relative to other factors. The truth about steroids, the one thing that must always be kept in mind, is that:
We just do not know what the effect of steroid use is on one's ability to hit a baseball.
Strength and baseball power are not perfectly related. The key with hitting for power is the efficient transfer of energy from your muscles to the ball via the bat. This requires the ability to make contact, proper mechanics, and, yes, some physical strength. Of these, physical strength is probably the least important when it comes to hitting a baseball hard.
2. Weight Lifting
While we're on the subject of strength, it's worth pointing out that not only is it hard to separate the effects of strength from other aspects of hitting, it's also almost impossible to separate the effects of weight-lifting without steroids from the effects of weight-lifting with steroids, with respect to baseball players.
Baseball players never used to lift weights. It was thought that weight lifting would screw up your swing and destroy your agility. Even as recently as the 1980's these things were viewed as more important than raw strength. It is not surprising that steroid use would become an issue at the same time as weight lifting; after all, the two are related. However, how do we know if Barry Bonds' strength gains are 10% due to weight lifting and 90% due to steroids or vice versa? We just don't know.
3. Smaller Ballparks
This has been rehashed elsewhere, but suffice to say that most of the modern ballparks that have been built are offensive havens. The stadiums built in the 1970's were often monstrosities that favored the pitcher. This trend has been reversing as teams have come to favor smaller, more intimate (read: pricey) ball parks.
4. Better Bats
The science of bats has come a long, long way. In the 1990's players switched to using a maple bat instead of traditional ash bat. These bats are made from better wood allowing them to be made much lighter. Lighter means faster. Faster means more bat speed. More bat speed means more power.
5. Juiced Balls
Yeah. When I first heard about this in 1998, I thought it was a conspiracy theory too. And yet, it may not have been wrong. There is good evidence that the balls in use today are much more lively than the balls used in previous generations. Some researchers claim that this may allow a ball to be hit as much as 30 feet farther. That's a lot. This also jives with the wonderment that many players and coaches often express when they see a little second baseman hit "what should have been an easy fly ball" for a home run. It's not just the big, burly men who are hitting more home runs.
6. Diluted Pitching
Expansion wouldn't cause league offense as a whole to go up for very long. For each crappy pitcher you add to the league, you also have to add a crappy hitter. However, it does mean that the good hitters that are already there get to face crappy pitchers in a higher percentage of their plate appearances. It works in reverse too: great pitchers get to face crappy hitters more often.
What's the result of this? The great ones play greater. You would see the frequency of both great individual hitting and great pitching performances go up. Anecdotally, this is the case. We've had more 20 strikeout games in the last 10 years than in all of MLB history. On a more quantitative note, almost all of the great single season strikeout performances (as a rate statistic) by pitchers are within the last 15 to 10 years. It should stand to reason that hitting would also see some bounce from this effect.
7. Different Offensive Philosophy
Joe Morgan may not like it, but guys do play for the three run homer. And they should, as it will lead to more wins. The natural strategic evolution of baseball is seeing the death of widespread use of inefficient tactics like the sacrifice bunt. It's a slow process, but as people become more educated as to the value of outs, they will be less likely to play for one run and more likely to play for three. And that's a good thing.
8. Modern Medicine
You know how many players in the 1960's had successful reconstructive elbow surgery? Zero. Nutrition and medicine are leaps and bounds better now than when even just 20 years ago. Why should it surprise is that this helps players perform better?
9. Fewer Pitchers Pitching Inside
This allegation is, of course, purely speculative, but many believe that the presence of protective gear has allowed hitters to crowd the plate more than ever, taking away half of the plate and forcing pitchers to work predominantly outside. Naturally, when you only have to worry about half as many pitch locations, it's easier to hit.
Now the point of listing all these factors isn't to convince you that steroids are meaningless. In fact, it's not even to convince you that each of the listed factors are meaningful.
