Thursday, November 1, 2018


Willie McCovey's passing reminds us of those paradoxical times when people thought it was amazing when a ballclub had four players who could hit 20+ HRs a year. (Examining that phenomenon as it existed in the four decades in which McCovey played is not part of this post, but it'd make an interesting follow-up...we'll try to remember to do that.)

What we're here to do today is a bit different. We want to examine McCovey's peak, which was a bit later in manifesting itself than what is usually characterized by sabermetric theory. (Truth told, peaks built around single seasons, such as the age 27 shibboleth, are ultimately not very useful--either for predictions or evaluations. We need more years, and we need to see peaks in the context of some number of years.)

And so, here, we're dusting off one of our favored "flavors of peak"--the six-year version. We require that a player collects at least 2500 plate appearances over those six years to be eligible to appear on a peak list--for which we resolutely (read: stubbornly) sort it by the old-school, "highly flawed" OPS+.

OPS+ is flawed, but what isn't? "Better" measures quickly become far too wonky and don't provide significant advances in understanding offensive ability--which is 90% responsible for the selection criteria involved in Hall of Fame arguments. (The other 10% are what people spend countless hours chasing their tales about.)

So, a useful basic approach to evaluating a hitter's historical achievement can still be found in OPS+, which is league and park adjusted--the basic and useful necessary adjustments. And, as noted, six-year increments give us a benchmark for how well a player can sustain a "peak" performance. When measured against all the hitters in baseball history, it's both illuminating and meaningful.

When we do this for McCovey, we see he has a great "stretch" (pun definitely intended...) from age 27-36 clustered in five six-year measures (ages 27-32, 28-33, 29-34, 30-35 and 31-36). In these five age ranges, McCovey ranks in the all-time top ten for OPS+ for six-year averages.

Most of this is driven by the three great seasons he had in a row from 1968-70, where his aggregate OPS+ tops out at 188. But the seasons surrounding these, particularly the years from 1965-67, weren't exactly chopped liver: McCovey's OPS+ for those years was 159. The backside (1971-74) was lower, but not that much lower (148 OPS+). All of that, and the forces of age as they impose themselves upon hitters, explains McCovey's continuing lofty position in the six-year rankings all the way out into the age 31-36 range.

And regarding the Hall of Fame, it's instructive to look at the leaderboards for six-year OPS+ to get a sense of how many hitters with lofty rankings over these "half a HoF" snapshots wind up in the Hall of Fame. We won't do anything systematic with that here--but let's look at the age 27-32 range with respect to who's in/out of the HoF.

The guys in the Hall are the ones in white type. As you can see, 21 of the Top 30 guys on this list have been inducted. (Several others ought to be inducted eventually--Barry Bonds, Miguel Cabrera, Manny Ramirez, Albert Pujols. And we can always hope that the Vets Committee--or whatever they're calling that overdetermined clump of misdirected ersatz lobbyists these days--will see fit to put in Dick Allen before he dies. That would bring us up to 26 out of 30.)

Rights, wrongs, and rants notwithstanding, we can see McCovey here at #10, where he's in fine company. RIP, Willie...

Tuesday, October 30, 2018


Following up on our discussion of what happened to the Astros in their ALCS matchup with the 2018 World Champion Boston Red Sox, we thought it might be worthwhile to see if playoff teams--and World Series winners in particular--showed a pattern of hitting well against relief pitchers. (You should know that the Dodgers, the first losers in two consecutive World Series since the Rangers did in 2010-11, had their bullpen shredded by both of the teams that beat them--the Astros in 2017, and the Red Sox this year...the Dodger relievers posted a 5.48 ERA in the just-completed Fall Classic.)

Thinking more globally, we went back to the data at Forman et fils ( to look at the overall performance vs. relievers over the past decade. (That gives us nine years of data to work with--a total of 270 data points--just shy of what's needed to win twelve slightly used Dodger Blue™ cupcakes.) Do teams that make the playoffs hit better than average against relievers? And do teams that win the World Series exceed the average of "garden variety" post-season teams?

The answer to both these questions is "yes." The table at right breaks it all out for you. Teams that
made the post season have their OPS+ vs. relievers displayed in bold type. Teams with a 120 "sOPS+" (Sean's acronym, not ours!) are shown in scalding orange; we've also color-coded teams with 110-119 (pale orange), 100-109 (yellow), and--on the opposite side of the spectrum--teams whose "sOPS+" is less than 85 (pale, pale blue).

At the bottom of the chart you have some averages--these are yearly "sOPS+" averages for the playoff teams. As you can see, the figures are uniformly above league average: for the nine years in question, the average "sOPS+" is 107.

Finally, note the cells with the double-thick lines around them. These are the World Series winners. And, yes, the World Series winners (as seen in the double-thick-lined box at the very bottom right of the table) are better yet on average than their post-season also-rans. Over the past nine years, World Series winners have an aggregate "sOPS+" of 112 vs. relievers.

Now, doing well in this statistic doesn't guarantee you a trip to the post-season; after all, it's only one component of team performance. There are many examples of teams doing well in this statistic who didn't make it to the playoffs at all. But if you do make it, having an offense that is able to do damage against the opposition's bullpen seems to give you a measurable advantage with respect to winning the World Series.

(And to complete another historical tidbit that was given a teaser above: teams that lost consecutive appearances in the World Series include not only the 2017-18 Dodgers and 2010-11 Rangers, but the 1991-92 Braves, the 1977-78 Dodgers, the 1963-64 Yankees, the 1952-53 Dodgers, the 1936-37 Giants, the 1923-24 Giants, the 1921-22 Yankees, and two teams--the 1911-12 Giants and the 1907-09 Detroit Tigers, who are the only teams to lose three World Series in a row. By doing it this year and last, however, the Dodgers have joined the Giants as the only teams to have three instances of "two-time loser" syndrome in the World Series. To match their Bay Area rivals, they'll need to make it back to the World Series next year--and hit the skids again...)

Friday, October 19, 2018


...of your opinion about the call that clearly affected the outcome of Game 4 in the ALCS between the Red Sox and the Astros, there is one incontrovertible (and ironic) fact.

The Astros' bullpen, which had posted only one sub-par month (July, 5.19 ERA) during a season of exemplary achievement, picked a most unfortunate time to regress, giving serious ground in three games during the ALCS. Their overall ERA for the series (5.79) was actually better than their overall performance.

The Red Sox bullpen, considered suspect by many, managed to bend but not break during the series--and that made all the difference.

Peeking out from the stats is the fact that both pitching staffs were having trouble with their control. Red Sox pitchers averaged 5.09 BB/9 during the series, which looks a lot more like 1949 than 2018. The Astros were better (four walks per 9 IP), but this is still well above the regular season MLB average.

