Well it’s been a while (i.e., here and here) since I checked in on Inland Seas, the Quarterly Journal of the National Museum of the Great Lakes, an interesting cross between an academic journal and a popular magazine dating to 1945. The journal and museum are the centerpieces of the Great Lakes Historical Society. The museum is a restored lake freighter (shown below) built in 1911 and now docked in the Maumee River in Toledo, Ohio.
The latest (Vol. 75, No. 2) issue’s first article is titled Early Maps of the Great Lakes and the First Boat Trip Across Lake Erie in 1669–a topic sure to get my attention. It turns out that no, Robert LaSalle and his 34 crewmen were not in fact the first to traverse the length of Lakes Erie, St. Clair and Huron in their famous sailing ship, the Griffon. Rather, it was two French Jesuits in canoes ten years earlier who did so, and who even made a pretty accurate map of it, given the circumstances. A major part of the Lake Erie traverse was done in March/April, 1670, in which they dealt with lots of ice, high winds, swampings, hostile natives and other perils inherent in such an escapade. Great stuff there.
But my favorite part of this journal may well be the “Great Lakes News” section, wherein various events from the previous three months are briefly mentioned. Many of these are entirely mundane. For example, we read that on January 6, “The Walter J. McCarthy Jr. departed Duluth after spending nearly two days loading frozen [taconite] pellets” and that on January 1 the last downbound commercial vessel of the shipping season cleared the Welland Canal.
But there’s usually also some much more interesting stuff, and so it is this time.
We learn for example that on January 6, the crew of the US Coast Guard’s Mackinaw happened to witness a stray dog go through the ice in the St. Mary’s River (connecting Lakes Superior and Huron) and to see it then struggle onto an island therein. Fully 20 crewmen then went in search, but finding no dog “set a campfire on shore and left a bowl of macaroni”, apparently considerate of the fact that this dog might be a vegetarian. A couple of days later they found the bowl empty, and the dog nearby, and then motored on over to Cheboygan where they delivered the dog to its (no-doubt surprised and thankful) owners.
But it gets better.On March 12, the US Coast Guard and several other agencies rescued 46 ice fishermen from an ice floe that broke free near Catawba Island, in SW Lake Erie. Another 100 or so escaped either by swimming or running across existing ice bridges before the full break occurred. The article doesn’t say it, but undoubtedly there are also a bunch more snowmobiles, ATVs and pickup trucks now resting on the bottom of western Lake Erie–the Coast Guard saves persons first, property second, if at all. Try swimming for land in the open (ice) waters of Lake Erie in early March after you’ve had maybe a six pack (or more) and tell me how it goes. This type of event happens more frequently than you might imagine–there are a lot of rusting snowmobiles at the bottom of Lake Erie.
The Canadian CG has different issues: “…the Canadian Coast Guard’s Hero class of midshore patrol boats are suffering from extreme rolling in even moderate seas. The rolling is so severe that crew members stuff jackets under the edge of their bunks to raise them so they will not be flung to the deck while asleep. Seasickness affects many crew members…”.
Not everything of interest involves the two Coast Guards however.
For example, on February 7, in Superior WI, we read that “the horn on the docked American Spirit stuck in the ‘on’ position, disturbing the neighbors at the nearby McDonald’s and local residences. Some hours later the horn was shut off. The sound could be heard for miles, as it should”. Is anything much worse than going to the local McDonald’s for morning coffee and cholesterol and getting summarily blasted out of there by a ship’s horn? I mean, other than having to listen to the music that one would otherwise be subjected to…
If you’ve been thinking (naively!) that ship fires would probably be among the easier class of possible fires to deal with, at least from a total water availability standpoint…well not so fast. It seems that “the St. Clair caught fire at its lay-up dock in Toledo…Fire crews from Toledo had a hard time getting hydrants on the dock to work… and had to just play water on the ship and let the fire burn out…”. Success in this case was measured in terms of preventing other nearby ships at the port from also catching fire.
There are non-boat-related news items as well. If you have some spare change, Ohio Governor Mike DeWine is seeking some “real money” to help combat Microcystis algal growth in Lake Erie. Dig deep now, because there’s nothing micro about the amount desired–about $1 billion (DeWine was heard to say “fight green with green” after the announcement). Farmers in the Maumee River basin (responsible for the phosphorous loading that contributes to the algal blooms) were in turn heard to respond “I’ll be glad to show you what some green corn and soybeans look like Mike”. And so on.
Also noted is that the Canadian government is actively seeking a temporary, light duty icebreaker as a replacement for those that will be laid up for repairs this winter. If you would happen to have a spare icebreaker that you don’t think you’ll need this winter, contact them.
Canada also takes this opportunity for a friendly seasonal reminder to always keep your stick on the ice, icebreaker or no.
I’ve been remiss in the book review department lately, where “lately” starts at roughly day one of this blog. This post changes all that in a hurry.
Recently I noticed the nearly 1400 page CRC Handbook of Aqueous Solubility Data (2010) sitting nearby, reminding me that in nearly nine years I’d not in fact read any of it. So I looked at the first couple of pages, and well, like old Mission Impossible episodes, once you engage, you’re in for the duration. Bottom line: this is a great read, and as a paperweight or ballast, even greater. This tome takes no prisoners: aqueous solubilities for 4661 organic chemicals, sans break. All organic chemistry, all the time; in it to win it.