No, the point is that we just do not know how much these individual factors have contributed to the offensive boom. The media has turned this into a black and white issue: steroids, used by cheaters, have caused the offensive explosion. The truth isn't nearly that simple. There are a plethora of factors that may or may not have contributed to the offensive explosion in baseball. Trying to separate one from the other is likely a fool's errand.
(Interestingly, in the case of Barry Lamar Bonds, you can also add the existence of a marvelous hitting aid as a potential factor in his power surge. I'm not sure how much I take this claim seriously, but it is fascinating to think about.)
So. What does all this mean? What do I think about steroids in baseball and Barry Bonds in particular.
First, because it's so hard to separate which factors were instrumental in the increased offense in baseball, we shouldn't be giving players asterisks or discounting their records in the record book. We should be letting history write its own narrative about the players involved. Each era in baseball has to be properly adjusted for before you can properly appreciate the achievements that took place during that era. Hitters in 1968 struggle to hit even .300. A bunch of guys will clear that number this year. Context, as always, is everything, and it is this context, completely neutral and completely scientific, that will cause us to look back on this era and properly discount the value of the offensive numbers that were put up.
It's ironic then that the media hates the very people that advocate these adjustments. We're the geeks, those guys with a slide rule. We're ruining baseball with our numbers. You'd think that the politics of steroids would have made for the strange bedfellows of geeks and writers. What does that say about how much the media hates geeks relative to steroids?
Yes, I do think steroids are cheating. I do think that they violate the spirit of the game. I do not want them to have anything to do with baseball. We now have a system in place for this. Guys who are caught cheating should serve their suspensions and then be allowed to return to baseball. They should not be banned from the Hall of Fame and they should not have their records invalidated.
That being said, the fact that they cheated should weigh into the Hall of Fame process. It speaks to their lack of character and does call their performance into question to some degree. However, this criteria should only be used in borderline cases. I don't think steroids can make a guy who belongs outside the Hall into a no doubt Hall of Famer.
As for Barry Bonds, I think that there's an excellent chance that the man used steroids. Unfortunately, he did so at a time when there were no consequences and now that there are consequences, he has not failed a test. There's absolutely no way you can invalidate what he's done officially without some kind of failed test.
Is Barry the home run king? Well, yeah, if you mean that he's hit more home runs than anyone in Major League Baseball history. Of course, that would be true even if he had failed a test. The games still count. If you mean that Barry is the greatest slugger of all time, you'd be wrong and will continue to be wrong unless Barry can belt another 150 home runs. That's about what he'd need to surpass the Babe after appropriate context adjustments.
Barry Bonds is a first ballot, no doubt, surefire, inner-circle Hall of Famer. He should get 100% of the Hall of Fame vote. He won't because some will let the steroid issue convince them that somehow he isn't worthy, despite his pre-2001 numbers. It won't matter, because no one gets 100% of the vote anyway, not even Cal Ripken.
Most importantly, I think that steroid use in baseball is not rampant. I think that most guys do not use steroids. I think that the steroid issue is a media driven frenzy designed to give themselves something about which to moralize without fear of reproach. I just want the issue to die, to go away and never return. I want baseball to be about baseball again. I want to be able to listen to a baseball game on TV without the announcers bringing up steroids.
That will be a good day.
Thursday, August 9, 2007
Do you see what Mr. Abraham has done? A-Rod works hard, therefore he is a good guy and less likely to use steroids. A-Rod's suspicion level is mitigated by Peter Abraham's perception of how hard A-Rod works at his craft.
I cannot tell you categorically that Rodriguez has never used PEDs. But I can tell you this: I’ve never witnessed a baseball player who works harder at being good. I used to get to Legends Field around 7:45 a.m. most mornings in spring training and A-Rod was always on a back field taking grounders. Not sometimes. Always.
During the season, we’re allowed in the clubhouse 3.5 hours before the game and he is always there, either having finished working out or on his way. He also lifts weights after games. The Yankee coaches marvel at this work ethic and hold him up as an example to their younger players.