Thursday, October 18, 2018


So, OK, this is not really a "post-season" snapshot. There are no stats on post-season bullpen performance in this post.

What we do have, however, is a meditation on the changing perspective on the bullpen and its strategic importance for success that reverts back to more straightforward stats in order to capture those changes.

No one needs to be reminded that relief pitching is undergoing a transformation--the Tampa Bay Rays have made sure of that. We can expect more relief innings over the next couple of years as other teams attempt to emulate their "opener/delayed-starter-in-relief" strategy that was seemingly such a success.

But the value modeling that sabermetrics has imposed upon the game doesn't see it that way. Those numbers suggest that relievers did less to help their teams win games in 2018 than was the case in the previous seasons. Those modeling stats presume a different reality than what people see when they watch an individual game. And they tell us, year in and year out, that relief pitching has a net negative value in the overall model. This season, relief pitching had its most negative overall value according to Wins Above Average than has been the case in nearly half a century.

Is this hard to believe? Not for some. We find it hard to imagine, however, that teams whose bullpens post similar ERAs over a season can have significantly different WAR values. Of course, ERA has been "proven" problematic at the individual pitcher level by the recent attempts to use batter vs. pitcher (BvP) stats the go-to measure; but individual pitchers are not the only measurement aspect that we need to define and evaluate.

In fact, with the increase in reliever innings, it actually becomes more important to develop better aggregate measures for overall team performance in this area. And part of that effort should be to more tightly relate it to actual wins and losses.

And that's what we can at least start to putting together these various measures in scatter chart relationships. The ERA+/WAA scatter correlation shows a lot of discrepancy in the -2.5 WAA range, with ERA+ values being all over the chart. Some high-achieving WAA teams are actually have sub-par ERA+ values.

How, then, is this any real advance over a ERA+/WPCT scatter correlation? While there are always teams who "beat" their WPCT projections based on their ERA+ (due to the fact that such teams give up extra runs in games already lost.

The solid correlation in the 90-110 ERA+ region with WPCT demonstrates that there's general set of principles that remain in operation in the mid-range of the distribution, but that it frays a bit at the extremes. That's a more natural set of relationships based on real-life game situations. It suggests that there's more meaning in reliever WPCT than has been claimed for the past twenty years.

And the game is changing in ways that will likely reinforce this. When we look at the final month of the 2018 season, we see several interesting aspects of how this is manifesting itself.

In September 2018, we can see that certain teams experienced "make-or-break" months with respect to the post-season in terms of bullpen performance. The table at left sorts relief pitching in descending order of ERA.

Looking at it, we can see how one team (the Brewers) clearly rode their bullpen performance into the post-season.

And we can see how two teams (the Cardinals and Diamondbacks) wound up falling short of playoff appearances due to the poor performance of their reliever in the final month. (The third team coded in green, the Mariners, were caught and passed earlier in the year by the A's, who rode their bullpen into the playoffs.)

The color coding here is of some interest. Seven of the teams with the best performance from their bullpens (seven of the twelve with better-than-average ERAs) wound up in the post-season. Three of the top four teams in September bullpen performance are still competing in the post-season at this time (Brewers, Dodgers, Astros--only the Red Sox had a subpar performance from their relievers in September, and they managed to keep a lid on things in enough of their appearances to generate more relief wins than losses).

Relief pitching is not broken out sufficiently in the otherwise overly-parsed situational data for us to know why the Braves could go 9-3 with a 5.05 ERA, but we can make an educated guess: their mop-up relievers in already lost games gave up a lot of runs. A team like the Indians (who suffered a virtually complete reversal in bullpen performance in 2018 after a fine season the year before) managed to blow leads at crucial moments, saddling themselves with losses, but they did not pitch poorly in already lost games.

What we can tell you is that the playoff teams in 2018 posted an aggregate 65-34 record in September games where decisions were picked up by relief pitchers. We'll let you decide if you think that is as meaningless as many still seem to think is the case.

Sunday, October 7, 2018


Ah, the September song. Is it a preview of "coming attractions" as regards offense?

Joe P., who felt the urge a couple months back to double down on the "take and rake" offense, would doubtless point to the fact that run scoring levels are still relatively robust (4.45 per game in 2018, and 4.44 in September) and dismiss the dip in batting average (BA) for the month (.243) as being meaningless. (After all, batting average is meaningless, n'est-ce pas? So long as isolated power (ISO) can remain at all-time highs, offense can remain "robust enough.")

But such is not going to be the case if one other factor continues to follow its trend line. The rise in strikeouts--more specifically, the rise in the percentage of strikeouts that occur in plate appearance where a batter has two strikes on him--will at some point have a cratering effect on batting average, which will domino in to on-base percentage (OBP) and slugging average (SLG).

Our chart at right shows the K-to-2-strike percentage as it's evolved from 1988 to 2018 (these are the only years where the play-by-play data is detailed enough to capture this info). As you can see, this percentage is slowly but inexorably on the rise and has risen by 30% over thirty years--with the fastest rate of gain occurring in the past decade after a long lull due to the "baked-in" effects of the offensive explosion.

Additionally, BA and tOPS+ values for two-strike situations have been decaying over this time frame. (The tOPS+ stat measures the OPS value of the two-strike PA against the overall OPS. This was close to fifty percent in 1988 and remained relatively constant throughout the explosion until 2009; now, however, that figure has moved down into the low forties. BA is declining along with it, with two-strike PAs reaching a new low this year (.173).

The direction of the trend lines means that the so-called "smart adjustment" that Joe P. touts (admirably defending the tenets of an increasingly senile sabermetrics) is pushing everything into perilous territory. Not only is the game becoming more two-dimensional offensively, but it's skating into a risky region where additional pitcher adjustments will bring BA down to levels seen in two months during 2018 (September: .243, June: .245) for the entire season.

Note that HR totals did recede this year (from the absurd 1.27 in 2017 back down to 1.15). But keep in mind that such levels have to at least be sustained in order to keep offense "robust enough." Pitching adjustments, in two forms--experiments with in-game pitcher usage, and analyses to counteract the "launch angle" phenomenon that was partially responsible for the HR spike--are beginning to make themselves felt. It's unlikely that hitters are going to adjust to such alterations by pitchers in a short period of time--leaving it highly likely that home runs will drop and strikeouts will continue to rise...

...Which will result in batting averages that look disturbingly similar to what we saw in the mid-to-late 1960s.

How far can HRs drop? That's harder to predict until we see more evidence of pitching staffs improving. In 2018, we had an unusually high number of really bad teams and really good teams. Several of the really bad teams barely improved their HR allowed rates, while the really good teams showed a higher rate of improvement. When such improvement becomes more uniform, it will begin to effect teams that managed to improve their HRs hit in 2018 and a more pronounced decline will set in.

