The basketball gods are with us



  • Our guys are ironing out all the wrinkles. Day by day they are learning. You can see them progressing nearly every game. You can see the cream rising to the top. Our rotation is becoming more defined each game. Our 3pt % from our 2 PG’s and Greene are outstanding and probably make the best 3pt trio in college basketball if they can maintain it until march! If you look at Ellis and Alexander you see a high shot percentage and Alexander’s ppm is super high! I have no idea how HCBS is going to work in all of our guards but the guys that are not knocking down 3’s better start spending time shooting more 3’s. That is going to be this teams identity with Ellis hanging out on the perimeter and our C walking their man out to the free throw line for the inlet pass, long rebounds, and put backs!

    Oh yeah this is a good article too!

    http://collegebasketballtalk.nbcsports.com/2014/12/11/self-says-no-10-kansas-is-not-good-right-now-and-that-should-scare-you/

    Over the next 3 games we will play 3 more top 100 opponents and will have played the toughest schedule to date! According to yahoo RPI Temple and Lafayette are in the top 100. Utah is going to be another close one IMO but I suppose we will see? Our guys are going to go into our conference battle tested more so than anyone! That is what’s going to make the difference. I like to watch us kill cupcakes but I think this is the way to go about business, Even though is not easy to watch our guys down by 18 against Florida and all of the close games that have had me screaming at the television set like an idiot! This is going to get us ready for another match up with UK and I know we are all ready for that rematch!



  • @Statmachine I agree totally. All these tough games that KU has played so far, it will make them better able to deal with the pressure certain teams like Texas will try to beat KU with. Utah has one if not two 7 footers and some pretty good guards too if I am not mistaken. This will be a close game if KU wins it. I dont know why, but I am always nervous about KU’s games at the Sprint Center. Its basically a home atmosphere for KU since they are so freeking close. But I dont think that gives them an edge the way that AFH does. So far this season KU has had trouble with guys like Josh Smith and the Fleet of Footers that Kentucky threw at us. Utah is just one more test to get them ready for the conference and beyond. Lets hope they pass that test.



  • I loved this line:

    “Perhaps more telling is that after blowing a defensive rotation — he was late on help-side and allowed Smith to catch an over-the-top pass in the post for a dunk — Oubre was yanked, yelled at on the bench … and put right back into the game a minute later.”

    I hope Self keeps doing that to these freshmen. I love it.



  • (posted elsewhere, but this thread looks like a better place for my comment)

    Some good signs:

    1: ‘Solving’ a physical opponent (a formula that will be necessary to repeat as soon as Saturday, and later against Texas and others)

    2: A team with balanced scoring: [PPG] Ellis 14.4, Mason 10.6, Alexander 9.6, Selden 9.3,

    3: Winning without Traylor (and Svi, for all intents and purposes)

    4: Repeatedly coming back against an opponent on the road

    5: Oubre’s positive attitude: “I love my team,” Oubre said. “We showed some signs down the stretch that we’re going to be great.”

    1. Lots of room for improvement, yet 7-1

    A cautionary note or two: 1: KU is the third “luckiest team” this year

    2: KU is facing a true test on Saturday. Despite beating some good names (Tennessee, Michigan State, Florida and Georgetown), the reality is that KU is 0-1 against top 25 teams this year. Utah is 1-1 against top 25.

    I’m repeating myself but the Utah game will speak volumes about what to expect from this team.



  • MSU was ranked 20 when we beat the. So that would make us 1-1 vs top 25 teams to date. I also don’t know how GTown was not ranked. Thst is, most certainly, a top 25 team.



  • @bskeet

    See my reply on the other thread.



  • @bskeet A cautionary note or two: 1: KU is the third “luckiest team” this year… I HOPE THE LUCK CONTINUES THIS WEEKEND!



  • I also think this years conf is going to be the hardest fought battle in the HCBS era! Our conf is sooo good this year. I just hope our guys are ready in less than a month to get down to business!



  • @Statmachine

    “Luck” tends to even out over the course of the basketball season. That’s one reason that it’s nearly impossible to go undefeated in basketball. A couple bad bounces here or there will almost certainly cost you a game at some point.