Alex was heavier last season, especially in his upper body, and it cost him on the field. He has dropped at least 15 pounds this season and has more range and quickness at third base and much quicker bat speed.
Along with the working out, he radically changed his diet. It’s to the point where he brings his own food to the stadium and calls ahead to restaurants to find out what’s on their menus.
There’s no reason to feel badly for a guy with that kind of talent and a contract that will change the lives of his great, great grandkids. But in this case, Rodriguez is being treated unfairly.
Now, if I had to venture a guess, I'd wager that Barry Bonds works harder than one can possibly imagine to be a great hitter. In fact, as I hope to touch on at a later date, if Bonds is using steroids, he may be working harder than he normally would because steroids enable him to push his body harder when training.
PED use and hard work are not mutually exclusive. PED use is that strange kind of cheating where you actually have to work harder when cheating than you do when not cheating. It can be driven by fear of failure or by desire to succeed, but either way you have to be driven to care enough to use PEDs.
Yet, we often throw up guys as examples of non-users just because they are hard working, affable guys. Because we perceive these guys playing the right way and being gritty and hustling and working hard, we elevate them beyond reproach. Bonds is a surly son of a bitch, so he doesn't get the benefit of the doubt.
But Pete Rose? He was a baseball hero, until it turned out he actually wasn't.
Wednesday, August 8, 2007
Tuesday, August 7, 2007
I will acknowledge Barry Bonds for what he has done: hit more home runs than anyone in history. It is a fascinating accomplishment, one that's worthy, on some level, of celebration. We have never taken records away in baseball history, and we should not take this one away unless we're prepared to take away a whole bunch of records and achievements during this era. We shouldn't put an asterisk next to it, either. There already is -- and always will be -- an imaginary asterisk next to this era. We should do what baseball has always done with its records and controversies: attach a story to them, and then let our best baseball fans -- they believe something fishy went on here -- decide how to recognize this achievement. As for Hank Aaron, he no longer will have the most home runs of anyone in history, but his legacy will not be lessened. Bonds' chase has given us another chance to celebrate the greatness of Aaron's career, and the strength of his purpose. His legacy might even be strengthened because, as far as we know, he hit 755 home runs naturally, legally and honestly.I can respect this opinion. People don't think less of Ruth for what he did. People haven't forgotten Roger Maris. And we're all learning how to put the context of the players' accomplishments in their proper context. We don't need witch hunt to extricate players' records and we don't need an asterisk.
The record book may now indicate Barry Bonds is the new home run king. But that doesn't mean fans -- both outside and inside the game -- have to recognize Bonds' spot above Hank Aaron. The beauty baseball has always maintained over other sports is accountability in the fans' perspective. You can trust your eyes in baseball. An error is an error. A missed bunt attempt is just that. What you see is, well, what you see. A pitcher who is throwing 88 mph at the end of one season and is magically hitting 98 on the gun the next spring? That's just not humanly possible, at least not without some form of help. Same goes for home run hitters, and Bonds tops this list. Not just because the only time he ever hit more than 49 home runs was when he reached 73 in 2001, but also because of the numerous allegations that Bonds used chemical help to reach late-career highs. Whether baseball or its fans want to admit it, these last 15 years will forever be viewed as the steroids era. Some say Bonds is being unfairly picked on. Maybe, but remember, the lab he used, BALCO, was the one the federal government raided. Bonds' name was front and center in the BALCO investigation and it's front and center among a large faction that simply does not believe he is the new home run king.What was Roger Maris on, Pedro? This makes me more angry than I have a right to be. Pedro Gomez has decided what is and is not humanly possible for a Hall of Fame athlete. Pedro Gomez knows what your body is capable of doing. After all, he has spent years researching bio-mechanics and physiology at world class institutions.
- ESPN's Pedro Gomez, as quoted here.
Wait. What's that? He hasn't. HE'S JUST A MOTHERHUMPING JOURNALIST!!?!?!??!?! YOU DON'T F(&!()*@#ING SAY!???!?