As you can see in the final comparison chart for R, HR, and BB (each month in 2018 is compared with the R/G, HR/G and BB/G from its corresponding month in 2017), the decline here was consistent but relatively uniform. (BB/G has a frequent pattern of being higher in April and September, due to weather and/or roster you can see, June was the biggest outlier, but that's because the HR rate was simply insane in June 2017 and it drove R/G up toward "offensive explosion" levels.)

A uniform year, such as was the case in 2018, is often followed by a more jagged change in the following years.

Next year we'll run these numbers for two parallel years, showing the months of 2019 against their analogous months for 2018 and 2017. And we'll be back a bit later this month with a look at big swings in BA, OBP and SLG at the league level over the history of baseball. Stay tuned...

Friday, August 31, 2018


Too much planning and writing for various manifestations of French film noir--and, frankly, the more mainstream versions of what we like to do here at BBB are kinda sorta covered in the sedimented river sludge of content at, so we await the conclusion of our book on French noir and our two upcoming festivals in Los Angeles and San Francisco to actually make a reasonable effort to cover baseball in something resembling our old, er, "panache."

But if you happen to find yourself in LA or SF on the dates specified in our accompanying illustrations, however, do come see us--might just talk baseball for (kindly pardon the pun...) a "change of pace."

Meanwhile, in the land of homeostatic homeritis, the August numbers are within moments of being final and official. Warmer weather propped batting average up a bit (.253), and HR/G rose slightly as compared with July (1.19 vs. 1.15), but a decline in walks (2.99/game as opposed to 3.26 in July) contributed to a slight decline in run scoring (4.46 per team per game as opposed to 4.7 for July).

When we say homeostatic, we mean it: the HR/G ratios for this year might be the most consistent across the months as any we've seen: 1.09 in April, 1.17 in May, 1.16 in June, 1.15 in July, 1.19 in August.

The last year the STDEV for HR/G by month was this low was in 2010. Such lack of volatility is actually pretty rare. The least volatile year for HR/G fluctuation was, of all years, the strike season in 1981.

Here is the vital sign comp chart updated through August 30 [at right], measured in percentage change from the 2018 month in question to its 2017 counterpart.

In case you're wondering, September has tended to produce HR/G at a 5% lower rate than the overall yearly average over the 2000-2017 time frame. That would suggest that the September HR/G rate will clock in at around 1.09.

Thursday, August 2, 2018


So July is in the books, and offense went up--but not because HRs returned to 2017 levels. No, it came about due to a rise in BA and OBP, with HR levels staying steady. The summary is provided at right.

Of course, HRs are still near historical highs (leaving the 2017 spike unto itself), so this "new normal" has to be taken with the same box of salt needed when we contemplate the continuing specter of the Orange Menace, but that's another story (and comparison) for another time.

More interestingly, we spent what little spare time we have right now investigating the effects of temperature on 2018 offense. Our approach is more statistically inclusive than elsewhere, of course (we continue to consider "shape" in how offense is created), and as a result there are some nuances here that bear further examination via additional breakouts in prior years.

As you might expect from what you've read elsewhere on the topic, there is generally a linear relationship between run scoring and temperature at game time. There are nuances, however--and these seem to have been overlooked. First, here's the full data set:

Note that we break up the categories into five-degree intervals (a different approach than everyone else). And when we do that we get something a bit different than a strictly linear result vis-a-vis run scoring and temperature.

Run scoring (at least in 2018) is actually higher in the coldest games (59 degrees or lower) than is the case for all games in the various temperature ranges between 60-84. It's only when we get to 85 degrees or higher than the game reverts to the scoring levels that prevailed during the long offensive explosion (1993-2008).

Note the HR/G is uniform at 85+ degrees, with a intermediate plateau in the low 80s, followed by a virtually uniform set results from 65-79. This is the so-called "smart game" referenced by Joe P., where homers prop up an offense that would otherwise be remarkably similar to what we saw in the 1963-72 era. (We'll get around to formally debunking Joe's characterization in subsequent posts.)

Note the odd fluctuations in BB/G--but pay especial attention to the extremes. Hot weather produces highest BA, ISO, and HR/G--it also produces more walks, which are likely due to pitchers being extremely careful in the increased number of men-on-base situations they face in these games. Cold weather suppresses (to an extent, at least) HR/G, but something about the weather conditions has an effect on BB/G, which shoots up to levels that look more like the late 40s "walk spike" phenomenon.

As a result, OBP is higher in these games than at any time other than the games played in 85+ degree conditions. And this counterintuitive shape combination produces more R/G than the so-called "intelligent" process of what's been called "take and rake."

It will be interesting to generate this exact breakout for 2017, for 2000 (height of the offensive explosion), 1992 (last year prior to the explosion), 1987 (first mega-HR year), and some other selected years in the past. We need to see if the "evolving" strategy of "take and rake" has caused changes in the relationship between run scoring and temperature.

From the data above, however, we can draw one tentative conclusion. Someone in baseball needs to figure out how to buck the temperature trend: an enterprising team (let's say the Rays...) should investigate all of the ways in which they can counteract the effects of hot weather. Is it a humidor, or is it something more strategically comprehensive in terms of how pitchers approach these games? And might it this be somehow related to the Rays' recent antithetical deployment of pitchers in a game? Perhaps a still-TBD combination of all the above?

While you contemplate what those adjustments might be, we'll look for some more spare time to run the additional breakouts...stay tuned.

Monday, July 23, 2018


Ortiz:"You're batting leadoff? I
thought you were the batboy!!"
Mookie Betts is having a great season, and that's not just great news for Red Sox fans. Mookie is not a "big man"--he's only 5'9", 180lbs. It has become extremely unusual in recent times for players of such (relatively) diminutive stature to have such a dominant offensive profile. So far, however, Mookie is flying high with a 193 OPS+ and is very much in the MVP discussion despite missing the better part of three weeks due to injury.

It turns out that Mookie is one of nine hitters who are 5'10" or shorter having at least robust offensive years (defined as a 120+ adjusted OPS) in 2018.

Now, nine may not sound like a lot--and it's not. But it's a helluva lot better than the numbers we see for "smallfry" in the recent past. Our table below shows that in recent years, hard-hitting little guys were a seriously endangered species.

Clearly two forces have been at work historically to chip away at the short-statured player. First, the general trend that people are getting taller. Second, the pervasive typecasting of small players as bereft of power, and a selection bias that favored middle infielders who had little or no chance of developing it.

What may be pushing things the other way is the perception that all players should possess a higher degree of power (measurable in ISO), opening up the search for short players capable of hitting for power. Of course, OPS+ is not driven only by ISO or SLG--but having that in addition to a solid OBP supported by a higher-than-average BA might just be the combination that has produced a sudden "bumper crop" of good-hitting smallfry.

