Posts Tagged ‘Ty Willihnganz’

Should the Mets defense get credit for Santana’s No-No?

June 2, 2012

On Friday night Johan Santana faced 32 St Louis Cardinal batters.  He struck out 8 of those batters and he walked 5 of them.  The other 19 Cardinal batters put the ball in play, but none of them reached base safely.  Who should get the credit for that fact?  Most every sane person would say Santana, but I would disagree.

Pitchers cannot control whether or not balls hit in the field of play become outs.  All pitchers can do is record outs by strikes, prevent walks by balls, and try to prevent batters from making contact with their bats that is square enough and forceful enough to make the baseball leave the field of play.

Against St Louis, Santana did the last thing well, but he was merely average on the other two.  National League pitchers record 29% of all outs made through strike outs, and that’s exactly the percentage Santana hit on Friday night.  Meaning,  Santana didn’t make the job of his defense any easier than it would normally be.  Thus he did not make a no-hitter more likely by reducing the number of batted balls that the defense had to successfully turn into outs (most multiple no-hit pitchers are power pitchers who make the odds of getting a hit lower by drastically reducing the number of outs the fielders have to make — see, Nolan Ryan).

Don’t get me wrong.  Santana had a nice night.  He only gave up 5 bases to the Cardinals.  That’s above average.  I am not criticizing his performance.  I am using the occasion of his no-hitter to make the general complaint that most no-hitters are a function of dumb luck and superior field defense, not pitching.  Unless a the no-hit pitcher recorded an inordinately high number of strikeouts, he didn’t really do anything to make the no-hitter more likely.   He either got lucky because every ball the opposition hit went close enough to a fielder that it could be turned into a routine out, or he was backed by a defense that turned a bunch of “normal hits” into “spectacular outs”.  (That’s why, generally speaking, you will have at least one or more really spectacular “he robbed him of a sure hit” outs recorded by the team’s field defense in every no-hitter.)

And I think a little of both happened last night.  An unusual number of balls hit in play were of the “playable” variety, and the Mets defense played the other balls superbly.

But who will get the credit in the history books?  Of course, that’s a rhetorical question.  Today, tomorrow, and 50 years from now (when we can’t even remember who played on the 2012 Mets) the credit will belong solely to Santana.   That’s baseball.


I tried the same lie Lucroy is trying… and my doctor called bulls#*t on me!!!

June 1, 2012

Jonathan Lucroy of the Milwaukee Brewers is trying to float the cockamamie story that he broke his hand when his wife dropped a suitcase on it.  It sounded fishy from the jump.  Then we came to find out he has a “boxer’s fracture”.  I know firsthand that he could not have gotten it without balling his fist and slamming it into a solid object.  In other words, his story is a baldfaced lie.

How do I know?  Oh… my doctor sort of told me.  No wait, he sort of told my parents in front of me, let’s put it that way.  Suffice to say I never forgot what a “boxer’s fracture” was and how you can and cannot get one.

Here’s the story.   In middle school we used to play touch football in the school yard before school.  Sometimes things got a little heated.  One day, for whatever reason, me and one of my friends got in a small tiff.  It wasn’t really even a fight.  But it was very cold and I landed a punch right on the side of his hard head.  My hand hurt so bad I couldn’t even grip a pen to write with.

But, being the 7th grade genius I was, I knew I couldn’t say I broke it fighting or I would have to endure six weeks of “What a stupid thing to do!” and “It serves you right for fighting!”  I mean, it was bad enough not being able to do anything at all with my main hand… who wants to add insult to such an annoying injury??

So I made up a really lame lie.  I claimed I somehow hurt it at “football practice”.  Who cares right?  The problem was I never sorted out how it actually happened.  I was real vague about that.  As Brad Pitt says in Inglorious Basterds “We have a word for that in English… it’s called ‘suspicious’!

But, I still don’t think it was necessary for my doctor to embarrass the living shit out of me in front of my parents.  But that’s exactly what he did.

First he has me recount my lameass story.  “Now, how did you say you broke your hand, Ty?”  When I finished he puts the X-Ray on one of those light deals and points out that the fracture was in an area and of a type that is called a “boxer’s fracture”.  The next words are burned into my brain

“Now, Ty.  You can’t possibly have gotten such a fracture in the manner you described.  You had to have punched something or someone.  Now, why don’t you explain how you really hurt your hand.”

After the cold sweat running down my face drained out of my eyes, I finally came clean.  And just as I suspected, everyone insulted my injury.