    KU needs to start getting into some convincing wins so that luck can break the other way and they still come out on top.



  • @justanotherfan said:

    “Luck” tends to even out over the course of the basketball season.

    True… And yet @Jesse-Newell 's story indicates that we tend to be a bit ‘luckier’ than the average team over the course of Bill Self’s tenure. His only speculation is that KU is “tougher” than other teams. I think it might be because we play more games in AFH than other teams 😉

    This may be empirical evidence to a home court advantage that is greater than others… I’ll call it the AFH-Factor. It has to be worth a couple points in every game we play at home.



  • @bskeet

    Luck favors the prepared mind. 😉



  • @DoubleDD That belongs in our quotes thread 😉



  • @JayHawkFanToo You’re right-- We’ve played some of these teams when they are ranked and MSU is still in a poll that I missed… So we are better against Top 25 competition.

    My point is – THIS YEAR – Utah doesn’t appear to be as much of an inferior opponent as folks might think based on their name… just as Florida, MSU, G’Town aren’t as superior… But they are good competition and we are starting to earn our ranking.

    More importantly, I see our defense improving and our passing/assists improving (still erratic on turnovers). And of course our 3pt shooting and free throws have been much better than the exhibitions and the early games.



  • @bskeet last game, passing was awful!!!



  • @Crimsonorblue22 True… but I saw a few good assists. Passing seems better when Svi is on the floor… Selden has shown the ability to find someone open as well.



  • @bskeet coach talked about it in the post game interview.



  • @bskeet

    Poor teams depend on luck but, good teams get lucky…GREAT teams make their own luck.



  • @JayHawkFanToo

    Explains why I don’t get lucky… er… um… wait, what!!!



  • @Kong

    With handle like Kong? Really? 🙂 🙂 🙂



  • @bskeet

    If that is true, I think that also may be a source of our March frustration. We can’t take AFH into the tournament with us, so those 8-12 points that home court is worth to us evaporate at a moment when we need them most.



  • @bskeet Neither Florida or Michigan St were ranked when we played them?



  • @bskeet Nevermind, I didnt even read the other posts before my previous post.



  • 🙂 hey, regarding the luck thing-- I’m not saying we were lucky to get to 7-1… I’m just repeating what @Jesse-Newell 's article suggested… I think he’s citing a KenPom.com statistic/metric. And I was trying to offer some plausible reasons why we might be “lucky”.

    And-- Mea culpa on the 0-1 record against top 25 teams… That was my mistake. Several of those teams were in the top 25 earlier in the season.

    ####Newell: Jayhawks have been ‘lucky’ in 2014-15####

    luck



  • So…every time yo win by 10 or less, luck is involved? I don’t buy it. When two disparate teams play a large margin could be expected; however, when two top 20-30 teams play the result will usually be a lot closer, normally single digits; good teams manage to win the close games. With parity in college basketball the big blow outs are now the exemption and not the rule and on any given day, any team can beat any other team; ask Nebraska and Michigan.

    If you know statistics, you know that you can manipulated them to appear to show anything you want, but upon closers scrutiny you can see the flaws in the hypothesis. Will Rogers famously said: “there are lies, damn lies and statistics…” Sometimes I believe statistician have too much time in their hands and a desire to come up with something new/different and hence draw conclusions that are really meaningless, such as this one, this early in the season. MIT graduate and prediction pioneer Jeff Sagarin has a disclaimer attached to his numbers that indicates that it takes a number of games before the model reaches “steady state” and early prediction are meaningless. Just my opinion and I could be wrong.



  • @JayHawkFanToo Clearly we need @KenPom on our site so he can explain his logic! 😉



  • @bskeet

    KenPom quit his day job and now he does full time predictions and needs to spice up his web site with a little fluff and controversy. I liked him better when he did it as a hobby.



  • @JayHawkFanToo said:

    So…every time yo win by 10 or less, luck is involved? I don’t buy it. When two disparate teams play a large margin could be expected; however, when two top 20-30 teams play the result will usually be a lot closer, normally single digits; good teams manage to win the close games.