Also, whether or not he cheated, Barry is the new home run king, if by "home run king," we mean "the guy who has hit more home runs than anyone else." If by "home run king," we mean "the best home run hitter who ever lived" that title still belongs to Babe Ruth, after we apply the requisite adjustments for era.
You all probably already know what I think about it. It basically just throws Barry, McGwire, and Sosa under the same bus as Raffy Palmeiro, who actually deserves it. What drives me nuts isn't so much the bringing up of Bonds' link to steroids. Again, this link definitely exists, it's just far from definitive. It's the presumption that some players are obviously users and some players are not.
Who knows which is which (and who is who)? People just lump people in the categories they want to based on their own opinions formed on nothing more rational than the answers to the questions "Do I like this guy?" and "Do I think this guy looks like he used steroids?"
There is now a system in place for labeling people steroids users. Can we please let it work?
There are only a handful of players who have been proven to have broken baseball's rules regarding performance enhancing drugs. Barry Lamar Bonds is not one of them.
Congratulations, Barry. Someday people might even remember you as the guy who almost joined A-Rod in the 800 club.
Sunday, August 5, 2007
Barry Bonds will almost certainly claim the position of the game's greatest power/speed combination, and probably will hold that spot for many years. He will probably break the career record for walks drawn, Babe Ruth's record now, Rickey Henderson's perhaps before it becomes Bonds'. He may well break the career record for runs scored, Ty Cobb's record now, with Henderson also in line to intercept that one. Unlike Henderson, he drives in almost as many as he scores. He will break or has already broken the career record for intentional walks. When people begin to take in all of his accomplishments, Bonds may well be rated among the five greatest players in the history of baseball.Welcome to Steroids Week here at Basebology! As perhaps all of you know, steroids is my least favorite baseball topic in the world, mostly because it's not a baseball topic. Any remaining distaste for this subject is introduced by the grandstanding of media members, who at least have a job selling papers, and politicians, who apparently prefer to wag their finger at rich people more than they prefer to solve actual problems.
- Bill James, as published in The New Bill James Historical Baseball Abstract, analyzing Bonds' career through the 1999 season.
Nonetheless, I feel compelled, given the events of the weekend to discuss this topic at length before I finally shelve it for all time. It is my sincere desire that after this week I will have nothing more to say about the issue and therefore can simply talk about the greatest sport ever created by man.
An Apology To My Reader(s)
Therefore, the time has come to unveil the mystery names that you all have been waiting for with bated breath. Allow me to re-run the chart of last week with player names included and one (not so) slight modification, in bold.
Home Runs by Age:
Age: 20 21 22 23 24 25 26 27 28 29 30
Hank Aaron: 13 27 26 44 30 39 40 34 45 44 24
Barry Bonds: xx 16 25 24 19 33 25 34 46 37 33
Age: 31 32 33 34 35 36 37 38 39 40 41 42
Hank Aaron: 32 44 39 29 44 38 47 34 40 20 12 10
Barry Bonds: 42 40 37 34 49 73 46 45 45 5 26 20
As many of you supposed, Player A was indeed Hank Aaron, whose home runs as presented here do total his career mark of 755. However, many were stumped as to who Player B was. Your confusion was not without cause: I cheated you. In fact, there is no player in MLB history who has put up Player B's numbers. In this corrected version of the chart I have restored the 30 home runs that I lopped off of Barry Bonds' record setting campaign at age 36.
Why do this? Because it is a striking how similar Bonds' career is to Aaron's once the spectacular aberration of 2001 is removed. It was this realization that prompted me to host Steroids Week. Today, rather than talk about steroids in general, which will happen later this week, I want to focus on Barry Bonds in particular. I want to examine what the evidence against Barry is, what his accomplishments are, what his accomplishments should be regarded as, and why he is so controversial.
Let's get started.