The question now is, when will Jonathan Lucroy do the same?



Why do coaches sit players who are in foul trouble?

March 23, 2012

Last night the Wisconsin Badgers had a five point lead early in the first half when Jared Berggren, their most productive big man, picked up his second foul.  Coach Bo Ryan replaced him with his much less experienced substitute.  Coach Ryan did the same when Wisconsin’s other productive big man, Mike Bruesewitz likewise picked up his second foul.  Neither played for the rest of the first half, and Syracuse was able to open up a ten point bulge and maintain a six point halftime lead.  Both players finished the game with additional fouls available to them.  Berggren picked up only one more foul in the rest of his action.  The Badgers rallied to take the lead in the second half, but ultimately lost the game by one point.

My question is why on Earth didn’t Coach Ryan leave his best players on the floor?  By removing them for the greater part of the first half, he may have cost Wisconsin the game (Berggren is one of Wisconsin’s top MWS win producers).

I realize Coach Ryan was simply following conventional wisdom, but why is that strategy considered accepted wisdom?  It doesn’t make any sense to me.  There is no necessary reason to disqualify one of your best players from long stretches of a game when the rules do not require you to do so.  What you are doing is effectively taking out one of your more productive players and artificially limiting his minutes without good cause.

So why do coaches follow this practice so blindly?  Let’s examine and debunk the most oft-heard rationale:

1. We must have him available “for later”

Often coaches will justify removing a player who is in foul trouble on the grounds that doing insured that the player would be available to play the latter minutes of a game.  This rationale rests on the faulty premise that certain minutes in a game (the last ones) are more important than any other minutes.  They are not!  I can make a strong argument that Wisconsin would have won easily and would not have needed a last second heave by Jordan Taylor had Berggren remained in the game in the first half.  In order to “be in the game” late, you must put yourself in position.  No minute, and no possession, is more important than any other.

Besides which, coaches cannot predict when a player will foul again.  How does the coach know that the player won’t commit another foul for forty minutes?  The problem is one of perception.  When a player commits fouls more rapidly than usual, the coach’s perception becomes skewed.   Suddenly the player appears “foul-proned” and the coach, believing this, will miscalculate the likelihood of the player committing another foul.

2.  “They’ll attack him for easy baskets”

This rationale is also based on a faulty premise — that a player cannot play aggressive defense without fouling, or alternatively, that a team can induce fouls on a player by “going at him”.  If the first premise were true, teams ought to shoot much higher percentages, and/or we ought to be seeing more players foul out.  If the second premise were true, why don’t teams simply target the other team’s star players immediately?  If fouls are so easy to induce, why not try to induce them?  Because, its not that easy, that’s why.

The simple fact is, the “2 foul rule” is another example of conventional wisdom that is not wise at all.  Its one of those unwritten rules that coaches are afraid to break for fear of looking “foolish” (like when Packers coach Mike Sherman cost the team a playoff game because he didn’t have the stones to go for it on 4th and a millimeter).  Following the “foul trouble” removal practice is actually foolish and detrimental to the teams whose coaches follow it.  Like the Badgers last night.  (Can you tell I’m bitter… read the preceding post).

FOOTNOTE — There’s one scenario I will accept for removing a player early in the game because of foul difficulty.  If the player in question is a primary ballhandler who is also one of the team’s best foul shooters, then I will accept the excuse that he was removed early because “we need him at the end”.  The reason I create this exception is because I recognize that there is one legitimate difference between the ending minutes of a game and every other minute in a game.

In the ending minutes of a close game, the trailing opponent will often deliberately foul members of the leading team in an attempt to regain possession of the basketball in a timely manner.  Rarely will teams employ such a strategy at any other point in the game.  So that’s a tangible difference.  That I will accept.  And I will also accept that if such a strategy were employed, then yes, you would want to insure that your best ballhandling foulshooter were eligible to play those minutes.  That was not the case last night with either Berggren or Bruesewitz.

The LeBron Edict killed the Wisconsin Badgers last night

March 23, 2012

With 13 seconds left and the Wisconsin Badgers down by one point, I and every member of the Syracuse Orangemen knew that Wisconsin’s Jordan Taylor would take the last shot, no matter what.  Knowing this, Syracuse ran two men at him and he nevertheless hoisted a 40 foot fadeaway three pointer that had next to no chance of splashing home.