    You either don’t know what luck is, then, or you don’t understand statistics fundamentally. The reason close games get counted as ‘lucky’ by KenPom and others is because when games are close, variance and noise are bigger factors in determining the outcome. Consider a WVU/Syracuse game from 2011 that was decided by a point. WVU had the winning shot pulled off the cylinder, but the ref didn’t call the goal tend. WVU got unlucky. They couldn’t do anything to make the ref make the correct call, but they left themselves vulnerable to that by being in a tight game. Or consider what it means to be a 40% 3pt shooter. It doesn’t mean you go miss-make-miss-make-miss every game. You could go 2/3, 1/2, 1/7, 2/3 over the span of four games and still wind up at that percentage. But if the cold game is also a close one, again, that’s exactly what it means to have bad luck. The better or tougher team doesn’t always win. If you have a margin greater than 10 points, though, that’s high enough that you can rule out statistical noise as a significant factor in the outcome.

    Will Rogers and the public at large just don’t understand what guys like Nate Silver and Ken Pomeroy are trying to do. If you really know statistics, then you know that the only people that can be fooled by manipulating them to ‘say whatever you want’ are people that don’t understand how the information is derived. It’s like any question of logic; it’s not just what you ask, but how you ask it that determines the validity of assertions made with the data. In other words, garbage in, garbage out. And Sagarin isn’t saying that early predictions are meaningless, he’s just saying that predictive models become more accurate the more data they have to work with, which I think would be self-evident.

    Lastly, nobody makes their own luck. By definition, luck is a factor of elements and/or circumstances beyond one’s control. The difference is that some people set themselves up to capitalize on luck when it happens, and others curse themselves for not.



  • @konkeyDong

    I had a Jaybate-like long post with a technical explanation of my position but I lost it when looking for an emoji icon. Oh well…probably not appropriate for sports forum anyway. Too lazy to re-write it.



  • I saw on tv tonight that Brannen will make his first start as a Jayhawks.



  • @konkeyDong - So, folks that do stats are just way smarter than everyone else? We just simply don’t understand what they are trying to do, so we can’t question the value or validity?

    Lucky because you win close games? Hogwash and bullsh**. Great teams win close games. Champions win close games. And I don’t need a statistical lecture to know that.

    What that tells me, if I’m smart enough to figure it out, is that “luck” statistic has nothing to do with who might or might not be the best team, or the champion.

    Therefore, it is useless tripe.



  • @HighEliteMajor said:

    So, folks that do stats are just way smarter than everyone else? We just simply don’t understand what they are trying to do, so we can’t question the value or validity?

    Lucky because you win close games? Hogwash and bullsh**. Great teams win close games. Champions win close games. And I don’t need a statistical lecture to know that.

    Well, you definitely misunderstood the post, so what am I to conclude? I don’t think that people who are versed in statistics are way smarter than everyone else, the same way I don’t assume that people can speak Mandarin Chinese or know how to work on a Cessna engine are smarter than everyone else. They just have a particular skill in a particular field. You can question the validity of their conclusions all you want, but when you don’t have that skill and you comment on their work, you can wind up looking foolish just as quickly as I would trying to correct someone’s Chinese.

    Yeah, great teams win close games more often than less great teams. That’s not the point of the stat. What a higher luck stat indicates is that you’re playing a lot more close games and winning. In other words, if you win a lot of games rating high in the ‘luck’ category, it points to being fundamentally less sound. You’re winding up more lucky than good because actually good teams wouldn’t be playing as many close games to begin with. The best teams are the ones that consistently blow out their opponents, right? Hats off, though, for proving my point.



  • @konkeyDong No, the stat is useless. Completely useless. And the stats come from folks that aren’t involved in sports, or the games. All they do is crunch numbers. So perhaps they are the Cessna mechanic, while those that actually “do” are the pilots.

    The best teams are not the teams the blow teams out regularly. Stats don’t measure character, and chemistry, and what it really takes to win consistently. Winning close games does not point to being less fundamentally sound. You say that is what is attempting to be proven. Those two events – close games vs. being less fundamentally sound have nothing to do with one another. The entire discussion assumes that connection to have validity. I have coached several teams in each sport … baseball, football, and basketball. And the best teams I’ve ever coached played a lot of close games, but had the knack for regularly winning close games (and did not regularly blow people out).