Organizationally, the book is quite something else again. The first section is engagingly titled “Solubility Data”, comprised of 4661 entries arranged in–you guessed it–numerical order. Entry number one gets right after it, by way of bromodichloromethane (or alternatively, dichlorobromomethane–experts pressed for time just say “CHBrCl2”). Within it, as with each such entry, is found all kinds of useful data, including molecular weights, boiling and melting points, and of course, solubilities (both molar and by weight!). All necessary references are also included, for the skeptical–these authors aren’t hiding anything here. A “Comments” field contains useful ancillary information, such as “recrystallized”. There is also a complex “TPEAA” evaluation, avowedly for experts only.
The next entry, (chlorodibromomethane), is fairly similar to the first. In fact, all 4661 entries are markedly similar. Exactly the same actually, just slightly different. There is no guesswork as to just what the point of this book is. The Solubility Data section occupies fully the first 700 pages of the book…as well as the last 700 pages. If you want wild topical variations from one entry to the next, try an encyclopedia, newspaper or Science magazine: this book is for chemically focused readers.
One note is that the sheer volume of material can be an issue. But this is not unexpected–people do vary in the specific organic chemicals that will hold their attention indefinitely, after all. But then–just boom–you hit an entry that snaps you right out of it. For me entry 151 provides a good example: nitroglycerin (C3H5N3O9). Talk about boom! Is it really that hard to imagine the history involved in determining the boiling point of that sucker?! Research dollars available! And that could give you a heart attack just thinking about. However, to keep the book from exploding well beyond its 1400 pages (thus beyond a leisurely reading), the authors wisely leave such details to the reader.
Or take something like entry 4289, which most know simply as
(Metahanesulfonamide, N[1′-[2-(2,1,3-benzoxadiazol-5-yl)ethyl]-3,4-dihydro-4-oxospiro[2H-1-benzopyran-2,4′-piperidin]-6-yl]-). Catchy name, sure, but even the casual reader will note that chemical 4289 has a mysterious “intrinsic” solubility listed. What the hell’s that supposed to mean, one briefly wonders aloud, before moving on to entry 4290, which happens to be one colchicine. Now colchicine is, genetically speaking, a very important chemical, capable of instantly doubling an organism’s chromosome number. Talk about explosive, this is massive, all-at-once mutation, like something out of a B-grade 1950s-era film with giant ants that take over Guam or whatever–but without any H-bombs, atolls or any of that whole scene. Oh so you were thinking that everything was all “better living through chemistry” were you? Well think again hombre. Not for the squeamish.
I would be remiss (per request of the authors) if I did not note that this book has vey few weaknesses. The only one I could find was for entry #22, urea (CH4N2O), for which no boiling point is given. But think it through again: is ignorance of the boiling point of urea really a weakness…or rather an open research opportunity? I mean, who doesn’t have a stove after all? Speaking of urea and stoves, oh man, there was that time a buddy and I were climbing Mt. Rainier, and as usual it was damn cold, so we had a bottle to use to avoid those unwanted “wee-hour” excursions outside the tent…but it turns out that at breakfast we mixed it up with the water bottle…well let me tell you, that will impart flavor to the old oatmeal!
We can get into those details more later but we’re out of time for today. In summary, this book has been unduly neglected, given its importance to industrial society and the career advancement of the authors. Read it for Christ’s sake–it’s been nine years already and aqueous solubility issues really are out there.
Stay tuned for the next in the series, where we take a closer look at Dynamic elasticities and breaking points of commercial hardwoods, tentatively planned for the summer of 2024. This post is hereby concluded and the decision is final. Special mention to all those who participated with minimal regret.
I’m going to give this topic another explanatory shot with some different graphics, because many still don’t grasp the serious problems inherent in trying to signal and noise from tree ring size. The most advanced method for attempting this is called Regional Curve Standardization, or RCS, in which ring size is averaged over a set of sampled trees, according to the rings’ biological age (i.e. ring number, counting from tree center), and then dividing each individual series by this average. I include five time series graphs, successively containing more information, to try to illustrate the problem. I don’t know that I can make it any clearer than this.
First, shown below are the hypothetical series of 11 trees sampled at a single sampling location.
Each black line shows the annual ring area progression for each of 11 trees having origin dates spaced exactly 10 years apart (the bold line is just the oldest tree of the group). By using ring area as the metric we automatically remove part of the non-climatic trend, which is the purely geometric (inverse quadratic) effect from each series. Any remaining variation is then entirely biological and it exhibits a very standard tree growth pattern, one in which growth rate increases to a maximum value reached relatively early life (here, around age 80 or so) and then declines more slowly toward a stable asymptote, which I fix at 1.0. Each tree’s trajectory occurs in a constant climate over the 300-400 year period measured.
The next figure adds two components:
First, the blue line represents a constantly increasing climatic parameter over time, say temperature, expressed as a ratio of its effect on ring size at year 0. Thus, at year 400, the cumulative climatic effect on ring area, regardless of biological age, is exactly 3-fold of its year zero value (scale at right). The second addition is the series of red lines, which simply represent those same 11 trees’ growth trajectories growing under this climate trend. The climatic effect on growth is a super simple linear ramp in all cases–I am not invoking any kind of problematic, complex growth response (e.g. “divergence”), or any other complication. Thus, by definition, if we divide the two corresponding ring series for each tree, we get exactly the blue line, in all cases.