A decade ago, neo-sabes had predicted extinction for such players--and the numbers you see in the 2000-09 time frame would certainly have made such a prediction seem plausible. But we see here at the least the possibility of a counter-trend. Remember these are hitters whose overall offensive profile (BA, OBP, and SLG) is lifting them to prominence--most of them are not hulking low-average power hitters relying on ISO to boost their SLG. There's a chance that some of these smallfry (read: big little men) will be Hall of Famers one which we say, "Hallelujah!".

Some think Mookie is the second coming of Willie Mays. Time will tell if he really has enough power to make that comparison more plausible, but size-wise, personality-wise, speed-and-defense-wise he's the same breath of fresh air that we got when the Say Hey Kid was in the prime of his golden youth. We dug out our YEPS (Year-End Projection System) spreadsheet to see what it projected for Mookie at season's end: as one might expect, it projects a dropoff over the next two months, but the overall projection is still for a season with an OPS+ in the 170 range.

That is a good first step toward being a Mays-like player.

Here are the nine "smallfry" posting 120+ OPS+ seasons thus far in 2018--if you're a "smallfry" yourself, light a candle in the window for these guys. It would be great if all nine stayed in the 120+ zone...

Ozzie Albies, Jose Altuve, Andrew Benintendi, Betts, Khris Davis, Eddie Escobar, Scooter Gennett, Jose Ramirez, Jean Segura

Saturday, July 21, 2018


Here's the latest: run scoring and hitting in general is up, but HRs are down--just the first piece of information refuting Joe P.'s  recent "defense" of what a growing cadre of disillusioned statheads are calling the "take and rake" philosophy.

We'll get back to undressing Joe's argument at a later date, but suffice it to say that it's OBP that drives offense. And there are two ways to increase OBP--draw more walks or make more hits. That's what's happening in July. Run scoring is at its highest rate because BA and OBP have recovered, while HRs are still down.

It's a sign that a sizable number of hitters are setting aside the "all or nothing" approach after they watched their collective BA push itself into 1960s levels for nearly six weeks during May-June.

It's also a sign that there's a something of a starting pitcher crisis occurring this month--but not in terms of HRs allowed. No, the symptom seems to be more basic--and sabermetrically inconvenient. It appears (as shown in the table at left) that many teams' starters have suddenly become more hittable. Batting average is up, and it is strongly correlated with the often sharp rise in starting pitcher ERA thus far in July.

Sixteen teams have their starters posting July ERAs at least ten percent higher than the overall team ERA. Nineteen teams have starting pitchers who are generally more hittable in July than they've been over the course of the season to date.

(As is likely the case with most of you, we don't quite know what to do with the Tampa Bay data, since their starters are still "unto themselves." But what's clear is that the Rays are not giving up very many HRs in July, and that's how they've lowered their starters' ERA even though they are giving up more hits.) More evidence of a slow but steady adjustment from the single-minded "take and rake."

Thursday, July 19, 2018


QMAX and FIP are odd stepbrothers, working overlapping areas of analysis from diametrically opposed rationales. FIP's strength came from two things:

1) a huge push from the "fielding-independent" fad that took over sabermetrics, pushing it headlong into its first and most intense "neo" phase (prior to its series of calcifications that have left analysis marooned in a cul-de-sac);

2) the ability to be calculated quickly and easily without recourse to granular data.

QMAX is a better tool for starting pitchers (it was never meant to address relievers), but: it began with a counterintuitive perspective that grated on the 1990s community--it refused (still does, actually) to work with runs and run adjustment to generate its suite of stats, including the base measures (hit and walk prevention values, and a probabilistic QMAX winning percentage--abbreviated QWP, which if we say so ourselves is witty as hell--or at least Hieronymous Bosch's depiction of hell, a place where selected neo-sabes (they know who they are..) and a certain Orange Menace may yet spend eternity.

It was hampered by the fact that you had to calculate and adjust the grades by individual game, and while a math whiz like Sean Forman could automate that (and did, way back in the primordial ooze of what became Forman et fils--yeah, yeah:, it could not be done by the so-called "littery man" of baseball analysis.

That made QMAX difficult to transmit to the masses--not that said masses were exactly clamoring for it, mind you.

But now...that's changed. One evening after watching Fille du Diable, the French noir we'll be showing in San Francisco a week from tonight (featuring "Goth girl" Andrée Clément in a simply astonishing performance), we had something akin to an epileptic seizure that lead to a sweaty breakthrough regarding how to calculate QMAX with just basic adjustments of mainstream rate stats. (Or did the sweaty breakthrough lead to the seizure? As the soothsayer sayeth: pick a card, any card...)

So here's how it works. (We provide some pitching leaders over the past two months, with their stats from the May 15-July 15 snapshot, again courtesy of David Pinto's Day-by-Day database.) Our first table (above) shows the basic data for the eleven pitchers with the best QWPs for the time frame in question. We see ERA, K/9, BB/9, and David's concoction, Cy Young Points (a fun measure, which we abbreviate CYP, which--of course--rhymes with QWP).

We added a rate stat version for David's stat just to "double down" on the fun (and won't we all be glad when we never hear that term again...) which shows that while Trevor Bauer had a great run over the past couple months according to CYP, he's not the leader in CYP/9 (contrary to popular belief, CYP/9 is not a sci-fi "binge" series on the Android Channel). That distinction belongs to the mysterious lefty Blake Snell, the last starter standing in Tampa Bay.

QMAX will show up in the next table, but if you can intuit that it will show us these same pitchers in the same order as presented above, then you'll know that Chris Sale has the best QWP over the past two months, which is why he's passed Justin Verlander as the #1 starter in the AL.  So QMAX will pass the "smell test" of those stat-adjusting ideologues who trash ERA as almost as useless as batting average--though this is not quite a ringing endorsement of anything. What's clear is that ERA is transitory, particularly in smaller sample sizes (the ones that neo-sabes rail against until they start using them for their own purposes), and our hope is that a Quick & Dirty QMAX (...jeez, Malcolm, just now working in that acronym? talk about your buried ledes...) will provide a more robust way of looking at the performance value of starters, particularly in sub-season snippets.

So here's the rest of the stats involved in how we get to an "indicated QMAX" (best estimate without applying the grading method manually to each start) score. We need to adjust H/9 to the QMAX "S" value (hit prevention). Our "bathtub gin regression" shows that .44 of the H/9 is a good first cut at this base value. That value is shown in the Q/Si column. (Remember: the lower, the better).