Much has been made of Barry Bonds' late career power surge. In fact, this surge, along with elevated levels of offense in general, is the impetus for the media circus that surrounds Bonds' quest to break Hank Aaron's record.
Reread, if you would, Dear Reader, the opening quote from Mr. Bill James. Bill wrote those words before Barry Bonds played his age 35 season, a full year before Bonds shattered the single season home run mark.
Barry Bonds, in 1999, was an inner-circle Hall of Famer, a rare baseball talent and a perennial MVP. Yet, when he exploded for 73 home runs in 2001, people were shocked. As if a Hall of Famer having an historically great season was unusual. In fact, it is quite the contrary: we expect these types of seasons to come from Hall of Famers, not that they always do.
In a certain sense, then, it was Bonds' misfortune that he should suddenly have a season for the ages right when people's sensitivity to steroid use was beginning to peak. If, as in my original quiz, Barry Bonds had hit only 43 home runs that year, no one would have noticed. Bonds' career path would look suspiciously like that of Mr. Aaron.
Furthermore, it's not as if this type of fluke season is entirely unprecedented. In 1996, Brady Anderson had one of the most famous fluke seasons of all time, hitting 50 home runs. He never hit more than 24 in any other season. Outside of his 61 in '61, Roger Maris had a single season high of 39 home runs. He had only one other season over 30. If Maris and Anderson can do it, why then are we so shocked when an all time great player does it?
And then there's the proverbial other shoe: why did Barry's home run totals immediately return to his established career norms. If Barry had really found the fountain of steroidal youth, why did it only manifest itself in one spectacular season? I will grant that he did sustain some, though not nearly all, of his power: his at bats per home run did drop in later seasons. But is this cause or effect? Bonds has always had one of the most selective batting eyes in baseball. It is entirely possible that Bonds' decreased at bats per home run post 2001 is rather the result of higher percentage of his at bats ending on mistakes by the pitcher: they were trying to be careful and perhaps walk him, but they screwed up, and Bonds capitalized. Pitchers dramatically altered their approach to Bonds after 2001, and separating this new approach from Barry's new home run rate is nigh impossible.
Additionally, the idea that Bonds was not always a power hitter is thrown around haphazardly, usually in conjunction with an observation that 40 year old Barry is bigger than 25 year old Barry. This idea is silly. When Bonds arrived in the majors, power numbers in MLB were not where they are today. When one adjusts for context, Bonds' numbers are more impressive than they initially appear early in his career and less impressive later on. The inverse is true for Aaron's numbers: he arrived in a high offense era and ended his career in a pitcher friendly environment. When these adjustments are applied, their career paths are even more similar.
In fact, when you properly adjust for context, Aaron's career home run totals are still more impressive than Bonds', though not as impressive as Ruth's. The irony of the media cacophony for an asterisk is that they don't need one: the era adjustment that should always be applied when comparing players of different eras already adjusts for the increased offense of the late 1990's and early 2000's.
Finally, it should be noted that Barry also plays in an era with vastly improved medical technology. This technology, even and especially the legal kind, has allowed Bonds to play healthily far longer than he otherwise would have been able to. Other players too have seen this benefit. It's a shame that people attribute his late career productivity entirely to steroids and not to in any part to modern medicine.
Twenty-one years ago, Barry Bonds looked like the graphite shaft of a golf club.Apparently, if you get bigger as you get older, you are on steroids. This comes as a great surprise to every 40 year old, beer league softball player in the world. Honestly, the idea that Barry is juicing because he's bigger than he was when he was 20 is absurd. Lots of things can change naturally in twenty years.
- Vin Scully, during a Giants-Dodgers broadcast this week. (Jon Weisman, SportsIllustrated.com), as quoted at Baseball Prospectus.