In the third figure:
I add a green line–this is the estimated RCS curve, computed the standard way (by aligning each tree according to its biological age and then averaging the ring sizes over all trees). This RCS curve is thus the estimated non-climatic ring size variation, which we accordingly remove from each tree by dividing the red growth series by it. Finally, we average the resulting 11 index series, over each of the 400 years, giving the stated goal: the estimated climatic time series.
It is at first glance entirely clear that the green RCS curve does not even come close to matching any of the black curves representing the true non-climatic variation…which it must. According to standard dendroclimatological practice we would now divide the 11 red curves by this green RCS curve–which is thereby guaranteed not to return the true climatic signal. So what will it return?
It returns the orange line shown above. No that’s not a mistake: it will return an estimated climatic trend of zero.
And this is the entire point–the supposedly most advanced tree ring detrending method is fully incapable of returning the real climatic trend when one exists. Note that I’m keeping everything very simple here–this result does not depend on: (1) either the direction or magnitude of the true trend, or (2) the magnitude, or shape, of the non-climatic trend in the sampled trees (including no such whatsoever). That is, this type or magnitude of result is not specific to the situation I set up. The problem can be reduced, but never eliminated, by increasing the variance in tree ages in the sample. But since standard field sampling practice is to sample the oldest possible trees at a site, this is very rare, a fact which the data of the International Tree Ring Database (ITRDB) shows clearly–which is ironic given that Keith Briffa and Ed Cook mentioned the importance of exactly this issue in a white paper available at the ITRDB site.
Lastly, suppose now that the last usable year for all ring series occurred a few decades ago. This will occur, for example, due to many ITRDB field samples being collected decades ago now, or for any perceived problems in the climate-to-ring response calibration function, which is must be stable and dependable (notably, the “divergence” effect, in which linear relationships between climate and ring size break down, badly). What will be the result of eliminating, say, the last five decades of data, and replace them with instrumental data? Well, you will then get exactly this:
Look familiar? Does that look like anything remotely approaching success to you? Again, I have not even broached other possibly confounding problems, such as co-varying growth determinants (e.g. increasing CO2- or N-fertilization, changing soil moistures, or inter-tree competition), nor non-linear responses in the calibration function, nor any of the thorny issues in large-scale sampling strategies, reconstructions and their corresponding data analysis methods. Those things would all exacerbate the problem, not improve it. It’s a total analytical mess–beginning and end of story.
I can’t make it any clearer than this. And yes I have the R code that generated these data if you want to see it.
Some Easter slide guitar, courtesy of one of the true masters thereof, Kelly Joe Phelps.
Well I know, yeah I know…that I’ve been converted…
Now do you?
You’ve got to know sir
That I’ve made me a change
That I’m not afraid to call my Savior’s name
Well I know…that I’ve been converted now…
Kelly Joe Phelps, I’ve Been Converted
I just closed my eyes again–
Climbed aboard the Dream Weaver train
Trying to take away my worries of today
And leave tomorrow behind
Fly me high through the starry skies
Take me to an astral plane
Across the highways of fantasy
Help me to forget today’s pain
Though the dawn may be coming soon
There may still be some time
Fly me away to the bright side of the moon
And meet me on the other side
I don’t know his name for sure but I think somebody said “Hi Harlan”” to him from their car stopped at an intersection. He is well known in those parts.
I’ve seen him for months on the streets, and since I’ve been here less than a year, I’d guess he’s been there much longer. He looks to be in his 60s, and walks with a single crutch at all times, such that your can hear him coming even when you don’t see him. He accosts almost every passer-by with a much garbled “Could you spare a dollar, I’m trying to get something to eat”. He seems to be reasonably successful, based on the number of people I see stopped with him, and as far as I can tell, he actually uses the money for food, not alcohol (a big issue with street beggars). He has, for all I can tell, not a soul in this world to count on for anything. I have no idea where he stays at night.
When I first saw him last summer he acted as described above. I had not seen him throughout the winter, yesterday being the first time I’d ventured out on the streets in that area. Harlan was still begging but now also yelling intermittently–incoherent phrases aimed at nobody in particular, and with gusto.
It was still chilly out, but I found a nice spot in the afternoon sun and set down my guitar and amp and plugged in and set up. I could hear Harlan coming down the sidewalk, and he pointed at my stuff and mumbled something incoherent that appeared to involve some danger of being arrested by the cops or something, I’m not sure. I replied “OK man” and continued with what I was doing, and Harlan moved on.
There was hardly anybody on the streets but it was downright comfortable for the first time in months so I started playing, for the practice if nothing else. I soon noticed a guy off to my right 10 yards, smoking a cigarette and listening. A few minutes later he came up and said he had no money with him but if he did he’d give me some, because I sounded great, quite similar to Pat Metheney. He was a bassist; he knew music and paid me other generous compliments. I replied no problem man, being compared favorably to Pat Metheny is worth more to me than dollar or two. He left but came back soon with two friends, threw in a tip and we all talked briefly about guitar favorites: Leo Kottke, Ry Cooder, and Chris Smither in particular. I convinced them that yes, they really should see Chris when he comes to town in May. And Leo Kottke’s song “I Yell at Traffic” came to my mind.