The adjustment to Q/Si that's needed is to account for extra-base hits and HRs. As was posited by the perpetrators of FIP, the distribution of doubles and triples is uniform enough to set aside, leaving a HR adjustment for QMAX in order to have the "S" value reflect as much of the "total base" effect in "hit prevention" as possible. We get that together by two relative measures of HRs allowed by pitchers: the first, the straight HR/9 rate; the second, HR TB as a function of overall TB allowed. These two modify each other and can be expressed in a formula with a multiplier that then adjusts upward for the "total base" effect, giving us a more realistic QMAX "S" score (the left-most column in green, the one called QSihr (indicated QMAX adjusted for homers).

As you can see, this doesn't make much difference for some hurlers (Sale, Aaron Nola, Jacob deGrom, and Bauer), but it does alter the values for those with HR issues (in this two-month snapshot, that's be Justin Verlander, Mike Foltynewicz, Corey Kluber). Their adjusted "S" scores really do adjust upward.

With adjusted "S" in place, we can perform an analogous procedure for the "walk prevention" component (QMAX "C") which adjusts for a couple of minor idiosyncracies that the relationship of the matrix approach to grading "walk prevention" and the range of BB/9 sometimes conspire to distort...and when we do that, we get a good approximation of what QMAX "C" would look like if it were calculated by hand. (The process is similar to curve-fitting, except we're doing it--as usual--in the bathtub.)

Finally, we can generate QWPs for the separate "S" and "C" functions, and create a formula to blend them into a final aggregate, indicated, Q&D QWP (also sometimes referred to as the quicker picker-upper...though we think most of those so inclined will prefer the cotton-pickin' picker-uppers shown at right).

What we see above is that over the past two months, Chris Sale is sailing along, Ross Stripling has done a reasonably passable impersonation of Greg Maddux circa 1997, Blake Snell has been the "power precipice" starter par excellence, and Aaron Nola has become the ace of the Phillies. It's wonderful to be able to do Q&D QMAX under the supervision of a partially house-trained dachshund and a semi-monitored regimen of directed medication (see above), and--despite the levity--this is pretty damn cool after all these years of doing it by hand. Summertime, and the QMAX is easy: really, now, what more could one ask for--except for "regime change," that is?

POSTSCRIPT: A reader suggested that it might be useful to provide an example of how close the Q&D QMAX is to the official method. In other words, how close does quick-and-dirty do?

That answer, to be sufficient, would require a lot more work than it's possible to do (at least for awhile). But we can at least look at an example that provided the most challenging amount of work to bring the QMAX matrix mechanism into sync with more conventional statistical distributions.

The challenge lies in the possibility of distortion between the "C" value and its grading process within the QMAX matrix with the more straightforward BB/9 stat. Adjusting BB/9 for the QMAX structure can get tricky in extreme cases (see, for example, the QMAX discussion of Tommy Byrne). Even someone whose walk totals exceed their innings pitched will never approach the QMAX maximum value, so we either need a separate "actuarial table" that cross-references these values or we have to develop a conversion formula that replaces the need for such a table.

Fortunately, we were able to do the latter, and here you can see the results of that when we apply it to Blake Snell, 2018's poster boy for high BB/9 averages. (It's actually not THAT high--4.2 over his eleven starts from May 15-July 12--but an ordinary conversion would produce a QMAX "C" value higher than the BB/9, which can only happen on the opposite end of the spectrum.)

Snell has become a "power precipice"
pitcher in 2018, usually characterized by
having a lower "S" score than "C" score.
The end goal, of course, is to get the QPW value (QMAX Winning Percentage) as calculated by the Q&D version as close to the hand-calculated value in the start-by-start method. In Blake Snell's case, we find that his Q&D QWP is .640.

What's the hand-calculated QWP? It's .639.

Now, mind you, not every one of these is going to be that close--not hardly. But the overall deviation in the Q&D QWP values for the ninety-one pitchers with at least 50 IP during the May 15-July 15 time frame is 2.4%.

That's encouraging enough to be able to present more QMAX info using the Q&D expect to see more in-season data using it in the future.

Thursday, July 5, 2018


Offense and homers spiked over the first three days of July, but things cooled down somewhat on the Fourth...perhaps the hitters didn't want to upstage the fireworks.

After four days in July, runs and HR's are now behind last year's pace, while BB's are running ever so slightly ahead.

Of course, when we say behind last year's pace, we need to remember that the HR pace in July 2017 (1.25 per game) was the sixth highest monthly total in major league history. The current July 2018 pace for HR/G would rank tenth.

A stretch of especially warm weather is supposed to work its way across the country this week--we'll see how it affects offense. As a rule, the higher the temperature, the more runs and HRs. Stay tuned...

Wednesday, July 4, 2018


In the tiny-bubble world of baseball innovation, the Tampa Bay Rays continue to give us much. But even Kevin Cash may have gone too far last night when extra-inning desperation forced the Rays' manager to turn our favorite avoirdupois-challenged southpaw, Vidal Nuño, into a two-way player.

Nuño responded to this with the type of underdog intensity that one would expect from someone who is simultaneously marginal and overfed. With the Rays playing an interleague game in Miami, they were already letting pitchers bat; by the fourteenth inning, Cash was out of double switches--so Nuño found himself in the batter's box.

And before you could say boo, Nuño flared one down the left-field line that landed fair and rolled toward the stands in foul territory. Marlins LF Derek Dietrich got to the ball in a hurry and fired to second base--where Nuño, valiantly impersonating a baserunner, was trying to stretch his single into a double. (Vidal was 2-for-26 lifetime when the plate appearance had begun.) The result is telegraphed in our video capture...

So into the sixteenth inning we go, and the Rays have taken the lead again when it is once again Nuño's slot in the batting order. Hoping to save his bullpen, Cash lets him hit again. The pitch from Brett Graves is low and over the plate--right in Vidal's, er, "wheelhouse"--and the portly one uses his modified "sand wedge" swing to slap the ball into the right-field corner.

This one drives in a run, and looks certain to be Nuño's first major-league extra-base hit, but as he "motors" down the first base line, he comes up lame, clutching at his right hamstring. He's stopped at first by the injury and has to be removed from the game.

The Rays go on to win, and Nuño gets his third win of the year (remember, he was 5-21 lifetime when recalled from the minors late in May)--but earlier this morning he was placed on the disabled list.

It's definitely a "story of my life" scenario for Vidal, who'd frankly been startlingly stellar (3-0, 1.50 ERA) as a cog in the Rays' fog-shrouded machine since his return from oblivion. Ironic, of course, that he'd get injured as a hitter, as if some kind of cosmic compensation was needed for having had the audacity to double his lifetime hit total in the space of two plate appearances...

So the sun has set on Nuño's empire, at least for the foreseeable future.

Sunday, July 1, 2018


June's games and their associated data are complete: the early swoon abated in the second half of the month, keeping it essentially on track with the R/G, HR/G and BB/G produced in May. The comparison of June 2018 with June 2017 still remains stark, however, as our differential percentage chart indicates.