    UConn was 40th in scoring margin last season. But I understand the circular nature of this discussion … “oh, that’s not what we’re trying to show.” Or “the NCAA tourney is luck.” Or whatever.

    Here’s what the article said: “A measure of the deviation between a team’s actual winning percentage and what one would expect from its game-by-game efficiencies. It’s a Dean Oliver invention. Essentially, a team involved in a lot of close games should not win (or lose) all of them. Those that do will be viewed as lucky (or unlucky).”

    That is just complete b.s. A team “should not win (or lose) all of them”? Right, they “should not.” It’s just a fundamental flaw to assume that it is “luck” when they do. The mistaken premise is the assumption that they “should not.” That does not consider that good teams, the best teams, actually “should.”

    It assumes that good vs. luck is defined by the margin of victory. Only someone who has not been around sports would even consider that as a measuring stick. It ignores the concept of consistency, which is a key component of great teams.

    Look, I know I won’t convince you. So I’m not even trying. Not sure how much you’ve coached, or been in that situation. But you certainly approach it with a certain arrogance … perhaps one that is lacking from practical experience.

    I’ve seen this stuff first hand. I coached a basketball team, and we rarely won by double digits. But we never lost. We beat teams that would blow out the teams that we beat by a handful of points. Same in football. Style of play dictated that in some years, we were going to have smaller margins of victory. And certainly in baseball, where a pitching/defense teams … such as the Royals … are not going to win by large margins. But the Royals, actually, were not a “lucky” team. They had perhaps the surest of things, a lockdown bullpen. The baseball team I coached this past summer couldn’t seem to blow anyone out, but we kept winning, and kept getting tourney trophies. We were consistent.

    When one connects margin of victory and luck, it denotes a lesser level of skill or “earning it.” And a lower reliability in repeating the result. And that just isn’t the real world of sports. It ignores one important variable – consistency. Great teams have consistency. And that ain’t luck.



  • @konkeyDong

    I think you are giving too much credit to a pretty useless “statistic.” By definition, luck is something that cannot be calculated or predicted, so when some body quantifies it, it is by definition an oxymoron. Lucky wins are those won by 1 point by a half court shot as time expires, wining by 5, 6, 7, 8 or 9 point does not fall in the category of “lucky.”

    you wrote…

    **What a higher luck stat indicates is that you’re playing a lot more close games and winning. In other words, if you win a lot of games rating high in the ‘luck’ category, it points to being fundamentally less sound. You’re winding up more lucky than good because actually good teams wouldn’t be playing as many close games to begin with. The best teams are the ones that consistently blow out their opponents, right? **

    This is a fundamentally flawed premise because it assumes that you are playing the same competition and luck is allowing you to win. 20-30 years ago a game between a major conference program and Mid-major was a one sided affair; now…not so much and mid-majors beating a major conference team are common place; scores are getting closer and closer every year a result of the parity that exists in the sport . If KU switches to an all punch bag schedule, they would win by 20+ points most every game or it could switch to a tougher schedule (like now) where it still wins by virtue of being the better team, but score margin would only be in the single digits, does this mean that KU is lucky? You are saying that KU is not a good team because it has played (and won) several close games…and good teams do not play close games…you don’t consider that KU is actually winning because it is better than the other team, be that by 5 points or 10 points or 20 points but better nonetheless. I don’t think this is correct. What you are saying is that every game that is won the single digits category is a lucky win and I personally think this is not correct.



  • I’m going to take these points one at a time:

    @HighEliteMajor said:

    The best teams are not the teams the blow teams out regularly. Stats don’t measure character, and chemistry, and what it really takes to win consistently.

    No, stats don’t measure character, chemistry, or other intangibles. They measure results and compare them to the results of other agents engaged in a particular activity. But if you have a group of teams that produce a similar number of wins against similar competition, on the whole, when they began to play one another, you’d assume that the ones that beat their best opponents by the largest margins most frequently would prevail more often than not. And if you did so, your assumption would be rewarded more ofthen than not too.