I resumed playing and a little later, Harlan came around the corner, yelling, stopped for a minute, and then sat down on some restaurant steps a few feet away. He stopped yelling and muttering to himself. He just say there, listening. Sensing this, I broke into a slow and deliberate rendition of arguably the most beautiful song I know, Bob Dylan’s Visions of Johanna, a waltz which I do in the key of A. Harlan continued to sit and gaze into the distance, in the warm sun and listen, the sound reverberating through the street. And then through another piece, before getting up and continuing his march. Hopefully, a few minutes of beauty and solace in an otherwise desperate existence.
If I see him again, I’m going to do it again, except that I’m going to try to play the best thing my fingers will generate.
Some while back I checked out covers of this relatively unknown classic–of which there are many–for the Bob Dylan Project. A couple of particularly good ones are below but feel free to contribute more…
So, the IPCC has produced a special report on the issue of limiting the global temperature increase to 1.5 degrees C. This report is still open for comments for another 13 days…if you are an “expert” in the IPCC’s eyes. And what if you are not? Well if you’re American, you could still have commented, for a 30 day period that ended last week (Feb. 8), through a commenting system run by the United States Global Change Research Program (USGCRP)…assuming you actually knew about it. And that latter issue is the topic of this post.
All IPCC report drafts are open to expert review, internationally, through a system the IPCC operates. In that system, you apply to be a reviewer by submitting your name and qualifications, which basically involves stating your expertise, including your degree and a list of up to five publications that demonstrate it. Then IPCC-associated folks say yes or no to your request.
But IPCC reports are also open to comments by national governments. The United States of course does so, the USGCRP administering this process. But unlike the IPCC process, the USGCRP solicits comments from… anybody. The notifications for these comment periods are required by law to be posted in the Federal Register, and the notice also appears on a USGCRP web page (corresponding links here and here; screenshots for the two below).
At least for this report, the USGCRP also posted four Twitter notices, on January 16, 24, 29 and February 5, all identical. Why they waited six days before the first notice I don’t know. Below is the Jan. 24 notice.
You still have to register, but in that process you just select the category from a drop-down list that best describes your status, in one of five broad categories, screenshot below:
I now encourage you to read the Federal Register notice linked to above. Notice exactly what it says. Specifically, even though the process is open to everyone, the entire notice, including the title (“Call for Expert Reviewers…”) is framed in the language of “expert” reviewer, the crux of which reads as follows:
As part of the U.S. Government Review, starting on 8 January 2018, experts wishing to contribute to the U.S. Government review are encouraged to register via the USGCRP Review and Comment System (https://review.globalchange.gov/?)… The USGCRP coordination office will compile U.S. expert comments and submit to the IPCC, on behalf of the Department of State, by the prescribed deadline. U.S. experts have the opportunity to submit properly formatted comments via the USGCRP Review and Comment System (https://review.globalchange.gov/?) from 8 January to 8 February 2018. To be considered for inclusion in the U.S. Government submission, comments must be received by 8 February 2018.
Experts may choose to provide comments directly through the IPCC’s Expert Review process, which occurs in parallel with the U.S. Government Review. Registration opened on 15 December 2017, and runs through 18 February 2018: https://www.ipcc.ch/?apps/?comments/?sr15/?sod/?register.php
The Government and Expert Review of the IPCC Special Report on Global Warming of 1.5 °C ends February 25, 2018.
Do you see any indication anywhere in any of it, that indicates that the commenting process is in fact open to the general citizens of the United States? I don’t. This is in fact only apparent when you actually go to the USGCRP Review and Comment page, and attempt to register, per the screen shot above. To say nothing of the fact that experts using the IPCC’s review system have 90 days to comment whereas those using the USGCRP’s have only 30.
OK, so then one day ~two weeks ago I was wasting my time and energy, which is to say I was reading Twitter comments, and I noticed a climate scientist, Katharine Hayhoe relay a message inviting “colleagues” to comment on the IPCC report (original comment here). In response, a climate activist, Steve Bloom, asked her directly (paraphrasing) “And what about people like me?”, meaning non-academics (and non-experts to the IPCC).
This conversation immediately went downhill, but the bottom line in this context is that Hayhoe either (1) had no idea that all Americans still had nearly another two weeks or so to comment on the report, or (2) she did know but didn’t tell him. I have no evidence for believing the latter, and so the logical conclusion is the former. I didn’t see the exchange until a few days later, but when I did I jumped in to alert everyone that yes indeed, any American citizen could still comment for another week or so. I also directly criticized Hayhoe for not knowing this, given that she was a lead author on a chapter of another report, the National Climate Assessment #4 that just went through the USGCRP review process. But after seeing how the USGCRP phrases their official notices (and Tweets) regarding their review process, I can surely see why she might not have known.
Hayhoe, who won the AGU’s “Climate Communication” award four years ago (with its $10,000 prize) made no response whatsoever to my comments—she simply blocked me on Twitter, meaning I can no longer read any of her comments there. No acknowledgement of the USGCRP process, no apology to Bloom, nothing. Her main comment in the process was to tell Bloom not to talk disrespectfully to climate scientists, adding that he’d been warned before, screen shot below.
Steve Bloom–no, no response from him either. The only person to comment at all on what I said was Richard Betts, a UK climate scientist who stated that it was interesting to learn that the United States allowed all citizens to comment on IPCC reports. Maybe the United States, unlike the IPCC, understands that having something important to say, is not limited to “experts”, whatever the latter entails exactly. Volumes could be written on that topic alone, but that’s not for the here and now.