Last June, homers were hit at the most frequent rate of any month in baseball history (1.35 per team per game) and run scoring shot up to 4.91 per game. The downturn in June 2018 finished in double digits (4.33 R/G, 1.16 HR/G).

Another way to track this data is to pick a "base month" and measure the monthly deviations from it that occur over time. There are actually two ways to do this--one where you track the changes month-by-month, using the prior month as the basis for the calculation, and other where you measure every month against the "base month" and get a cumulative rate of change.

Both are of sufficient interest to display here. First, the month-by-month changes [at right]. The "base month" we're using here in September 2017, the "cool down" month in last year's long homer siege (4.58 R/G, 1.19 HR/G, 3.25 BB/G). We can then see that April 2018 hit less HRs but drew more walks: the net result was a slight downturn in run scoring. May gained in HR/G over April, but pitchers were much stingier in terms of walks, which caused another downturn in R/G. And our comments comparing May 2018 to its successor month can now be seen in percentage terms, where runs went up slightly despite small declines in HR/G and BB/G.

We get a different view of this when we redirect the comparison to show us the differential of each month from the September 2017 "base month." As you'd expect, the April 2018 data is the same (April is compared to September 2017 in each method).

But in May we see the "cumulative" effect kicking in. We can see that relative to September 2017, May 2018 shows a larger cumulative drop in R/G, brought on by the flip-flops in HR/G and BB/G that show a cumulative decline in each of these measures. The June data shows how this data starts to converge, as the combined cumulative downturn in HR/G and BB/G is now about 80% of the decline in R/G.

What can we expect in July? There's often a decline in HR/G and R/G from the peaks achieved in the previous month; last year was no exception. It's possible that the protracted batting average swoon that occurred in the first half of June might have righted itself, however, and we may see some modest gains in July. Stay tuned...

Friday, June 29, 2018


Third time's the charm, even if some (if not most) of what's written here leans heavily toward the charmless. We come to enshrine (or cast into limbo) the "as if real" career of one Brock Hanke, the architect and utility player of the San Antonio Trotters--a living, breathing anomaly in his own write.

And after having looked at the overall data (#1) and a semi-traditional evaluation (#2), we now subject him to the third degree--a disqusition according to WAR (Wins Above Replacement).

Most everyone reading here knows of WAR; a large subset of you will register misgivings for a method that steps away from direct league-relative measurement, that oddly mixes defensive adjustments into purely offensive statistical measures; a system that purports to work via a simple additive function set but breaks from this approach in creating its final values.

It is truly a case of misbegotten modeling--but in a world where the mysticism of money continues to provide a suppressive weltanschauung for the theories that hide how things really work, it has become a pillar of salt disguised as a pillar of orthodoxy. It is the only statistical measure that was subject to a "summit meeting" to hammer out a negotiated compromise for "replacement value," a concept already steeped in money mysticism to a point of no return.

WAR's status is currently at a point analogous to what we see in The Wizard of Oz when Dorothy and her pals first visit the Emerald City; the bell and whistles they (and we) encounter are loud and intimidating, and make unreasonable demands on those who simply wish to remedy a few simple deficiencies in their lives/worldviews/thinking processes. We're not quite at the point where we can reveal the mathematical humbug (in the way that the Great Oz was exposed), but as with what we face in a distinctly un-Oz-like present-day America, we'd better brace ourselves for an avalanche of bluster in the wee hours before the truth will suddenly rise (in a long-delayed dawn).

All of which is to say that we had to create a version of WAR for Brock Hanke's career stats based on a bathtub-gin kluge, using the relationship existing between WAR values as calculated for players with similar offensive profiles with the Batting Runs values generated back in the "classical sabermetric age" by Pete Palmer and Gary Gillette. Those ratios provided us with the best estimate of what Hanke's WAR values would look like [table at right].

Note that these are the offensive values only. We did not keep track of defensive data in the games we played, occurring as they did in the pre-personal computer age. As he would himself cheerfully admit, Hanke was not much of a defender: the Trotters tried him out at third base, which did not make for a pretty picture (hey, the man is left-handed!). After a switch to catcher in mid-'72, he settled in at first base the following year, and would play 85% of his games there from that point onward.

At this point we should mention the "trad" stats you'd have seen in the previous two posts: .321 lifetime BA, 3023 H, 669 2B, 204 HR, 1685 RBI. On a mighty dynastic team with flashier players, Hanke was a hidden star, a solid OBP and RBI man. And the OWAR values, when added up, seem to confirm the notion that his career is of Hall of Fame quality.

But it's the "second order" usage of WAR--as a measure of "peak"--that will turn into the "valley of death" for Hanke at the hands of analysts. Systems devised by hack neo-sabes like Jay Jaffe, which simplistically try to split the difference between two inchoate and inadequate representations of offensive value, would penalize Hanke for not having a "peak" commensurate with his "career" value. (Hanke's "seven-year peak" in WAR is only 32--which, when utilized as part of the simple-minded averaging that is the basis of Jaffe's "system," leaves him with a "compromise value" of 58 WAR--which would leave him on the outside looking in as regards Cooperstown.)

Certainly there are better ways to use WAR than Jaffe and others have done: heck, they might even try converting it into a rate stat. When we do that, Hanke's value in the first baseman class gets an interesting boost. The average Hall of Fame first baseman puts up just under 5 WAR per year (using 660 plate appearances as the basis). That includes a few players (Jim Bottomley, George "High Pockets" Kelly) who are deficient both in terms of WAR/yr rate and career length.

Hanke's career length (25 seasons, 3200+ games, nearly 11,000 plate appearances despite an increasing amount of part-time play over his final decade) is not an issue. And his 4.99 WAR/660 plate appearances is right in the pocket for Hall of Fame first basemen.

But Jaffe's averaging method arbitrarily lops off 35% of Hanke's offensive value as measured in the rate stat. It's a bit less Draconian in the counting stat version, chopping off "only" 30% of the original year-by-year WAR total.

WAR itself would invariably adjust Hanke downward from his batting runs-derived value in the context of its opaque "methodology." And a generation of armchair analysts would prattle on about "complete players" in their hypertrophied mental-gymnastic assemblage of the Hall of Fame.

They would focus on what he could not do (hit HRs, run the bases, field like an All-Star) and find ways to minimize what he could do (hit, hit doubles, drive in runs at a rate elevated from the statistical norm, exceed his overall hitting rate stats as a pinch-hitter) in order to rally around the stultifying orthodoxy they wish to claim as "outside the box" thinking.