    Winning close games does not point to being less fundamentally sound. You say that is what is attempting to be proven. Those two events – close games vs. being less fundamentally sound have nothing to do with one another. The entire discussion assumes that connection to have validity. I have coached several teams in each sport … baseball, football, and basketball. And the best teams I’ve ever coached played a lot of close games, but had the knack for regularly winning close games (and did not regularly blow people out).

    This is a nice anecdote, but completely irrelevant. More on why in a second…

    Winning more close games doesn’t point to a lack of fundamental soundness. Playing more close games than what teams similar to you does, however. The idea isn’t to quantify what is, but what isn’t. What is it that you lack that is allowing weaker teams to hang with you more often than your peers? If it’s your style to play in a way that keeps games close inherently (like playing slowly), then yes, you’re going to wind up playing more close games than teams that don’t, but that’s not what the comparison is based on. If you’re not like your peers, that’s meaningful. The fact that you’d refer to the result as a ‘knack’ just goes to show it’s a factor you don’t consciously control. In fact, in this context, you can use the terms ‘knack’ and ‘luck’ interchangeably. KU has the most ‘knack’ this season of any D-1 team. In 1988, their ‘knack’ got them title. But however you describe it, I would think you’d be disconcerted with your team if they’re regularly putting in close performances against teams they should handle easily.

    UConn was 40th in scoring margin last season. But I understand the circular nature of this discussion … “oh, that’s not what we’re trying to show.” Or “the NCAA tourney is luck.” Or whatever.

    There’s nothing remotely circular about this discussion. Of course the NCAA tournament isn’t ‘luck’ or ‘all luck’ or anything of the sort, but I think anyone would be able to plainly see that luck, or the term I prefer, variance, plays a bigger part in determining the NCAA tournament champion than it does with say, a conference champion. Because it is single elim, you have less of a margin for error in the tournament, and thus events that are totally out of ones control, such as a bad call in the example above, have a bigger impact on that outcome than in other circumstances.

    Here’s what the article said: “A measure of the deviation between a team’s actual winning percentage and what one would expect from its game-by-game efficiencies. It’s a Dean Oliver invention. Essentially, a team involved in a lot of close games should not win (or lose) all of them. Those that do will be viewed as lucky (or unlucky).” That is just complete b.s. A team “should not win (or lose) all of them”? Right, they “should not.” It’s just a fundamental flaw to assume that it is “luck” when they do. The mistaken premise is the assumption that they “should not.” That does not consider that good teams, the best teams, actually “should.”

    Do you actually understand what Oliver and Pomeroy are saying? I’m not trying to be condescending, but your comment makes no sense. It might be true that given two statistically similar teams where one has played and won a lot of close games, and the other hasn’t that the team winning close games is actually better. It might be true that it’s because of character and heart or whatever. But when you’re talking about 351 teams and 15 seasons, it becomes harder to swallow that everyone who’s won more games than similar teams playing similar schedules is just more virtuous than everyone else.

    Kenpom’s statistics rate which teams are the best based on the results they actually produce, so he’d agree that the best teams should win close games more often than the lesser ones, but he’s already taking that into consideration. It’s when they are actually playing more close games than comparable teams and winning that he’s quantifying as luck. But perhaps it’s better to defer to what the actual inventor of the metric himself says:


    The principle behind the method - that a team’s won-loss record is closely related to the number of points it scores and allows - should be no surprise. It just makes sense that teams that win 60 games outscore their opponents by more than teams that win 50 do. However, one of the things that the Correlated Gaussian Method has added is that consistency also plays a role. Teams that win 60 games do not have to outscore their opponents by more on average than teams that win 50. They just need to be more consistent from game to game.

    On the other hand, luck resulting from ‘well-timed scoring’ is a weak force in the NBA. It doesn’t separate the good teams from the bad teams; it just separates two teams of similar quality. Taking the luckiest and unluckiest teams in the NBA, we usually find a total deviation of 10 to 13 wins. Luck has a place in basketball, just as the weather has a place in football and as Wrigley Field has a place in baseball. Each has an effect on the game, but, in the long run, the better teams win with or without the advantage or disadvantage of such factors. (In the short run, like the playoffs, luck can be pretty important. Witness the 1995 Houston Rockets.)

    Occasionally luck plays a major part in a team’s season. The '85-86 Clippers won 32 games, while their point totals led to an expectation of only 21 wins. A third of their victories (!) came out of the Twilight Zone. The '86-87 Clippers came back to reality, going through a pitiful 12-70 season in a daze. The '86-87 Warriors exceeded their Pythagorean projection by eight games, winning 42 instead of 34 games. They, too, crashed the following season, winning only 20. Both the Clippers and Warriors lost key personnel in their follow-up seasons, but neither ever showed any signs of life anyway. This sort of collapse can be seen throughout the history of basketball, but it’s also seen in baseball (and probably other sports). The baseball people called this the Johnson Effect. It’s the same effect in basketball so it gets the same name.


    It assumes that good vs. luck is defined by the margin of victory. Only someone who has not been around sports would even consider that as a measuring stick. It ignores the concept of consistency, which is a key component of great teams.

    NO, not even close. He’s assuming that teams that are more efficient offensively and defensively will produce greater margins of victory (adjusted for tempo) on average than teams with similar styles that have played similar opponents. Consistency is entirely the basis for this conclusion. If it were just margin of victory, you’d have a point, but it simply isn’t.

    Look, I know I won’t convince you. So I’m not even trying.

    You won’t convince me because your arguments are uncompelling, not because I refuse to be swayed. If you have a valid point, raise it. I’m all ears.

    Not sure how much you’ve coached, or been in that situation. But you certainly approach it with a certain arrogance … perhaps one that is lacking from practical experience.

    Arrogant, eh? Pot, may I please introduce myself, Mr. Kettle. I bet we both seldom walk into a room and think we aren’t the smartest guy there.

    I’ve seen this stuff first hand. I coached a basketball team, and we rarely won by double digits. But we never lost. We beat teams that would blow out the teams that we beat by a handful of points. Same in football. Style of play dictated that in some years, we were going to have smaller margins of victory. And certainly in baseball, where a pitching/defense teams … such as the Royals … are not going to win by large margins. But the Royals, actually, were not a “lucky” team. They had perhaps the surest of things, a lockdown bullpen. The baseball team I coached this past summer couldn’t seem to blow anyone out, but we kept winning, and kept getting tourney trophies. We were consistent.

    I don’t particularly care if Ken Pomeroy has never even dribbled a basketball in his life, but I’m going to go out on a very short and steady limb and guess that you, me, and Pomeroy have coached the exact same number of D-1 basketball teams as one another. Do I have that right? It makes no difference to whether or not his assertions are valid. What matters is how consistently his model makes valid predictions, and what he claims that rate to be. No more, no less. But now to revisit the issue of UConn and raise that of the Royals.

    It’s incredibly easy to say, now that the season is over, that it was obvious or predictable that such and such an outcome could result. Anyone can do it. It takes no insight, so your assertion that the Royals weren’t ‘lucky’ for factors that you can now name holds no weight. Predictions are what matter and you seem to believe that coaching experience is required to make accurate predictions about who future champions will be, and that statistical predictions are rubbish. Why, then, did no pundit who actually was a former D-1 coach predict UConn’s ascension to greatness prior to the dance? Not one even had them in their Final Four predictions. With the Royals and the Giants, it was the same story. Not a single professional pundit or former coach picked either team to make the World Series, let alone both of them. In fact, I can’t find even one example of a pundit advancing both teams beyond the first round of the ALDS and NDLS respectively. Pointing out that UConn, UK, the Royals, and the Giants were all ‘lucky’ should be a no-brainer regardless of who’s insights or intuitions you trust. Nobody saw it coming for a good reason. It was highly unlikely.

    When one connects margin of victory and luck, it denotes a lesser level of skill or “earning it.” And a lower reliability in repeating the result. And that just isn’t the real world of sports. It ignores one important variable – consistency. Great teams have consistency. And that ain’t luck.

    Luck and ‘earning it’ are mutually exclusive ideas. I know that UConn earned their national championship because they have a banner ready to hang that says so. The Giants have a trophy in their stadium. As I’ve already said, consistency is factored in with the luck stat. It’s all predicated on the results that statistically similar teams produce. Consistency is accounted for by default because the data derives from actual results. If it wasn’t, advanced statistical models for anything, sports or otherwise, wouldn’t work. This isn’t to say that statistical models are flawless or that statisticians don’t make mistakes. They do, but they try to account for that, and these models are constantly being revised in order to make more accurate predictions. When a statistician says that he’s 90% certain an event will take place, he’s also saying he expects to be wrong about 10% of the time. The worth of a model can be shown when, over time, the predicted value does or does not indeed correlate to that assertion.

    I think, honestly, that you’re umbrage at the descriptor ‘lucky’ is completely irrational. Being lucky doesn’t diminish your accomplishments. You can be a great coach, and still be lucky. I’m very willing to bet that all those games you coached with close margins of victory you still never escaped defeat every time, probably losing at least once because a ref or an ump made the wrong call. If have gone undefeated in all your endeavors, great, but then do us all a favor and get rid of that bum Self because I and every other one of the Jayhawk faithful are champing at the bit for a run of NCAA Championships that would embarrass the ghost of John Wooden.

    As I said above, luck, by it’s very definition, refers to things that one can’t actually control, but that those who do better at managing what they can control are more often poised to capitalize on good luck, and insulated from bad luck, and that the people who don’t or won’t control things that they could are the ones that constantly bemoan it. The only reason to think that there’s no such thing or that those who profit from it are somehow less deserving (or the corollary that those who failed to do so are entitled to recompense) is if you truly believe that all factors within an outcome are yours to control, but I somehow I can’t convince myself that the portion of some landfill that is dedicated to my losing Power Ball tickets doesn’t exist because of my lack of gumption.

    @JayHawkFanToo

    This is a fundamentally flawed premise because it assumes that you are playing the same competition and luck is allowing you to win. 20-30 years ago a game between a major conference program and Mid-major was a one sided affair; now…not so much and mid-majors beating a major conference team are common place; scores are getting closer and closer every year a result of the parity that exists in the sport . If KU switches to an all punch bag schedule, they would win by 20+ points most every game or it could switch to a tougher schedule (like now) where it still wins by virtue of being the better team, but score margin would only be in the single digits, does this mean that KU is lucky?

    As I said above, of course not. But SOS is already factored in. You can’t just pull one stat out of a set of data and say it’s bs while ignoring the way it’s compiled. The whole purpose of the stat is to identify why you have an outlier and how likely that is to last. There are a lot of ways to interpret what the stat means. @Jesse-Newell has said he thinks it denotes toughness, guys hanging in there and gutting out wins. I interpret it to mean just the opposite. How man times have you seen KU under Self run up a huge lead only to get complacent and allow the opposing team to get back into the game? How many tournament exits were predicated or punctuated by not stepping on the throat of an opponent and then falling apart at the last second? Hell, in 3 of 5 meetings with MSU under Self, Kansas has had a considerable lead under the 6 minute mark and watched it slowly be picked apart.



  • @JayHawkFanToo & @HighEliteMajor

    You both make great points here. I tend to be attracted to the sports analytics because it’s an interesting way to look at the game and suggests that we might be able to predict outcomes more accurately. But there are lots of human factors (peaking at the right time, a half-court shot that goes in, a bad call at a bad time, an injury, a suspension, a breakup with a girl-friend…) that influence the game and confound analytical models.

    This thread is a microcosm of the debate that has raged in the wake of Moneyball.

    In short-- you’ve illuminated some possible holes in the luck metric. I think all the assumptions you have questioned are fair. To me, that means they need to do some more work on it, not that luck doesn’t exist.

    @konkeyDong called it “noise”… but whatever you call it, I believe there are statistical irregularities which are more prone to effect the outcome of a game when games are close than when they are not.

    The biggest issue I now have with KenPom’s Luck metric (and I acknowledge there may be many), is the assumption that 10points is the threshold for the “luck” effect.

    This “luck” metric does not take into account style of play (as @HighEliteMajor eloquently explained) which could result in games with fewer possessions where the score might be in the 51-70 range vs teams that play a style that generates more possessions and scores in the 71-90 range. Games played in the 51-70 range are statistically going to have fewer points in the margin of victory than games in the 71-90. Put another way… a 9pt victory in a 51-60 final score is a greater margin of victory than a 9pt victory in an 81-90 game. The luck metric doesn’t seem to adjust for this.

    Anyway, I appreciate the perspectives and critical thinking on this thread. You’ve given me a deeper understanding and encouraged me to think differently.



  • @konkeyDong

    You wrote…

    "There are a lot of ways to interpret what the stat means. @Jesse-Newell has said he thinks it denotes toughness, guys hanging in there and gutting out wins. I interpret it to mean just the opposite."

    And this defines the fallacy of the approach. Math, and by extension statical analysis, are by definition "exact sciences " and as such, the results are what they are, unbiased and not open to interpretation. The fact that you see it the exact opposite than Newell would indicate that it is not the result of an objective approach but a subjective and biased one and hence, open to interpretation. An interesting excessive, no doubt, but a pretty useless one nonetheless.



  • By the way, I ran a statistical model to please @konkeyDong and I have found that Greene’s effort vs. Georgetown was 76.25% “luck” (but my model is only 90% accurate). You can’t expect all of your three point shots to go in, of course, so a statistical portion of those makes are “luck.” I determined that in the next 5 games, Greene will shoot 29.4% from three, as he will revert to the mean. Of course, I don’t know what the mean is for Greene so I ran multiple other models for Greene, based on a sample of players similar to Greene. The chances Greene shoots better than 29.4% is 41.2%. If he does shoot better than 29.4%, then we shall consider that “luck.” Why? Because I say it to be true. And because only “lucky” players shoot better than their statistical mean. Greene’s shooting over 50% from three this season. That is 12.2% luck, because the sample player of Greene’s ability shoots 37.8%. So, Greene’s success has largely been premised upon “luck.”

    I also found that there is only 35.8% chance that KU will make its three point shots going forward. That, of course, is because they have made that exact same % thus far this season. My model has a +/- error of 4.8% because you just never know what happens when the ball goes in the air. Or whether coach Self will pull a shooter who might make a shot before he actually takes it. Regardless, anything beyond the 35.8% rate is considered “luck”, again with a 90% accuracy rate.

    I will tell you that this statistical analysis is not useless. While it proves nothing, and may not apply to certain examples, and may not reflect the realities of sports and competition, and seeks to explain subjective influences using objective information, it is a valuable consideration, at least 68.2% of the time.



  • @JayHawkFanToo said:

    "There are a lot of ways to interpret what the stat means. @Jesse-Newell has said he thinks it denotes toughness, guys hanging in there and gutting out wins. I interpret it to mean just the opposite."

    And this defines the fallacy of the approach. Math, and by extension statical analysis, are by definition "exact sciences " and as such, the results are what they are, unbiased and not open to interpretation. The fact that you see it the exact opposite than Newell would indicate that it is not the result of an objective approach but a subjective and biased one and hence, open to interpretation. An interesting excessive, no doubt, but a pretty useless one nonetheless.

    Statistics is simply the science of applying mathematical calculations to a set of data to determine future probabilities. It’s inherently based on empirical evidence. Models are proved out by how well they match reality over time. If my comment left you with the impression that I believe the luck stat is somehow open for interpretation or somehow not an objective measure, that’s poor wording on my part. I don’t. Jesse is making a mistake because he’s being biased in reading the data. Team’s can’t force themselves to be lucky. Over time, a team exhibits that exhibits luck over a particular period of time will also exhibit the opposite and it will average out. There isn’t a way to manufacture luck. ‘Toughness’ isn’t translating itself into something else. Self has just had a few teams win a little more often than statistically probable. That’s all that’s being suggested by the stat and all I’m trying to point out. What I probably should have said is that you can come up with lots of hypotheses with what the causes of luck are, but there is only one answer and it’s something that can be proved out with data.



  • @konkeyDong And by the way, I’m just kidding around with you on my last post. No malice, as jb would say.



  • As though the basketball gods were following this thread… they gave us a game to fuel the debate: Are we good or lucky with a 3pt win over Utah?

    I want to say it was more goodness than luck… but whew. Who cares? It’s a big win!

    I officially believe this team can be a sweet 16 team… and may develop into an elite 8 team… Potential to be a final four team when they are hitting on all cylinders, as they did in the first half.


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