So, this is just one example of the kind of thing we’re dealing with in the whole climate change public outreach circus, or tragedy, whichever it is. But it’s one thing if it’s just an entertaining circus, and another thing altogether if your so-called “climate communicators” can’t communicate crucial facts about the public interaction process.
This post has been updated, with corrected data and modified discussion, as detailed in the text.
Does anything say “100 Years of the National Hockey League” like say, a Tampa Bay vs Vegas matchup. Montreal, Toronto, Ottawa? Please; bunch of party crashers them.
In case you missed it, National Hockey League play is, today, exactly 100 years old. On December 19, 1917 the first two games in the new league had the Toronto Arenas at the Montreal Wanderers, and the Montreal Canadiens at the Ottawa Senators. This limited slate was due in large part to those being the only four teams in the league. It turns out that the Wanderers got their first and only win in franchise history, which lasted just six games. They got past the Arenas in the common hockey score of 10-9. The Arenas, conversely, went on–along with the Canadiens–to become one of the two most storied franchises in NHL history: today’s Toronto Maple Leafs. The Senators’ first incarnation lasted until 1934, and after a 58 year absence came the second (and current) version in 1992.
So anyway, there’s hype and hoopla happening, and also discussions of the greatest seasons, teams, players, etc. As for me, I thought it would be great fun to crunch 90 years of team-season numbers to see what they indicated about team records, actual versus expected. Two minutes for tripping, and without even inhaling anything.
So yesterday I was riding the bus, which I only do when I need to tote both my guitar and amp downtown. The two-plus miles is just a little too far for the ~60 pound carry, especially given an injured shoulder and wrist, and sidewalks that are a mess from a foot of snow last week.
A couple of stops after boarding, on steps a guy with a very tattered beige coat, like something that might have been involved in say, some street fights, or use as a dog’s bed. He was dragging a heavy-looking plastic bag full recyclables, and sat down next to me.
“Play the guitar, eh?”
“Yeah” says I.
“What kind of stuff you like?”
“Acoustic 12…a lot of Bob Dylan, but also John Gorka, Chris Smither, Greg Brown, the Dead, some Zeppelin…some of my own stuff too.”
In the five minutes before he got off, he told me the abridged version of how he once played a lot, both guitar and keyboards, apparently as a professional musician, including a lot of local shows at various venues, with a band was busy and popular, mostly back in the 1980s and 90s I gathered. He said he made good money at it and even shared the bill with some well-known bands/acts, such as Mitch Ryder, Steppenwolf, and (I think) Dave Alvin’s band (The Blasters?). About how Ryder once got quite upset with him, when his band was supposed to be opening his show but he was instead drunk in a local bar, having completely forgotten about it. His band mates had to track him down, and the resulting delay caused Ryder to open for him, instead of vice-versa. He smiled at the memory.
I asked him if he was still performing or playing. He talked for a couple of minutes–about how that’s all gone now. He lives on disability and food stamps, supplemented I guess, by whatever he gets from collecting and hauling recyclables via foot and bus, and street begging, which he said he makes some money at.
“Yeah, I could…but damn alcohol…” he said.
As he got up to get off, I invited him to bring his guitar and we could jam together on the street. He said that would be cool, and would do so. There wasn’t time to get his name or number. Hope I see him again.
Now you would not think, just to look at him
But he was famous long ago
For playing the electric violin
On Desolation Row
Getting into some issues only makes you wish that you hadn’t, when you realize how messed up they are, at a fundamental level.
Here’s a great example involving statistical analysis, as applied to win/loss (“WL”) records of sports teams, the base concept of which is that it’s possible to estimate what a team’s WL record “should” have been, based on the number of goals/runs/points that it scored, and allowed, over a defined number of games (typically, a full season or more). This blog post by Bill James partially motivates my thoughts here.
Just where and when this basic idea originated I’m not 100 percent sure, but it appears to have been James, three to four decades ago, under the name “Pythagorean Expectation” (PE). Bill James, if you don’t know, is the originator, and/or popularizer, of a number of statistical methods or approaches applied to baseball data, which launched the so-called “SABR-metric” baseball analysis movement (SABR = Society for American Baseball Research). He is basically that movement’s founder.
In the linked post above, James uses the recent American League MVP votes for Jose Altuve and Aaron Judge, to make some great points regarding the merit of WAR (Wins Above Replacement), arguably the most popular of the many SABR-metric variables. The legitimacy of WAR is an involved topic on which much virtual ink has been spilled, but is not my focus here; in brief, it tries to estimate the contribution each player makes to his team’s WL record. In the article, James takes pointed exception to how WAR is used (by some, who argue based upon it, that the two players were basically about equally valuable in 2017). In the actual MVP vote, Altuve won by a landslide, and James agrees with the voters’ judgement (pun intended): WAR is flawed in evaluating true player worth in this context. Note that numerous problems have been identified with WAR, but James is bringing a new and serious one, and from a position of authority.