Of course, none of this should discount the possibility that Barry wanted to change and worked to enact change in his body. I have no doubt that Barry made a concerted effort to add muscle mass as he aged. However, no one ever seems to acknowledge that this can be done without having to use steroids. Baseball players until the 1990's were not heavily into weight training. It was thought that being too muscle bound would rob you of necessary agility and screw up your swing. There has been a massive increase in general strength training in baseball in the last two decades. Why couldn't Barry's increase in muscle mass be attributable to this? There are plenty of examples of athletes who are incredibly chiseled despite undergoing an Olympic level drug testing program. But if you're Barry Bonds, you're on steroids.
Two of the key events in the steroid saga in MLB has been the publishing of Jose Canseco's Juiced and Mark Fainaru-Wada and Lance Williams's Game of Shadows.
Barry has long been a favorite target of the media, and, to be fair, it's mostly his fault. He has often acted like a spoiled, petulant child. He plays the race card at will. He's not the most accessible guy. Barry Bonds, Jerk became an unshakable characterization long before the steroids accusations.
And yet, that's not even the biggest problem with Bonds as a media target. Quite simply, there's a wee bit of a conflict of interest at play for both Mr. Canseco and Messrs. Fainaru-Wada and Williams.
Not much needs to be said about Canseco. I mean, why wouldn't you take the word of an admitted cheat with an axe to grind, a love of the spotlight, and a need for income at face value?
As for Williams and Fainaru-Wada (I'm getting tired of typing that), they've been using the shield of journalism to lend their work credibility. For the record, I have not yet read Game of Shadows, though I plan on doing so in the near future. Therefore, my critiques have more to do with the tactics and motives of the two than their accusations.
First, being journalists, there is very little mainstream public forum to hold them accountable, as they themselves are the mainstream public forum. Journalists love to push the idea that they are saints: selfless heroes who hold The Man's feet to the proverbial fire, defenders of truth, justice and The American Way.
Of course, what they really are is employees of publishers who need to move product. Just like everyone else, journalists are subject to the pressures of the market, of supply and demand. Writing a book and publishing articles about how Barry Bonds didn't break the law, and worse, the spirit of baseball, is worth nothing. Taking down the most dominant athlete in the last half-century of baseball makes you a household name.
And, of course, since every other journalist is in the same scenario, the vast majority of them will not acknowledge this reality. After all, you need credibility to sell papers, and you can help maintain that credibility by refusing to acknowledge that selling papers has anything to do with your journalism. It's hypocritical, a charade of the most perverse variety, and it's why you will forgive me for not immediately crucifying Barry Bonds because two self-interested reporters illegally obtained sealed testimony and interviewed a jilted ex-mistress.
How I View Barry
I know this post has come across as one giant apology for Barry, and that's unfortunate. Ultimately, I don't know what Barry did or didn't do. I'm just angry that a complex issue has been reduced to a variety of sound bites that don't stand up to basic scrutiny. We've allowed the media to control the entire discussion on Barry Bonds and they've done what they do best: they've manufactured a crisis.
Ultimately, there are a few facts on which Barry can hang his supposedly over-sized hat: first, he was already an elite Hall of Famer before the steroids scandal. Secondly, he has never, not once, failed a test for performance enhancing drugs, despite the increased testing due to his failure of a test for banned stimulants. Third, even Victor Conte, BALCO mastermind and outer of many other high-profile cheaters, maintains that he did not have Bonds on a steroid regimen.
How should Bonds be viewed? If you want to be objective, do it the right way: adjust his numbers for context and put them in proper perspective. You'll find him comfortably behind Ruth and Aaron. Ultimately though, the fact remains that Barry Bonds has never been caught breaking a MLB rule regarding banned performance enhancing drugs. He has maintained his post 2001 home run rate despite being tested for steroids multiple times a year. What more can he possibly do?
Welcome to Steroids Week here at Basebology!
This list may grow as I remember more, but until then:
"What Do Statistics Tell Us About Steroids?" excerpted from Baseball Prospectus' Baseball Between The Numbers
"Prospectus Today: Principles" on Lance Williams and Mark Fainaru-Wada