Now remember, I said the possession started with 13 seconds on the clock and the Badgers down by one single point.  The Badgers, an outstanding foul shooting team who happened to be in the bonus, should have been in the driver’s seat.  The Badgers should have forced the issue, and at least made the Syracuse zone bend before taking a shot.

But, as Steve Martin used to say back when he was funny… “Nooooooooooo”.  Jordan Taylor, Wisconsin’s reputed (but not actual) best player, felt the burden was “upon him” to take the last second shot (I’m assuming this because he made no effort to involve his teammates).

Why did he think this?  Well, if he has basic cable, and if he watches ESPN at all, that’s all they ever talk about.  “Great players make great plays at big moments…” what’s that stupid ass canard they always spout?  It has no meaning, but it is meant to challenge the manhood of any player who doesn’t have the balls to throw up the last second shot.  Every time Lebron doesn’t take the last shot with the game on the line, no matter whether he is quadrupled teamed, the ESPN talking heads question whether he has the stones to take last second shots.  Never mind that one of his teammates might have a higher percentage shot than him.  If he passes off, he is deemed to be gutless.

And as a result of this, players who believe themselves to be the best player on their particular team, as Jordan Taylor must have felt last night, believe a special burden lies upon them to “win or lose” the game, to “put the game in their hands”.

NO!!  The object is to search for and take the best shot possible.  Not to damn the torpedoes and launch whatever you can get.  Last night it cost the Badgers.

Badger-Cuse matchup in a nutshell

March 20, 2012

The Wisconsin-Syracuse matchup is the key to my bracket. It features the age old matchup between the immovable object and the irresistible force.

On offense, Wisconsin likes to slow the game down, protect the basketball and take only high value shots (generally 3s, but layups if they can get them).  The Badgers commit fewer fouls than their opponents and turn the ball over much less.

On defense, the Badgers follow my “Avocado” defensive style.  The Avocado is tough on the outside and at the core, but squishy soft in between.  That describes the Badgers “high value” defense to a tee.  They will allow you to have all the 2 point jump shots your heart desires.  If you make them, as Michigan State did in the Big Ten Tourney, you will win.  What the Badgers will try not to allow are uncontested layups and unchallenged 3 point shots.  Those are the “high value” shots in any offensive sets, whereas 2 point jumpers are extremely low value (at the NBA level, 2 point jumpers are converted only 39% of the time on average, making each shot worth around 0.79 points.  3 pointers at both the high college and NBA level are converted around 35% of the time, making those worth 1.05 points per shot, and layup/dunks are converted around 60% of the time, making those worth around 1.2 points per attempt.  One can see how allowing the one and limiting the other can greatly improve your defense).

Syracuse is almost the polar opposite.  They don’t like the 3 on offense, but they love to run and try to get easy conversions off of steals.  Steals are their forte.  They are not a rebounding team.  They move the ball well on offense and they try to turn you over on defense.

Who will prevail?  I’m a Badger fan, so I’m hoping the Big Red will prevail, but Syracuse, with or without Fab Melo (he wasn’t all that productive in Win Score terms) will be a tough out.


Analyzing the NCAA Basketball 8-9 Matchups, by the numbers

March 12, 2012

Theoretically, the toughest picks to make in the first round of the NCAA basketball tournament are the 8-9 games in each region.  This year’s tournament features three pretty even match-ups and one match-up that should be one-sided.

Below I post the comparative numbers in each of the 8-9 matchups.  The comparisons are between each team’s statistics and the comparable statistics posted by the mythical “average” team.  The first column features each team’s “Team” and “Opposition” Win Score averages versus the mythical average opponent, and the second column features each team’s “Offensive” and “Defensive” efficiency averages versus the mythical average opponent.  So, for instance, if Memphis averaged a Team Win Score of 44.2, and the Mythical Average Team Win Score against the same schedule were 34.2, then in the first column of “MWS”, Memphis would have a 10.0.  If Memphis had an Opponent Win Score average of 34.2 and the Mythical Average Team had an Opponent Win Score of 44.2, then in the second column of “MWS” Memphis would also have a 10.0.  If Memphis had an offensive efficiency average of 115.0, and the Mythical Average Team had an offensive efficiency average of 105.0, then Memphis would have a first column “PVOA” of 10.0, and so on.

Iowa St-Uconn
MWS  Total
Iowa St 13.4 6.9 20.3
Uconn 12.6 6.5 19.1
PVOA  Total
Iowa St 12.1 5.6 17.7
Uconn 8.1 5.9 13.9
MWS  Total
Memphis 12.9 11.2 24.1
St Louis 5.3 12.6 17.9
PVOA  Total
Memphis 9.9 10.9 20.9
St Louis 8.7 11.6 20.3
MWS  Total
Alabama 5.1 11.8 16.9
Creighton 15.6 2.9 18.5
PVOA  Total
Alabama 2.9 11.8 14.7
Creighton 15.2 -0.8 14.4
MWS  Total
Kansas St 6.6 13.2 19.8
SouthMiss 5.7 4.1 11.7
PVOA  Total
Kansas St 6.6 10.3 16.9
SouthMiss 7.5 0.8 8.3

Two Potential NCAA Upset Picks, with supporting math

March 12, 2012

Perusing the NCAA brackets, I have spotted two potential upsets, Harvard over Vanderbilt and Texas over Cincinnati.  Each upset pick is based on “Point Value over Average” meaning the teams ability to play above their opponents offensive and defensive efficiency averages.

I provide the supporting math for each pick.

Harvard over Vanderbilt

Harvard 103.8 85.9
Opp 96.9 95.3
PVOA 6.9 9.4
Vandy 106.5 94.8
Opp 95.7 100.1
PVOA 10.8 5.3
Harvard 98.5 96.7
Vandy 97.1 101.7
Harv 100.1 59.9
Vandy 96.9 40.1

Texas over Cincinnati

Texas 103.8 94.2
Opp 94.4 100.4
PVOA 9.4 6.2
Cinn 101.7 91.8
Opp 96.3 97.9
PVOA 5.4 6.1
Texas 97.7 99.6
Cinn 95.5 101.2
Texas 99.4 55.8
Cinn 97.5 44.2


Here’s what I did.  The first column for each team shows the team’s offensive and defensive efficiency per 100 possessions.  The next column shows the offensive and defensive efficiencies allowed by their opponents.  The third column is their offensive and defensive PVOAs, the amounts they play above and below the given efficiencies.  I then applied each team’s PVOA to the other team’s offensive and defensive efficiencies. Those are the third set of numbers.  Finally, I took the averages from each and projected an efficiency “Score” for each team in the matchup.  Meaning, for instance, Harvard’s “Score” was the average of Harvard’s “Vandy Adjusted” Offensive efficiency and Vandy’s “Harvard Adjusted” Defensive Efficiency, which equaled 100.1, and Vandy’s “Score” was just the opposite calculation, which equaled 96.9.

The final number next to each team’s likely offensive efficiency was the likelihood of victory, which is computed according to the likelihood of a team with the given offensive and defensive efficiency average prevailing in the game.  Harvard’s likelihood of victory, according to PVOA, is 59.9%.  Texas’ likelihood of upsetting Cincinnati is a bit less at 55.8%.

Ranking every 2012 NBA rookie performance using Marginal Win Score

March 9, 2012

Kawhi Leonard: Los Rookie of the Year Leader

Using the basketball metric known as Marginal Win Score, I have measured the contribution of every single NBA rookie who has played at least 100 minutes this season, and I have ranked each according to his “Value” Score (wins plus wins above 0.500%).

ROOKS tm WS dWS MWS W% W__L W0.5 V
K Lnard SA 12.63 7.47 2.57 0.939 3.3__0.2 1.5 4.8
R Rubio Min 7.65 5.78 0.93 0.661 3.7__2.0 0.9 4.5
K Faried Den 19.71 8.76 5.47 1.431 2.3__(-0.6) 1.4 3.7
C Prsons Hou 8.41 7.14 0.63 0.611 2.5__1.7 0.4 2.9
G Ayon NO 13.98 9.82 2.08 0.856 2.1__0.4 0.8 2.9
E Kanter Uta 13.21 9.41 1.89 0.825 1.8__0.4 0.7 2.5
D Wllms Min 10.06 8.69 0.68 0.618 2.0__1.3 0.3 2.3
J Butler Chi 10.76 -2.46 6.61 1.624 1.1__(-0.4) 0.7 1.8
K Irving Cle 8.01 8.75 -0.37 0.439 1.8__2.4 -0.3 1.5
N Vcevic Phi 12.72 11.67 0.52 0.591 1.3__0.9 0.2 1.5
T Thmpsn Cle 9.24 9.11 0.06 0.514 1.3__1.2 0.1 1.4
I Thomas Sac 6.49 7.16 -0.33 0.445 1.5__1.8 -0.2 1.3
J Harrllsn NY 11.74 9.62 1.06 0.682 1.0__0.4 0.3 1.3
L Allen Phi 11.45 11.04 0.19 0.536 1.0__0.9 0.1 1.1
I Shmprt NY 3.23 4.69 -0.73 0.377 1.5__2.4 -0.4 1.1
K Thmpsn GS 4.69 5.06 -0.18 0.471 1.2__1.3 -0.1 1.1
S Mack Was 7.05 6.57 0.24 0.543 0.9__0.7 0.1 0.9
A Burks Uta 3.08 2.57 0.25 0.546 0.9__0.8 0.1 0.9
J Jhnsn Bos 8.85 6.11 1.36 0.734 0.6__0.2 0.2 0.8
J Stone Den 8.54 3.76 2.39 0.908 0.5__0.1 0.2 0.7
J Hmiltn Den 9.01 8.79 0.11 0.521 0.3__0.2 0.1 0.3
R Jcksn OKC 1.49 3.82 -1.16 0.305 0.5__1.1 -0.3 0.2
B Bymbo Cha 10.47 12.78 -1.15 0.306 0.7__1.7 -0.5 0.2
M Mrris Pho 7.74 10.64 -1.45 0.256 0.8__2.4 -0.8 0.1
M Broks NJ 5.85 8.59 -1.37 0.268 1.0__2.8 -0.9 0.1
J Wllams NJ 10.02 12.62 -1.31 0.281 0.3__0.6 -0.2 0.1
J Leuer Mil 9.82 12.62 -1.39 0.264 0.5__1.4 -0.4 0.1
K Wlker Cha 6.05 9.09 -1.52 0.244 1.1__3.3 -1.2 -0.1
E Mre Bos 0.86 3.89 -1.51 0.245 0.2__0.7 -0.3 -0.1
T Hrris Mil 8.21 11.43 -1.61 0.229 0.3__1.0 -0.3 -0.1
J Slby Mem -2.13 2.61 -2.36 0.101 0.1__0.8 -0.4 -0.3
W Rssll Det 0.56 5.43 -2.43 0.089 0.1__1.1 -0.5 -0.4
C Sngltn Was 5.69 10.09 -2.19 0.129 0.4__2.7 -1.2 -0.8
I Jhnsn Atl 7.44 9.44 -0.99 0.333 0.6__1.3 -0.3 -0.9
D Mrris LAL 1.97 11.73 -4.88 -0.326 (-0.2)__0.7 -0.4 -0.6
C Jsph SA 2.15 10.77 -4.31 -0.225 (-0.2)__1.0 -0.6 -0.8
C Hggns Cha -3.49 4.47 -3.98 -0.173 (-0.2)__1.3 -0.7 -0.9
N Smith Port -2.24 9.43 -5.83 -0.487 (-0.3)__0.9 -0.6 -0.9
C Jnkins GS 2.98 13.89 -5.45 -0.423 (-0.3)__1.0 -0.6 -0.9
J Pargo Mem -2.64 7.85 -5.24 -0.387 (-0.4)__1.6 -0.9 -1.4
J Vesely Was 5.16 12.78 -3.81 -0.143 (-0.3)__2.2 -1.2 -1.5
N Cole Mia 0.83 6.56 -2.86 0.016 0.0__3.3 -1.6 -1.6
J Frdtte Sac 2.48 11.12 -4.32 -0.229 (-0.6)__3.5 -2.1 -2.7
B Knght Det 3.12 9.96 -3.42 -0.078 (-0.4)__5.6 -2.9 -3.3
6.12 8.20 -0.88 0.351 -11.8 22.8

SF Kawhi Leonard the ROY leader

As the chart shows, in terms of Value Ranking, Kawhi Leonard has passed the Spanish Sensation Ricky Rubio right by.  Leonard is having a spectacular season for the Spurs, and you barely ever hear about him.  What a shame.

Rubio has come back to the pack, but he is still having a pretty good season.  Fellow PG Kyrie Irving is proving to be a productive player, but he struggles on defense.  I expected that to happen to Rubio, but not to the Duke-trained Irving.

Derrick Williams has come on very strong for the Timberwolves as well.  What a massive upgrade he is over the awful, awful SF Michael Beasley.  Whoever the Twolves dump Beasley on is going to be in for a dip in the standings.

Two other players who need to be mentioned are SF Chandler Parsons of the Houston Rockets, and someone named Ayon, who plays PF/C for the New Orleans Hornets.  I never heard of Ayon, to be honest with you, but he is very productive.

The larger story is the general lack of production from rookies in general.  The entire rookie class has a collective Value Ranking that barely exceeds the Value Ranking of Miami SF LeBron James!  Rookies simply do not contribute very much to a team.  That’s why it is foolish to pin too much of your hopes on the draft.  Only one or at most a handful of rookies ever make a significant contribution to their NBA teams.

And you run the risk of having them destroy your season.  PG Brandon Knight is absolutely killing the Detroit Pistons.  Same goes for PG/SG Jimmer Fredette and the Sacramento Kings.  I thought “JimmerMania” was supposed to hit the NBA?  Jimmer cannot make baskets at the professional level.  The Kings drafteed a better player inm the second round when they drafted Washington PG Isiah Lord Thomas II.

The Garbage King of the rookie class appears to be Chicago rookie from Marquette Jimmy Butler.  Butler has barely played this season, but he has been unbelievably productive when he has played.  In fact, in terms of Value, he has contributed more to the Bulls in his short minutes on the court than Kyrie Irving has contributed to the Cavaliers.  Whether that will bear out over the long haul is pretty doubtful, but nevertheless an impressive debut for a pretty lightly regarded prospect.

EDIT:  The original post contained a monster oversight.  I missed PF Kenneth Faried from the Denver Nuggets.  Luckily, he is coached by George Karl, a man who hates rookies who are not scorers.  Had Karl played Faried anywhere near the minutes his production demands, Faried would be the ROY leader, and I would have had to edit the entire post.  Thank you, George.

Power Ranking the 2012 NCAA Tournament Field

March 8, 2012

Below is my power ranking of the likeliest participants in the 2012 NCAA mens basketball tournament, using the normally reliable Joe Lunardi as my early guide. (I have included all of the teams down to his “Second Four Out”, but there could be conference tournament upsets still to come)

You may use these rankings as a guide next week when you are filling out your tournament sheet.  Here is an explanation of my rankings.

Remember, however, these rankings are only a guide.   The tournament games will not be uniformally decided by strength.  Somewhere in the neighborhood of 25% of the games in each round will be “upsets”, in the sense that the lesser team will beat the stronger team (For a simple reason — even lopsided matchups feature teams with at least a 20% chance of winning).  The trick is to figure out where those upsets will fall and where they will not.

1 Kentucky 0.634 0.917 1.551
2 Kansas 0.544 0.922 1.466
3 UNC 0.651 0.793 1.444
4 Ohio St 0.511 0.919 1.431
5 Mich St 0.572 0.841 1.412
6 Syracuse 0.523 0.773 1.296
7 Wisconsin 0.445 0.787 1.232
8 Missouri 0.443 0.745 1.188
9 N Mexico 0.439 0.713 1.152
10 Baylor 0.452 0.661 1.113
11 California 0.418 0.689 1.108
12 Duke 0.441 0.666 1.107
13 Florida 0.425 0.662 1.087
14 Indiana 0.454 0.629 1.083
15 Witch St 0.359 0.717 1.076
16 St Marys 0.408 0.662 1.069
17 Gtown 0.401 0.631 1.031
18 Memp 0.394 0.629 1.024
19 Gonzaga 0.437 0.568 1.005
20 UNLV 0.405 0.597 1.002
21 Louisville 0.382 0.602 0.984
22 Marq 0.345 0.599 0.944
23 St Louis 0.304 0.639 0.944
24 Virginia 0.339 0.591 0.931
25 Belmont 0.311 0.552 0.863
26 Harvard 0.337 0.506 0.843
27 Kan St 0.313 0.526 0.839
28 Vanderbilt 0.323 0.514 0.837
29 Alabama 0.308 0.512 0.819
30 BYU 0.347 0.471 0.818
31 Murr St 0.289 0.524 0.814
32 Texas 0.328 0.476 0.804
33 Iowa St 0.305 0.546 0.851
34 Arizona 0.303 0.479 0.782
35 Iona 0.301 0.466 0.767
36 Creighton 0.316 0.449 0.765
37 Michigan 0.325 0.441 0.766
38 Davidson 0.282 0.463 0.745
39 SD State 0.243 0.483 0.726
40 Oregon 0.265 0.454 0.719
41 Uconn 0.316 0.392 0.708
42 W VA 0.265 0.435 0.699
43 St Josephs 0.301 0.387 0.688
44 No Dame 0.319 0.421 0.675
45 Lng Bch St 0.265 0.399 0.664
46 Temple 0.267 0.382 0.649
47 Drexel 0.189 0.428 0.617
48 Miss St 0.259 0.353 0.612
49 NC State 0.299 0.312 0.611
50 Washing 0.211 0.381 0.592
51 Purdue 0.201 0.383 0.584
52 Xavier 0.192 0.382 0.574
53 SanD State 0.242 0.323 0.565
54 Cinn 0.184 0.379 0.564
55 Vcomm 0.196 0.362 0.558
56 Lehigh 0.177 0.359 0.536
57 Akron 0.209 0.321 0.531
58 Montana 0.194 0.331 0.525
59 Col St 0.198 0.326 0.524
60 Seton Hall 0.206 0.301 0.507
61 Tennessee 0.194 0.311 0.505
62 UNC Ash 0.199 0.285 0.484
63 Sth Mssp 0.148 0.327 0.475
64 Nevada 0.159 0.313 0.473
65 Nwestern 0.143 0.276 0.419
66 Miami 0.172 0.227 0.399
67 S Flor 0.145 0.189 0.334
68 Long Islnd 0.128 0.134 0.262
69 Loy Md 0.114 0.142 0.256
70 Detroit 0.021 0.024 0.045
71 W Kent -0.068 -0.053 -0.121

Initial Observations about Overvalued Teams

Remember, this post went up well before the tournament selections, so there are several teams on here who will not make the field (I also excluded some of the sure #16 seeds).  At the time of writing, it appears some of the Big Ten teams might be overvalued, and might be ripe for upset picks.  The Michigan Wolverines are ranked #8 in the country, but by my comparative strength measurements they are well down the list.  Northwestern and Purdue also look like phonies.

On the other hand, it appears the Pac 12 is getting shortchanged.  California is stronger than they have been given credit for, and there are other teams out there like Oregon and Arizona who deserve bids ahead of the lesser Big Ten teams.

Another team that is likely to be overseeded is the Marquette Golden Eagles.  Marquette is a strong team, but not nearly as comparatively strong as Joe Lunardi’s forecasted 2 seed would suggest.  Indeed, many of the Big East teams appear as though they may be overvalued as well.  Syracuse is a perennial underachiever.  If you are targeting a top seed to fall, you could do a lot worse than Syracuse.


If you will notice, the three power rankings produce 3 separate favorites.  If you go by Marginal Win Score, the favorite is North Carolina.  If you go by PVOA, the favorite is Kansas.  If you combine the two, the favorite is Kentucky.  There is a simple explanation.  MWS is a more holistic ranking.  It rewards teams who do the little things that create wins, whereas PVOA concentrates on rewarding scoring efficiency.

North Carolina is not a great scoring team, but they are a tremendous rebounding and possessionary team.  Ohio State and Kansas are great scoring and scoring defense teams, but not in UNC’s league when it comes to the “Hustle Board”.  And Kentucky is strong in both areas, but it is not the strongest in either.  Its dealer’s choice this tournament season.

I will have more analysis as we get into the weekend.

Q: Who the hell is Cleveland Buckner? A: He’s the “JD Tippit” of the Chamberlain 100 Point Game

March 3, 2012

Following up on yesterday’s post, a couple more thoughts on the legitimacy (or lack thereof) of Wilt Chamberlain’s 100 point scoring night.

At least the Knicks made Wilt earn his 100

I ran ten simulated games on Whatifsports between the 1962 Knicks and the 1962 Warriors and the average effective scoring for the Knicks was (-7.9) points and for the Warriors it was (+3.5).  The highest effective scoring totals I could achieve for each team was (+6.5) for the Knicks and (+27.0) for the Warriors. On Wilt’s Big Night, the Warriors were (+28) and the Knicks were (+9).  So its theoretically possible that each team simply had an unusually hot night on that particular night. However, it would have been unlikely without some defensive laxity.  In the 10 game simulation run, I produced only one positive scoring night for the Knicks and five for the Warriors.  I produced no games where both teams had positive scoring nights.

Something else weighing somewhat in Chamberlain’s favor is the breakdown of his scoring.  First of all, the Knicks were making Chamberlain earn his hundred from the foul line.  On a normal night in the 1962 season, Chamberlain would have shot 26 free throws on 63 field goal attempts.  On this night the Knicks made him shoot 32, of which he made 28.  Moreover, Chamberlain must have fouled out the Knicks best defensive center, Darrell Imhoff, so he presumably was going against their second stringer, Cleveland Buckner, for most of the game.  And while Chamberlain’s teammates were clearly force feeding him in the second half (I have no problem with that), the Knicks were just as clearly playing some semblance of defense on Chamberlain, as Chamberlain went 22 for 37 from the field in the second half.  Yeah, that’s not great defense, but its not dunk after dunk.

Curiously Huge Scoring Night for a Knick named Cleveland Buckner

Here’s where I have a problem.  It appears the Warriors were giving up points on the offensive end to get more opportunities for Wilt on the offensive end.  In my mind, that’s “queering the pitch” as the British would say.

Here’s my evidence that everything wasn’t on the up-and-up. The three backups for the Knicks (Buckner, Dave Budd, and Donnie Butcher) combined to make 25 of 40 shots from the field (62.5%).  That’s 48% better than the 1961-62 NBA average.  If the 29-51 Knicks had that kind of scoring talent on their bench, they shouldn’t have been 29-51!!  Indeed, on a normal night in 1962, with the same shot mix from the same players, the three should have hit only 40.0%.  That’s a large increase in average, suggesting lack of contested shots by the Warriors (or possibly by Chamberlain himself) in the second half of the game, possibly for the purpose of getting the ball back faster to get shot attempts for Wilt (I’m assuming the second half is when most of the reserve minutes happened).  It’s sort of like deliberately letting the computer score in Tecmo Bowl in order to see how many rushing yards you could get for Randall Cunningham.

The box score contains even more evidence of potentially soft defense by Philadelphia.  Far fewer than average free throw attempts by the Knick reserves. Why is that evidence of soft defense?  On one occasion one of my basketball coaches came in to the locker room at halftime and he simply stared at the score book.  When he finally raised his head, he looked directly at me and screamed, “Ty!! Do you know how many fouls you have?!”  I was completely dumbfounded at the question and I replied timidly, “I don’t know… I think zero”.  I really didn’t understand what he was getting at.  He pounced on that answer, “Yeah, that’s right… you aint playin no defense!!”

If my ex-coach’s somewhat suspect logic is accepted as presumptive evidence of soft defensive effort (I still to this day won’t accept it as conclusive proof of lack of effort, but I will accept it as presumptive proof.  In other words, once established, then the burden would have shifted to me to rebut — in which case I would have cited my counterpart’s lack of inside shooting as explanation for my lack of fouling), then the Warriors “weren’t playin no defense” on two of the aforementioned 3 reserve Knicks: C Cleveland Buckner, and F Dave Budd (both inside players — pointing again to Chamberlain as the culprit).

Buckner, a reserve forward-center who didn’t even last one more full season in the NBA, and who shot just 43.7% from the field for his career, somehow went 16-for-26 against Wilt Chamberlain, and, since he was a big man with a low field goal percentage, one can assume that most of his shots on Wilt’s 100 point night were close-in shots.  If that is the case, and if you wanted to argue against the point that the Warriors were “laying down” on defense in the second half, then how would you explain the fact that in 26 field goal attempts, Buckner shot only 1 free throw!! If he were going to the line at his normal rate, he would have shot 10 free throws.

And then there’s the case of reserve Dave Budd.  Budd was a also a 43% field goal shooter who took about 0.4 free throws for every field goal attempt. Yet on Wilt’s night he shot 75% from the field (6-8) and took only one free throw attempt for his 8 field goal attempts.  So, combined, you have 34 field goal attempts, 2 free throw attempts, and 22 made field goals from a piss poor team’s two reserve front court players, where on a normal night you would have expected 34 field goal attempts to produce 14 makes and 14 trips to the free throw line.  So, either these guys both got peculiarly hot at the same time on the same night, or we someone or “ones” was letting them get to the basket in order to get Wilt more shot attempts.

So, all in all, here’s is what I’m going to conclude about Wilt’s 100 point night:

1. The Warriors force fed Wilt the ball in the second half to get him to 100 (which is fine);

2. The Knicks made him earn the 100 by putting him on the line; but,

3. The Warriors, and possibly Wilt himself, laid down on defense to get more scoring opps for Wilt in the second half, which in my mind taints the result.

Footnote:  While I could not find Cleveland Buckner’s college statistics, its interesting to find that he is 74 and he has a Facebook page.  Which is more proof that Donnie Deutsch was right to predict that some hipper social media site will soon displace Facebook.