One of James’ main arguments involves inappropriate use of the PE, specifically that the “expected” number of wins by a team is quite irrelevant–it’s the *actual* number that matters when assessing any given player’s contribution to it. For the 2017 season, the PE estimates that Judge’s team, the New York Yankers, “should” have gone 101-61, instead of their actual 91-71, and thus in turn, every Yanker player is getting some additional proportion of those ten extra, imaginary wins, added to his seasonal WAR estimate. For Altuve’s team, the Houston Astros, that’s not an issue because their actual and PE WL records were identical (both 101-61). The WAR-mongers, and most self identified SABR-metricians for that matter, automatically then conclude that a team like this year’s Yanks were “unlucky”: they should have won 101 games, but doggone lady luck was against ’em in distributing their runs scored (and allowed) across their 162 games…such that they only won 91 instead. Other league teams balance the overall ledger by being luck beneficiaries–if not outright pretenders. There are major problems with this whole mode of thought, some of which James rips in his essay, correctly IMO.
But one additional major problem here is that James started the PE craze to begin with, and neither he, nor anybody else who have subsequently either modified or used it, seems to understand the problems inherent in that metric. James instead addresses issues in the application of the PE as input to the metric (WAR) that he takes issue with, not the legitimacy of the PE itself. Well, there are in fact several issues with the PE, ones that collectively illustrate important issues in statistical philosophy and practice. If you’re going to criticize, start at the root, not the branches.
The issue is one of statistical methodology, and the name of the metric is itself a big clue–it was chosen because the PE formula is similar to the Pythagorean theorem of geometry: A^2 + B^2 = C^2, where A, B and C are the three sides of a right triangle. The original (James) PE equation was: W = S^2 / (S^2 + A^2), where W = winning percentage, S = total runs scored and A = total runs allowed, summed over all the teams in a league, over one or more seasons. That is, it supposedly mimicked the ratio of squared lengths between one side, and the hypotenuse, of a right triangle. Just how James came to this structural form, and parameter values, I don’t know and likely very few besides James himself do; presumably the details are in one of his annual Baseball Abstracts from 1977 to 1988, since he doesn’t discuss the issue that I can see, in either of his “Historical Baseball Abstract” books. Perhaps he thought that runs scored and allowed were fully independent of each other, orthogonal, like the two sides of a right triangle. I don’t know.
It seems to me very likely that James derived his equation via fitting various curves to some empirical data set, although it is possible he was operating from some (unknown) theoretical basis. Others who followed him, and supposedly “improved” the metric’s accuracy definitely fitted curves to data, since all parameters (exponents) were lowered to values (e.g. 1.81) for which no theoretical basis is even possible to conceive of: show me the theoretical basis for anything that scales up/down according to the ratio of a sum of parts, and one component thereof, by the power of 1.81. The current PE incarnation (claimed as the definitive word on the matter by some) has the exponents themselves as variables, dependent on the so-called “run environment”, the total number of runs scored and allowed, per game. Thus, the exponents for any given season are estimated by R^0.285, where R is the average number of runs scored per game (both teams) over all games of a season.
Even assuming that James did in fact try to base his PE on theory somehow, he didn’t do it right, and that’s a big problem, because there is in fact a very definite theoretical basis for exactly this type of problem…but one never followed, and apparently never even recognized, by SABR-metricians. At least I’ve seen no discussion of it anywhere, and I’ve read my share of baseball analytics essays. Instead, it’s an example of the curve-fitting mentality that is utterly ubiquitous among them. (I have seen some theoretically driven analytics in baseball, but mostly as applied to ball velocity and trajectory off the bat, as predicted from e.g., bat and ball elasticity, temperature, launch angle, and etc, and also the analysis of bat breakage, a big problem a few years back. And these were by Alan Nathan, an actual physicist).
Much of science, especially non-experimental science, involves estimating relationships from empirical data. And there’s good reason for that–most natural systems are complex, and often, one simply does not know, quantitatively and apriori, the fundamental operating relationships upon which to build a theory, much less how those interact with each other in complex ways at the time and space scales of interest. Therefore one tries instead to estimate those relationships by fitting models to empirical data–often some type of regression model, but not necessarily. It goes without saying that since the system is complex, you can only hope to detect some part of the full signal from the noise, often just one component of it. It’s an inverse, or inferential, approach to understanding a system, as opposed to forward modeling driven by theory; these are the two opposing approaches to understanding a system.
On those (rare) occasions when you do have a system amenable to theoretical analysis…well you dang well better do so. Geneticists know this: they don’t ignore binomial/multinomial models, in favor of curve fitting, to estimate likely nuclear transmission genetic processes in diploid population genetics and inheritance. That would be entirely stupid, given that we know for sure that diploid chromosomes conform to a binomial process during meiosis the vast majority of the time. We understand the underlying driving process–it’s simple and ubiquitous.
The binomial must be about the simplest possible stochastic model…but the Poisson isn’t too far behind. The Poisson predicts the expected distribution of the occurrence of discrete events in a set of sample units, given knowledge of the average occurrence rate determined over the full set thereof. It is in fact exactly the appropriate model for predicting the per-game distribution of runs/goals scored (and allowed), in sports such as baseball, hockey, golf, soccer, lacrosse, etc. (i.e. sports in which scoring is integer-valued and all scoring events are positive and of equal value).
To start with, the Poisson model can test a wider variety of hypotheses. The PE can only predict a team’s WL record, whereas the Poisson can test whether or not a team’s actual runs scored (and allowed) distribution, follows expectation. To the extent that they do follow is corresponding evidence of true randomness generating the variance in scores across games. This in turn means that the run scoring (or allowing) process is stationary, i.e., it is governed by an unchanging set of drivers. Conversely, if the observed distributions differ significantly from expectation, that’s corresponding evidence that those drivers are not stationary, meaning that teams’ inherent ability to score (and/or allow) runs is dynamic–they change over time (i.e. between games). That’s an important piece of knowledge in and of itself.