EPILOG: Of course, the question is whether a player with Hanke's offensive profile and specific career path could actually exist. Baseball and WAR, WAR and baseball now go hand-in-hand to curtail this possibility, boiling the game down increasingly--inexorably--to isolated power. The approach they are taking is slowly--inexorably--leading us toward a version of the game where there is zero chance that such a player could ever exist.
"Personally," the former Charlie O. the Mule "wrote" in his autobiography,
"the guy should be in the Hall simply for having the nutty idea that I could play
baseball in the first place."

And that's a shame, because as a player, Hanke is incredibly good for the game. He makes possible a type of human connection that the average fan needs in order to have sufficient choice in role models. You don't have to fit into an "elite" vision to still be excellent: there are many ways to be valuable, productive, inspirational. And you can wind up in the Hall of Fame because you were famous for not being the best, but something uniquely valuable.

That's an evaluation that WAR can never make--and that's why Brock Hanke (the "mythical" one and the "real" one--who's to know which is which?) is the type of figure that history (and this moment in history...) really needs to discover and embrace.

Tuesday, June 26, 2018


Taking the standard two-month snapshot, and as always with thanks to David Pinto's Day-by-Day database, we present the best hitters in baseball over the past two months as measured by OPS:

That's 34 hitters with a .900 or better OPS from April 25-June 24. The Reds have three hitters with .950+ OPS performances over this period (Joey Votto, Scooter Gennett and Eugenio Suarez), as do the Red Sox (J. D. Martinez, Mookie Betts, Andrew Benintendi). The Dodgers have three guys over .925 (Max Muncy, Joc Pederson, and Yasiel Puig).

The Indians have two hitters (Jose Ramirez and Francisco Lindor) with two-month OPS values over 1.000. A player they waived last year (Jesus Aguilar) has been a power monger for the Brewers for the past two months.

Did you ever expect to see Daniel Descalso on this list?

Not a lot of folks with really high walk totals here--Mike Trout, Votto, Shin-Soo Choo, and the Dodgers' latest turnaround hitter Muncy.

Here are some well-known names who've been struggling in one form or another for the past couple months:

Harper isn't even walking at his usual level since his three-week hot start at the beginning of the season. The NL may have adjusted to Hoskins; likewise could be the case for Sanchez. Perez rode the HR boost last year, and his continued focus in that direction is now cratering his BA. Braun's ongoing decline has been exacerbated by injuries, which are also the primary reason for Fowler's struggles this year. It is hard to understand why the Orioles are bothering to give Davis so much playing time...

Sunday, June 24, 2018


So here again we pick up the saga of the one and only Brock Hanke, rogue owner of Ye Olde San Antonio Trotters--and, if the numbers below are taken "as if real." a pretty nifty hitter to boot. The question we left you with last time: are these career numbers (repeated below, with slight corrections in the OPS column...) the stuff of Cooperstown?

A wrinkle that we must consider in such an evaluation is the time frame in which Hanke played, and the exact year in which he would have become eligible for the Hall. Hanging up his cleats and cashing in his franchise for whereabouts unknown at the end of 1995, he'd appear on the Hall of Fame for the first time in 2001. We would not expect him to come close to induction on that first ballot, but his basic traditional stats (3000+ hits, nearly 1700 RBI, .321 BA, and .414 OBP) would certainly keep him from falling off the ballot the first time around.

In 2001, Forman et fils (Baseball Reference) was in its infancy, and the WAR method was not nearly so ingrained in the brain stems of those who were fulminating in the post-Bill James era of statistical systems. (To the detriment of much and many, however, this would soon change.) 2001 brought us 9/11 and the beginning of a cascading quagmire, and baseball was just about to blow up too, thanks to Barry Bonds hitting 73 HRs and cementing the steroid witch hunt (yes, there really have been witch hunts in America, but they don't involve the Orange Menace, who is the biggest loud foul in the nation's history).

Hanke, then, would be only as controversial as the Trotters had managed to become within that alternative scenario, but he'd also be seen as a guy who'd never been close to being the best player on his team. (Not with that Mule the Trotters stole away from Charlie Finley--but that's another tall tale.)

Our job here is to look at various "traditional" (actually, "non-technical") stats--those that don't require complicated formulae and modeling assumptions--in conducting a preliminary evaluation of Hanke's Hall of Fame case. (We'll get to the "technical stats" in Part 3.)

So--hits. 3000 hits has been a bellwether stat for Hall of Famers ever since Cooperstown was invented. Only three players with 3000+ hits are likely not to be inducted in the Hall, at least for a good while: Pete Rose, Alex Rodriguez, and Rafael Palmeiro. We can expect the others (Derek Jeter, Adrian Beltre, Ichiro Suzuki, and Albert Pujols) to get the nod rather quickly once they are eligible for induction.

And, as you can see, down there in 29th place on this list, is Hanke.

Now it's true that it took him longer than anyone on the list to reach the 3000 hit plateau (twenty-five years), and for some that might raise a red (or possibly just a pink) flag. But that league-relative on-base plus slugging (OPS+, a stat just on this side of the "non-technical" least in our book) is (as noted earlier) quite robust. We have to remember that Hanke played mostly in a low-to-average run scoring era (the seventies and eighties). So the quality of his hitting is not subject to doubt.

Next: doubles. While Hanke was not a power hitter per se (he wound up with just over 200 HRs, but this averages out to only about nine per year due to his egregious longevity), he was exceptionally proficient with the two-bagger. He was what we might term a "precision gap hitter," with sufficient bat control to foil whatever outfield positioning was deployed against him. Even late in his career, the percentage of his total hits that went for doubles remained consistently around 22%, a very high percentage; his lifetime D/H ratio ranks 21st all-time.

On the lifetime doubles leaders chart, then, it's not surprising to find Hanke (with his 669 lifetime two-baggers) residing in the #5 slot on the list.

Next: runs batted in. Here's a stat that gets no respect any more: the arguments have been talked through until the listener is bluer in the face than those doing the take-down spiel.

All that said, however, you can see that the lifetime RBI leaders list contains a lot of Hall of Famers. Bonds, Rodriguez, Palmeiro and probably Manny Ramirez are going to remain "tainted" for some time to come, but the chart clearly shows us that hitters who can amass 1600+ RBI are, by and large, going to wind up in Cooperstown.

Again, there's the fact that Hanke took those twenty-five long years to compile his 1685 RBI; he has, as a quick look back at his stat line will show, only one season (1987) where he actually managed to amass 100+ RBI in a season.

But something else to consider is that Hanke's lifetime RBI/TB ratio is .387. Among hitters with 1600+ RBI, that ranks fifth all-time. And which hitters are on either side of Hanke's RBI/TB ratio? Why, Jimmie Foxx (.388) and Babe Ruth (.382), that's who. And those two hitters were able to generate a lot of RBI via HRs--something that Hanke mostly didn't do.

A small but notable aspect of the above stems from the fact that Hanke became a dangerous pinch-hitter in the latter stages of his career. (The "alt-universe" stats indicate that he was 6-for-13 as a pinch-hitter in his rookie season, and just kept delivering in the pinch for the next two dozen years. While he was never a pinch-hit specialist like Manny Mota, Jose Morales or Jerry Lynch, he did amass over 500 lifetime PAs as a pinch-hitter, hitting a sensational .353 and driving in more runs (150) than his total number of pinch hits (146). It's only a footnote in his career, but it's a boisterous one.

Next: on-base percentage. Here's a stat that can't be overlooked in terms of its correlation to offensive value. Our table at left shows the 35 hitters with more than 7000 lifetime plate appearances who compiled a .400+ OBP.

And sliding in at #20 on the list is Hanke, with .414. Of the 19 players ahead of him, 16 are in the Hall of Fame--and one of those not there is Bonds, still suffering from "the taint." (It also shows us that OBP is the key reason why Edgar Martinez is so tantalizingly close to being inducted, and appears to have a solid chance to make it in the 2019 voting. It's also quite likely that Todd Helton will eventually make it, though it might be via the Vets Committee.)

And, finally: adjusted OPS (OPS+). We've shown you Hanke's lifetime OPS+ of 143. What you haven't seen (yet) is where that ranks amongst hitters with at least 7000 PAs, and how many of them are in Cooperstown.

Hanke ranks 39th on the lifetime OPS+ list. Of the 38 players who are ahead of him on this chart (at right), 30 of them are in the Hall. The only exceptions are Bonds, Mark McGwire (both "tainted"), Dick Allen (he's listed in the dictionary as a synonym of "star-crossed"), Ramirez (likely "tainted"), Pujols and Miguel Cabrera (still active), Martinez, and Lance Berkman (most likely too short a career to make the cut).

Underneath him, the hitters with 140-142 OPS+ are thirteen in number. Eight of these are in the Hall, while four of the five who aren't are David Ortiz, Larry Walker, A-Rod, and Sheffield. (Frank Howard is the fifth, and the one most likely to remain on the outside looking in.)

SO...the prima facie case for Hanke is actually rather strong. He's weak on black ink and grey ink, but key counting and rate stats place him among the elite. In 2001, he might well have gotten 40-45% of the vote from the BBWAA.

But--of course--in our "real" world, we have WAR. And while that has yet to become the method of "denying due process" to all other statistical formulations, its proponents--like the Orange Menace--are hard at work trying to do so. In order to bring Mohammed to the mountain, we're going to have to walk through the valley of death and confront WAR.

Which is just what we'll do next time. Stay tuned...

Saturday, June 23, 2018


Heated-up weather and games scheduled in hitters' parks this past week (Coors, Fenway) bumped up hitting and run scoring a bit, but with eight days left in June, overall BA for the month is still in a range to be among the lowest in the history of the game (.243). Just for reference, the lowest monthly BA for June is .239, set in (you guessed it) 1968.

While runs and hits went up, homers stayed steady at a pace about 15% below last June. Of course that is still near the top of such HR/G measures in baseball history.

Walks made a comeback in the past week, but the overall rate for June is now just about on par with May, and doesn't seem to have any unusual characteristics at this time.

Friday, June 22, 2018


Pretend for just a moment that it's twenty years ago. Bill Clinton is President; Donald Trump is a real estate buffoon. The vampires of the Republican Party have not yet found the elixir that permits their "undead" to operate darkly in the light of day. And there is no Forman et fils (Baseball Reference, for those who've stumbled in here for the first time) or Phangrafs--worse yet, no David Pinto.

That means you're reading your baseball stats (if you were wonky enough to do so) in a thick volume entitled Total Baseball. And if your wonkiness extended into an alternative universe (little would we know that we'd really be needing one twenty years later...) you'd have a copy of that doorstop with a series of entries in TB's statistical reference section that told a different version of baseball history from 1971 on.

That would be the book with several odd-sounding franchises--the most notable (if not the most notorious) being the San Antonio Trotters. In 1998, the Trotters had been dissolved, disbanded, and dumped in the same place that, back here in the present day, one can only hope will be the not-too-distant resting place of Le Anti-Grand Orange; but what they did to baseball in the previous quarter-century was both beyond belief and beyond the pale.

Perhaps the chief architect of this meta-tectonic travesty was one Brock Hanke, who took a deck of cards one late-winter evening in 1971 and gave Robert Coover a serious run for his money. ("Dice are nice," Hanke proclaimed, "but I can knock the earth off its axis with this house of cards.") The rabbit hole that Hanke opened up at the feet of yours truly and a rotating cadre of unmentionables would soon invoke a dynasty so gloriously odious, so superciliously subversive, so patently absurd that it could only fold back on the funhouse image of America that would all too soon turn into a proto-fascist quagmire.

Hanke had only two saving graces in the midst of this mishegoss: first, there were no emails with which to taint the tattered remnant of his mortal being; second, by virtue of being the first playing owner of a baseball team since 1890 he was able to secure a semi-permanent roster slot for himself on the Trotters, where he slowly and painstakingly compiled a set of statistics like no other player before or since.

And so, if you blinked backwards, or ingested some mushrooms with extra mischievous "magic," you'd suddenly see a set of statistics in Total Baseball like those displayed in the table (above right). With league-relative stats at their zenith of usage (prior to the deadening era of WAR...), we see that Hanke, while clearly a curious specimen, is also undeniably a productive curiosity, what with his 143 OPS+.

The details of these twenty-five years are both beyond our ken and beneath contempt--there's that flashing image of the execrable Orange Kewpie Doll again--so we'll spare you from a narrative that likely would cause you to follow in the footsteps of Ray Milland's character in The Man with The X-Ray Eyes. What matters here is to take all this hoo-hah at face value and evaluate it with a relatively straight face, as if it were somehow "real."

The question on the floor is as follows: is this the statistical log of a (gulp!) Hall of Famer? We'll leave you lying on the floor with that slow drip of nitrous oxide seeping into your lungs, bound and gagged by these alien, improbable numbers. Don't even try to numb your senses with that years' supply of Novocaine chewing gum you see above you on the shelf, so close yet so firmly out of reach...just read the numbers until your eyes begin to cross; and, before you laugh yourself into a blissful unconsciousness, "double down" on your opinion of their overall quality. (Forget about the Hanke you may have met in real life: forgive--or overlook--his not-so-occasional weakness for buxom Goth girls. Focus on the man who defied the odds and, thanks to an unkempt seam in time and space, compiled these numbers like so much wreckage salvaged from the sea. Then decide whether these numbers qualify him for a plaque in Cooperstown, where his grin will be the spitting image of the cat who swallowed the canary.)

This trickster's Cheshire tale will continue anon...