But the primary question of interest here involves the WL record and its relationship to runs scored and allowed. If a team’s runs scored and allowed both closely follow Poisson expectations–then prediction of the WL record follows from theory. Specifically, the distribution of differences in two Poisson distributions follows the Skellam distribution, described by the British statistician J.G. Skellam in the 1950s, as part of his extensive work on point processes. That is, the Skellam directly predicts the WL record whenever the Poisson assumptions are satisfied. However, even if a team’s run distribution deviates significantly from Poisson expectation, it is still possible to accurately estimate the expected WL record, by simply resampling–drawing randomly several thousand times from the observed distributions–allowing computers to do what they’re really good at. [Note that in low scoring sports like hockey and baseball, many ties will be predicted, and sports differ greatly in how they break ties at the end of regulation play. The National Hockey League and Major League Baseball vary greatly in this respect, especially now that NHL ties can be decided by shoot-out, which is a completely different process than regulation play. In either case, it’s necessary to identify games that are tied at the end of regulation.]
If instead you take an empirical data set and fit some equation to those data–any equation, no matter how good the fit–you run the risk of committing a very big error indeed, one of the biggest you can in fact make. Specifically, if the data do in fact deviate from Poisson expectation, i.e. non-stationary processes are operating, you will mistake your data-fitted model for the true expectation–the baseline reference point from which to assess random variation. Show me a bigger error that you can make then that one–it will affect every conclusion you subsequently come to. So, if you want to assess how “lucky” a team was with its WL record, relative to runs scored and allowed, don’t do that. And don’t get me started on use of the term “luck” in SABR-metrics, when what they really mean is chance, or stochastic, variation. The conflation of such terms in sports that very clearly involve heavy doses of both skill and chance, is a fairly flagrant violation of the whole point of language. James is quite right in pointing this out.
I was originally hoping to get into some data analysis to demonstrate the above points but that will have to wait–the underlying statistical concepts needed to be discussed first and that’s all I have time for right now. Rest assured that it’s not hard to analyze the relevant data in R (but it can be a time-consuming pain to obtain and properly format it).
I would also like to remind everyone to try to lay off high fastballs, keep your stick on the ice, and stay tuned to this channel for further fascinating discussions of all kinds. Remember that Tuesdays are dollar dog night, but also that we discontinued 10 cent beer night 40 years ago, given the results.
Broken bottles, broken plates
Broken switches, broken gates
Broken dishes, broken parts
Streets are filled with broken hearts
Broken words never meant to be spoken
Everything is broken
Broken cutters, broken saws
Broken buckles, broken laws
Broken bodies, broken bones
Broken voices on broken phones
Broken hands on broken ploughs
Broken treaties, broken vows
Broken pipes, broken tools
People bending broken rules
Hound dog howling, bullfrog croaking
Everything is broken
Bob Dylan, 1989
So, there was a high school class reunion a few months back, and it’s World Series time again, so now seems a good time for an overdue, second episode of our series of the above title. In episode one, I explored an incident involving sub-optimal decision making in high school so I think I’ll just continue on that theme here.
I saw a number of old classmates, and teammates, at the reunion. I think class reunions are great. They can cause one to reflect on really important topics, such as the passage of time, or the nature of life’s changes. Or to even deeper things. Explosives for example. Just what “loud” really entails. The nature of stupidity.
It seems that I had become aware that personal fireworks were legal in the next county, and had thus traveled the 40 miles to obtain a few dozen “M-80” fireworks, ostensibly for use during the Fourth of July. It also seems that sometime later, my friend Steve and I found ourselves parked in front of our friend Doug Brown’s house after dark, with said bag of M-80s and a lighter. Now, an M-80, we’d been told, contained the equivalent gunpowder of a quarter stick of dynamite, which I thought was pretty impressive but did no actual testing of. If one of these things goes off on, say, someone’s front porch, it would not typically go unnoticed, and that concept did seem, to us, worthy of some testing at that particular time.
It additionally seems that I was the driver and Doug’s house was off to our left. The plan, which I think we put a solid 30 seconds of thought into, was that we would launch one of these onto Doug’s porch–about maybe 75 ft away–while seated in the vehicle, so as to effect a prompt getaway. We came up with a fair and efficient division of labor in which Steve would light the fuse and hand the thing to me–I would then fire it toward the porch and immediately hit the gas, making ourselves rapidly scarce. It was a great plan as far as I was concerned: all I had to do was throw and floor it, whereas Steve had the equivalent of six to eight sticks of dynamite in a bag on his lap, with an open flame in his hand. This struck me as equitable, given that I was providing the vehicle and the right arm.
So…what’s the baseball connection here, you may wonder. Well, I played shortstop in high school, whereas Steve didn’t, and so it was logical that I should do whatever throwing was involved. Shortstop is a fun position, because you get to sprint to chase down ground balls, and then watch the first baseman sprint to chase down the throw you just sailed some distance beyond him. Now, 70-80 feet is a lot shorter than a typical throw from shortstop to first base…but an M-80 is also a lot lighter than a baseball. So I knew I should put some mustard on it to insure getting it at least somewhere near the porch. Being quite experienced at firing balls into the adjacent woods from deep short, I wasn’t too worried about it. If the M-80 banged off the front of the house first or whatever, no big deal, I mean assuming nobody opened the front door at the wrong instant.
Now may be a good time to remind ourselves of the importance of taking all potentially relevant variables into consideration–apriori even–in events like these. And do we think enough about the tangible value of trial runs? Probably some room for improvement there too.
Anyway, Steve successfully got said firework lit without blowing us up, and the ensuing exchange to me was also flawless. With right arm extended and a good five seconds or so to work with, I eyed Doug’s porch and applied my best Nolan Ryan fastball to the explosive. Now, I think it’s fair to say that (1) the average person is just not that aware of exactly where one’s car door meets one’s car roof, (2) that I qualify as quite average in that context, and (3) that that specific location took on above average significance, in that particular situation. In short, when my hand was just about to send said explosive device on it’s planned trajectory, said hand was inadvertently applied, with considerable force, to said vehicular location, and separated from said device, thereby placing the latter on a trajectory not nearly as likely to achieve the original objective. This in turn would necessitate a rapid adjustment in plan and action, not to mention vocalization.
This is more or less a science blog, and I ask you, are many topics more fascinating, really, than the physics of acoustics under confinement? Maybe heredity–I find that interesting too. Also, involuntary reflexes, impromptu vocalizations: good stuff. How about hand-eye coordination under duress? Personal safety and survival? Blood?
Bodily dismemberment? All topics worthy of consideration when you get down to it. Let’s explore some of these for just a moment.
Acoustic physics, let’s take. As we know, Newton’s First Law of Loud, states “Any acoustically active device, placed under spatial confinement, will manifest even more of its acoustic characteristics, in fact quite a lot more than you’d think just from theory alone”. Take spatial relationships: just how much room for rapid bodily movement is there, really, in the front passenger seat of a typical car? How can humans maximize movement efficiency in response to active, explosive devices experiencing random trajectories?
Now back to our story. To cut to the chase, upon hand-car impact, our active device–the one under current discussion–experienced a rather sudden change of x coordinate velocity–one markedly away from Doug’s front porch, opposite that really, which is to say in the general direction of one Steve. More specifically, toward Steve’s male-specific, hereditarily significant anatomy. And there it landed, for a brief moment. Although entirely stunned, and with my hand feeling possibly broken, I was still able to collect myself, breathe a sigh of relief and comment on just how fortunate we were, really, that said M-80 had not taken an alternate trajectory and landed instead, in or near the bag of 30 or so other M-80s, within the confines of our vehicle, in which we too were present, due to our plan, in the street in front of our friend Doug Brown’s house. Steve also reflected for a bit on this fortunate state and concurred that such an outcome would have been potentially problematic on several counts, not the least of which was just how autopsies and identifications based on scattered body parts are conducted.
The preceding is not in fact what transpired at that moment.
Rather, Steve executed what I think to this day is the most rapid series of body movements I’ve ever seen from a human being, with the possible exception of the time I scrambled up and over a rock to find my neck about three feet directly in front of the head of a large rattlesnake. Conscious thought was not part of the process. M-80s had fuse times of roughly six to seven seconds, going strictly from memory. I’d guestimate that at this point, about four of those remained. As I recall it, there were, in order (1) an involuntary yell, (2) a ceiling-constrained jump upward, and (3) a failed attempt to flick the thing, by a backhand motion, away from where it resided. This process took maybe two seconds, maximum, and led to another entirely frantic attempt–panicked would work–which succeeded in flinging the thing down towards Steve’s feet. This, very fortunately, was not where the bag of other M-80s had been placed, and additionally, it’s one thing to have your feet blown off but quite another to have your evolutionary lineage ended.
Down there our device detonated, with a flash, maybe 1 to 1.5 seconds later.
What M-80 detonations lack in duration and beauty of light display they make up for in sheer decibels; they aren’t fireworks so much as small bombs. This was the most unbelievably loud thing I’d ever heard, and that includes seeing Ted Nugent in the old concrete and steel Toledo Sports Arena (also with Steve). It was concussive. Steve told me he basically could not hear for several days. The car was immediately filled with an acrid cloud of sulfurous smoke. My hand felt very possibly broken. I could neither hear nor see, and my first thought was “We gotta get out of here right NOW, before Doug comes out and sees this”. Or even worse, his dad, with a possible call to the police. But even in the best of circumstances, it’s not easy to go straight from Nolan Ryan to Mario Andretti, quickly. I could not see without sticking my head out the window, which I did until the breeze created cleared out the cab. I’m not sure that Steve knew exactly what had happened or even where he was, but didn’t have time to investigate. I was pretty sure he was alive and that would have to be good enough for the moment.
I think the evening’s festivities were concluded with this event, although I wouldn’t necessarily place money on that either. If Doug is reading, I’d like to formally apologize for the rubber patch laid in front of his house and any subsequent effect on property values that may have resulted.
Thanks for reading and please stay tuned for the next episode, in which we’ll explore how surprisingly inconvenient cul-de-sacs can be in certain circumstances, and/or other fascinating topics.
Fewer prescribed medications and more of this instead would be my prescription. Absolute classic guitar work by Bobby and Jerry in the song transition starting at about 2:00, IMO.
WTF would I do without these guys?
This here one ain’t not so bad either: