Archive for Sports

2013 Robert Horry Memorial Playoffs All-”Rising Stock” Team

The 2013 NBA playoffs are over, and it’s time to reflect. In my opinion, one of the most fascinating lenses through which to view any NBA playoffs is in terms of players whose stock rose the most with the spotlight on them.

It felt like this playoffs featured more big names turning into stars, and more marginal guys turning into big names, than in the past few years. And, as often happens, it seemed like every time one surprising star got eliminated, it seemed that another emerged in the next round.

(I could have named this team after any of the dozens of players who have made names for themselves in the postseason, but I chose Robert Horry because I couldn’t think of anyone whose success was more closely tied to the playoffs than Big Shot Bob. And yes, I know Horry is not dead.)

So here is my 2013 Robert Horry Memorial* Playoffs All-”Rising Stock” team:

Stephen CurryStephen Curry – Guard, Golden State Warriors

Do you remember the first round? It was a while ago. In the first round, Curry was THE guy in the NBA. Nobody was more exciting for the first six games of the playoffs (plus that ridiculous 18-35 performance in 58 minutes in game one against the Spurs before he got worn out and/or injured). Curry averaged almost four three-pointers a game while shooting 44% from beyond the arc, 47% from the floor, did not miss a free throw in the Denver series, and almost managed to dish out almost 10 assists per game.

Mike Conley – Guard, Memphis Grizzlies

This was the playoffs where everyone realized that Memphis may not have wildly overpaid when they signed Conley to a five-year, $40 million extension a couple of years ago. We came to appreciate his defense, and the way he works the pick-and-roll. He didn’t set the world on fire with his shooting in the postseason, but he also didn’t turn the ball over, distributed nicely, and rebounded. Fans of franchises without all-star PG came out of the playoffs dreaming of this guy.

Danny Green – Guard, San Antonio Spurs

You’re sick of the Danny Green story by now: cut numerous times, played in the D-League, etc. But for five glorious games in the NBA Finals, Green was the best outside shooter in the NBA. At one point, he was 25-38 from three in the series. We knew Green was dangerous, but trending-on-Twitter-multiple-times dangerous? No chance. The only question is: do you now claim to have known Green had this in him before the series started, or are you honest?

Nate Robinson – Guard, Chicago Bulls

It was a playoffs full of amazing individual games, and until game six of the finals, perhaps none was more amazing than Chicago 142, Brooklyn 134 in triple overtime. This was “The Nate Robinson Game.” 34 points on 14-23 FG and a completely silly flying bank shot. Robinson, along with Joakim Noah, epitomized the underdog Bulls. 17 points on 51% shooting in round one meant that we all wanted to see what highlight-reel play this diminutive point guard would make next.

Kawhi LeonardKawhi Leonard – Forward, San Antonio Spurs

By the end of one of the best NBA Finals ever, was Kawhi Leonard the most dependable player on a dependable team? I say yes, despite the infamous missed free throw in game six. He averaged a double-double while guarding LeBron James for much of the series, and seemed to pour in big shot after big shot after key defensive play. A second-year SF who averaged 55% from the floor and 40% from three in the playoffs, plus 8.7 RPG? Yes please.

Paul George – Forward, Indiana Pacers

It’s possible that nobody’s stock rose higher in this playoffs than George’s. Even though George was an all-star this past season, playing in Indiana limited his exposure. But in taking the Heat to seven games, George was, in a word, ridiculous. He hit from anywhere and everywhere, going for 48% FG and 44% 3P in the Heat series (twisting the knife for many Jazz fans). It’s the best when a young guy already on a star trajectory makes “the leap” on the biggest stage.

Chris “Birdman” Andersen – Forward, Miami Heat

I know this is the choice you all are going to hate. Birdman is the oldest guy on this list by far, and it isn’t so much that his stock rose as an asset, but he definitely became something of a household name. In part, this is because everyone on the Heat is a celebrity (especially those with tattoo turtlenecks), and a bunch of casual fans now know this guy. But it’s also because Andersen at one point made 17 straight field goals. Miami definitely doesn’t win game one against Indiana without his physical play at both ends.

Roy Hibbert – Center, Indiana Pacers

Hibbert is another guy who, like Conley, engendered skepticism when he signed a four-year, $58 million extension last July. It didn’t help matters that Hibbert was then lackluster for much of the regular season. But he upshifted when it mattered most, averaging more than three blocks per game against the Knicks, then turning in a 22.1/10.4 line against the Heat. His block on Carmelo Anthony late in game six against New York and the charge he drew by going straight up against LeBron in game six of the ECF were things of beauty. With Dwight Howard falling apart physically and mentally, is Hibbert the best defensive center in the NBA?

Marc Gasol – Center, Memphis Grizzlies

It was a great postseason for Memphis overall, but perhaps nobody rose in prominence more than the large Spaniard. The fact that “Did Memphis end up with the better Gasol brother after all?” was a legitimate question among NBA fans by the end of the second round should tell you everything you need to know. 17.2/8.5 for a big man with range who can block shots is a solid postseason effort.

Honorable mention: David West (IND; great playoffs but overshadowed by George and Hibbert); Klay Thompson (GSW; overshadowed by Curry), Chandler Parsons (HOU; had a good series, but didn’t stick out the way that others on the list did), Kirk Hinrich (CHI; because people realized that the Bulls don’t win without him), Chris Copeland (NYK; ridiculous from three, and a fan favorite, but his team lost the only series where he played significant minutes), Boris Diaw (SAS; against all odds, had a decent NBA Finals and avenged himself from all of those “Fat Boris Diaw” jokes). 

So that’s the team. The fact that there was Did I miss anyone? Let me know in the comments.

 

Staying Home

It happened again. Another loudmouth on Twitter proclaimed himself the Commissioner of Being a Good Sports Fan and declared, essentially, that none of us has any right to complain about our teams if we are not going to the games. Because, of course, “true fans” go to all the games.

True fans do this, true fans do that.

It’s not quite the dumbest thing I’ve ever heard, but it’s close. And people keep saying it.

First of all, I am not aware of a cabinet-level position that gives anyone the right to decide what makes a true fan. So please do us all a favor and stop pretending that what you say matters (although, to your credit, it did inspire this blog post, so you’ve got that going for you).

But, second, let me tell you all the reasons I typically avoid LaVell Edwards Stadium like the plague despite being, I think, a pretty huge BYU football fan:

  • At home, I have an HD TV.
  • At home, I have a remote control so I don’t have to watch freshmen make fools of themselves trying to kick field goals during commercial breaks.
  • At home, I have free food that is better than anything you pay $45 for at the stadium.
  • At home, I have a couch, which is extremely comfortable and inviting unlike the metal benches (with the roughly 36 square inches of space they allow you).
  • At home, I do not have to be surrounded by idiots yelling at the coaches, players, and officials at the tops of their lungs despite the fact that nobody who can hear them cares what they have to say.
  • At home, I can show up for the game whenever I want with no traffic, and when the game is over I don’t have to sit in the mass exodus for an hour.
  • At home, I actually get cell service so I can talk to a theoretically unlimited number of friends about the game while I am watching it.
  • At home, I have every stat in the world at my finger tips; I can analyze the game from every angle that you can in the stadium and then some.

So what’s the argument against staying home? The “thrill” of being surrounded by 74,000 of your closest friends? Yeah. . . no thanks. Not only does that not do it for me, but it also has nothing whatsoever with being a “true fan” (if there is such a thing). But hey, knock yourself out, Mr. Commissioner.

Arbitrariness. Such a confusing thing.

Good GM, Bad GM: Late Bloomers and Draft Prowess

I don’t expect to receive an answer to this question since I know there only three of you out there reading my blog, but I’m going to ask it anyway.

Let’s say you’re evaluating an NBA GM’s drafting/scouting ability. Should he get credit for picks who ultimately turned into solid players, but did so only after leaving the team that drafted them? Take, for example, Kris Humphries. I know you think he’s overpaid, but don’t forget that after his two seasons with the Jazz, everyone believed he was a total bust. He notched just 0.1 total Win Shares during his first two seasons in the NBA. But fast forward a few seasons and Humphries has tallied a totally respectable 10.7 Win Shares while averaging a double-double over his past two seasons with the Nets. So should Kevin O’Connor get credit for drafting Humphries, a serviceable NBA starter, even though the Utah Jazz never benefited directly from that pick?

This is vaguely similar to questions digital marketers face around multi-touch attribution. If a user arrives at your site by clicking a paid search link in Google but does not purchase, and then a month later arrives at your site by typing your address into his browser and this time he does purchase, should that original paid search click-through get credit? If so, how much? It’s a little different because most NBA players would have been drafted eventually anyway; if Kevin O’Connor hadn’t picked Humphries, someone else would have, and we’d be wondering whether that person deserves credit.

I can see arguments both ways. A GM who picks a player who only pans out later in his career might have correctly read the player’s potential, and we should reward that GM for his vision. But a GM’s job is to deliver concrete wins to his team via the draft, and a late bloomer does not help his cause. In case anyone is out there reading, leave me a comment: what do you think?

Pickup Basketball Purism

I tweeted about this last night, but 140 characters just wasn’t enough for me to state my case regarding the scoring in pickup basketball. (I only tackle the really important issues on this blog.)

pickup basketballI love pickup basketball. In fact, the widespread availability of pickup basketball is one of the best reasons to live in Utah. Not only do we have YMCA-like fitness centers in every town, but on any given weeknight or weekday morning there is an 87.9% chance that there are four churches where guys are playing ball within a one-mile radius of any given location along the Wasatch Front. I love that every Monday, Wednesday, and Friday morning at 6:00 AM I drive for two minutes and I’m at basketball. Same thing on Thursday nights. Oh, and sometimes I play during lunch at work. (Despite all of this, I’m pretty terrible.)

What I don’t love is keeping score by 1s and 2s. You know, what would normally be a two-point field goal in high school, college, NBA, or really any organized form of basketball becomes a one-pointer, and a three-pointer counts for two.

Here’s my argument:

  1. Basketball—real basketball—has what I consider to be a fairly simple scoring system. If it were, say, pickup figure skating, or even pickup tennis, I could see wanting to simplify the score-keeping. But honestly, how hard is it to credit each team with two points for any basket inside the three-point line, and three points for any basket outside it? Am I missing something here?
  2. More importantly, counting by 1s and 2s fundamentally changes the game. By making a three-pointer worth twice as much as a two, instead of 1.5x, you’re possibly incenting people to play outside; you’re giving them a good reason to play bad (i.e., not very fun) basketball. When a three is a three and a two is a two, the upside of jacking up a bunch of threes probably doesn’t outweigh the upside of good ball movement and working for a decent shot inside. But when you’re counting by 1s and 2s, suddenly it might make more sense to play three or four guys around the arc and hoist up three point tries all game. Three-pointer after three-pointer is great for the shooter(s) when he’s hitting. . . and completely annoying for everyone else. Everyone hates the guy who brings the ball up the floor and then calls his own number by pulling up for a three. I’m not saying people consciously decide to play differently when counting by 1s and 2s, but the possibility is there (and it doesn’t need to be; see point #1).
  3. Along these same lines, remember, there are no free throws in pickup basketball, so even if you’re counting by 2s and 3s in a pickup game, the incentive to shoot a lot of threes is already higher than it is in organized basketball. Let’s say I’m an NBA player who shoots 50% generally from inside the three-point arc and 40% outside of it. Some fans look at this and say, 40% * 10 three-point tries = 12 points and 50% * 10 two-point tries is = 10 points, so shouldn’t you always take the three? The answer is no, primarily because this faulty analysis ignores the fact that in organized basketball you are far more likely to get fouled and produce valuable free throws when shooting inside the three-point line (driving to the basket or helping to create shots for teammates), so your two-point tries are more valuable than they seem on the face of it. The possibility of creating free throws does not exist in pickup basketball, whether you’re counting by 1s and 2s or whether you’re counting by 2s and 3s, so you’re already more incentivized to play outside than you normally would be; why make things even worse by increasing the value of a three-pointer unnecessarily?

As you can tell, I’ve given this some thought. And maybe that’s because I’m too much of a purist; the NBA and college ball have been playing with 2s and 3s since the early 1980s, and the ABA had it even earlier. It just seems silly to change something that works so well.

So now I am counting on you, all three of my blog readers (hi mom!), to tell me what I’m missing. Who invented counting by 1s and 2s and why did they do it? Do you have a preference and why? Did I miss something important?

NBA Team KPIs

Bear with me for a minute, basketball fans.

If you work in digital analytics, you are familiar with the concept of the Key Performance Indicator (KPI). A KPI is a piece of data, shown over time, that gives you immediate insight into how your business is performing against your goals. Sometimes they are very general (such as Orders per Visit, a.k.a. Conversion Rate) and sometimes they are more specific (for example, Bounce Rate for visitors coming from search). These things are lifeblood of some business goal you’ve set. A business typically has several KPIs that they monitor every day. And not every metric is a KPI; a common rule is that it isn’t a KPI unless it’s something that, if decreasing below acceptable norms, would cause your business to take immediate action to rectify.

If you don’t work in digital analytics, but you are an NBA fan, we can finally explain KPIs to you using NBA statistics, a language you probably already speak. Here it is, courtesy of basketball-reference.com:

How do basketball teams win games? While searching for an answer to that question, Dean Oliver identified what he called the “Four Factors of Basketball Success”:

Shooting (40%)
Turnovers (25%)
Rebounding (20%)
Free Throws (15%)

The number in parentheses is the approximate weight Mr. Oliver assigned each factor. Shooting is the most important factor, followed by turnovers, rebounding, and free throws.

The article goes on to explain that each of those four factors is expressed in a rate: Effective Field Goal Percentage, Turnover Rate, Rebounding Rate, and Free Throw Rate. These have all the markings of good KPIs. I want to be as good as I can be in each of those four areas, and if I succeed, I’m almost definitely going to win basketball games.

If I were compiling a basketball team, or coaching a basketball team (or advising a basketball team on how to begin analyzing itself), those would be my first KPIs. Those are the metrics that I would use to gauge success. And while basketball, like business, has one metric that trumps all others (for basketball, it’s wins; for business, it’s profit), these are strong leading indicators of a team’s ability to win.

So, basketball fan, think of your digital analytics friends as something like basketball coaches who are looking at effective field goal percentage and benching that wing player who won’t stop taking threes early in the shot clock, or a GM who sees that his team is weak in rebounding and therefore targets an athletic big man in the NBA Draft. It’s clear to an NBA fan, looking at how his team is performing in each of the Four Factors, how a coach or GM might address a deficiency in these areas, just as analysts are great at coming up with recommendations when a KPI is struggling and needs to improve.

In fact, that’s the great thing about KPIs: they provide a really nice, simple jumping off point for analysis. Why were the Jazz so bad at eFG% this past season? We can begin to answer that problem for management with some very specific advice, especially when we add in analysis of shot location and lineups/rotations. Why are my web site visitors who arrive after performing a Google search leaving so quickly? We can look at that user segment and see what they’re doing and where they are running into roadblocks, or look at our landing pages and analyze them for effectiveness. Same thing.

So now you’ve got something to talk about with your digital analyst friends. And digital analysts, you can ask your NBA friends how their team’s turnover rate has been trending lately. Your next cocktail party is sure to be a smashing success!

Sloan Sports Analytics Conference: Day Two

As I have been tweeting, blogging, and updating Facebook about the Sloan Sports Analytics Conference, I keep hearing comments like: “I wish I could go, but I will never be able to” and “this is definitely on my bucket list now.” A few things about this. First, at $500 for non-student admission, it’s a bargain; even with hotel and airfare I’ll bet most of you could do this conference for well under $1,500, and it will be a truly memorable experience. So start saving a few dollars a week in a cookie jar today. Second—and I don’t think people realize this—anyone can attend. You don’t need to work for ESPN or an NBA franchise. My sister has a friend who does Account Management for Google, but he loves sports and analytics so he pays his own way to fly out every year from the Bay Area. All are welcome.

The other thing which pleasantly surprised me (I touched on it yesterday) is that you do not need to be a Ph.D. candidate in advanced statistical modeling or econometrics to thoroughly enjoy the conference. There were some sessions that really stretched that area of my brain, and others that were accessible even to non-sports fans, let alone non-academics. So don’t let that scare you away.

Highlights and thoughts from day two:

  • There was a request on Facebook to hear more about Bill James. As the godfather of the Sloan Sports Analytics Conference, he was definitely one of the stars of the show. Unfortunately, I didn’t feel like he shared much new information about himself or his work. Simmons did a live BS Report with James at the end of day one, during which they rehashed his rise from unheralded part-time stats geek to patron saint of sports nerds, but it’s all stuff we read about in Moneyball. Day two featured a “Boxscore Rebooted” panel with James, John Thorn (MLB historian), and John Dewan (baseball info solutions), but most of it is so widely accepted in these circles at this point (“Wins for a pitcher is too arbitrary! The Internet makes analytics easier!”) that I barely took notes. To be honest, it felt really strange to be so nonplussed by this guy who quite literally invented advanced baseball analytics. In talking to a few other attendees, I got the sense that I’m not the only one. We all have tremendous deference for what Bill James has given the world, but he does not seem to be on the bleeding edge of sports analytics anymore.
  • The conference (at least this year) leaned heavily toward basketball, probably because the millennials who dominated the conference are in a demographic where the NBA is excelling, whereas I believe I heard that the average baseball fan is between 45 and 55 years old.
  • I reviewed three basketball-themed research papers in yesterday’s post, but the best was yet to come. The two best research papers by far (in my mind) dealt with “spacial analytics” in the NBA, meaning the study of where the 10 players and the basketball are placed on the floor (or in the air) when key events occur, as opposed to pouring over isolated numbers to obtain insight. Jared Dubin of Hardwood Paroxysm did an excellent job reviewing these two presentations (he even has screen captures), so I won’t go into too much detail.
  • I will add that I thought the rebounding study was not fully matured—it presented a ton of potential to help teams understand how to position players in rebounding situations, but it wasn’t quite there yet. Key Insight: Teams’ offensive rebounding percentage decreases significantly the farther the shooter is from the basket, until you get to the three point line. Behind the three point line, offensive rebounds are more common than for mid-range jumpers. Especially considering that neither a mid-range jumper nor a three is likely to generate a lot of free throws, it stands to reason that mid-range jumpers are the least effective shot on the floor (which we’ve all kind of known for some time, but it’s nice to have data to back up the theory).
  • My absolute favorite research paper was Kirk Goldsberry’s creation of the “Range %” number, a statistic which tells us the percentage of spots on the floor where players are effective scorers (defining “effective scorer” as “one point per FGA”). The average NBA player is effective from 17.2% of the 1,284 spots on the floor that Goldsberry measured by breaking the floor into a grid. Even though Tyson Chandler leads the NBA in FG%, he is far below average in Range %, scoring effectively from just 4.3% of the floor (not that anybody thinks Chandler’s high FG% means he is a great shooter). Dubin recaps the top few players in Range %. I was mildly surprised that Steve Nash beat out Ray Allen for the top spot (using data from 2006-2011), but mostly the data confirmed what you would expect in terms of the most comfortable shooters and least comfortable shooters. Key Insight: I can’t express this in terms of a specific recommendation, but Goldsberry’s most immediately applicable contributions are “heat maps” which show exactly where players are effective scores, as well as where they are less effective but still love to try. If I were a coach, I would buy Goldsberry’s technology (he did have a chance to share his methods with Mark Cuban at the end of the conference, so I assume the Mavs will be employing it shortly) and try to get my defense to force opposing scorers to the spots on the floor where they can be coaxed into shooting despite low effectiveness. Similarly, I would design plays that put my players in the best position to score from spots on the floor where they shoot well. It’s not rocket science, but I believe it would work. Isn’t this the kind of thing that Shane Battier has been doing for years? (And where has he been getting his data? Presumably just from video scouting. Goldsberry’s method is more complete.)
  • Best panel of the entire conference in my mind was Saturday’s “Fanalytics” featuring Bill Simmons, Jonathan Kraft, Tim Brosnan (EVP Business, MLB), Nathan Hubbard (CEO of Ticketmaster), and John Walsh (EVP, ESPN). It was supposed to have Mark Cuban on it as well, which would have been even better, but Cubes was running late. The whole thing was about improving the fan experience through technology. This one deserves sub-bullets:
    • The NFL is improving in every possible metric except for fan attendance. Today’s fan needs to be able to use the Internet on mobile devices (for Twitter, fantasy football, live video of other games, etc.) or they won’t come to the game. Mark Cuban doesn’t want people using their cell phones at NBA games, but the NFL recognizes that its whole fan experience model is different because of the pace of the game (frequent stops and starts) as well as the nature of the NFL (everything is happening all at once, on the same day of the week).
    • Kraft: “We’ve spent $2-3 million [to upgrade WiFi infrastructure at Gillette Stadium] in the last couple of years.” He continued, saying that to allow 70,000 people to stream video over WiFi at Gillette would cost “literally tens of millions of dollars.”
    • Simmons asked whether it would be feasible to charge different prices for tickets not just by section, but by individual seat. For example, one section at an NBA game might stretch from the baseline to almost mid-court, and why are those tickets priced the same? I had wondered this, since obviously the technology to price tickets on a seat-by-seat level exists. The answer is that if a fan sees that the guy next to him has a different face value on his ticket, he is likely to get resentful and angry. So they do it by section and live with the fact that this isn’t fully optimized pricing.
    • On the night of the AFC Championship Game, when Kraft wanted to relive Billy Cundiff’s missed FG, he went not to NFL.com, but to YouTube. This is surprising since the NFL maintains strict media rights, and the video was available on NFL.com. Why YouTube? Because a guy sitting in the endzone had the perfect angle to film the kick sailing wide left, and had uploaded the video. It was the best angle Kraft had seen. The lesson regarding NFL media rights and fan-shot video? “You can’t stop it, so you better start learning how to use it.”
    • TicketMaster operates both a primary ticket vendor and a secondary market vendor (TicketsNow), so they can use Omniture (nice shout out for my friends) to analyze ticket re-selling and compare with original sales. According to Hubbard, “Technology is showing us that our tickets are worth more than what we’re selling them for.”
  • Weird recurring theme of the conference was presenters’ inability to pronounce player names. The professionals did not have this problem, but the student researchers did. The two most egregious (and there were others) were the old classic “Da-RON” Williams instead of “DARE-in” and the even-less-excusable Kevin “Dur-ONT” instead of “Dur-ANT.” I mean, Kevin Durant is a top-three player. How can you be presenting on the NBA at a conference of sports nerds and not pronounce his name correctly?

I could keep going, but I need to stop somewhere. Suffice it to say, SSAC was an absolute blast. I can already see myself looking at certain aspects of game action and the sports world at large a little differently, in a good way. As I said to people numerous times during the conference, I will definitely be coming back, even if I have to plunk down my own money to do it. Sports and data, together at last. I think it’s a beautiful thing.

Sloan Sports Analytics Conference: Day One

It’s time for a different sort of analytics conference. The eMetrics festivities may not start until Monday on the west coast, but 2,200 sports dorks gathered in Boston this weekend to talk about sports analytics in the annual MIT Sloan Sports Analytics Conference.

What does this mean? Well, the sports world is full of data. Every dribble in basketball, every pitch in baseball, every snap in football generates new data points that we can analyze to understand the games we love. Last season, the Dallas Mavericks used advanced analysis to determine that their best starting lineup included J.J. Barea. They made the change. . . and won the NBA title. Analytics isn’t just for business anymore. That is what this conference is all about.

I won’t give a travelogue. Instead, some general, brief highlights and observations, from the perspective of a sports fan and digital analyst.

  • I know I just said that the conference is about analyzing the game and the players, but I was surprised at the amount of a.) sports strategy discussion devoid of data, and b.) sports business analytics (e.g., StubHub discussion ticket sales analytics; ESPN, NBC, and others discussing the world of media rights). There really is something for just about everyone.
  • There is a LOT of crossover between digital analytics and sports analytics. Maybe the tools are different, but the principles and challenges are the same. The basketball analytics panel featured a bunch of quotes that could have occurred at eMetrics or Omniture Summit:
    • “There is ‘counting things’ and there is ‘analyzing the things you count.” -Dean Oliver, ESPN Stats & Info
    • “Statistics do two things as a coach: they allow you to figure stuff out, and they allow you to communicate.” Jeff Van Gundy, ESPN analyst and former NBA coach
    • “”A lot of times in analytics, you don’t want to come out with a single number.” -Oliver
    • Oliver also talked about preparing insights for coaches, and said that he used “very few numbers” in these reports, instead translating everything into words that coaches (i.e., executives) could understand.
  • The people at this conference are crazy smart. 73 professional teams and something like 175 colleges are represented. I couldn’t even follow a lot of the math/statistics in the research papers. Unlike some conferences I’ve attended, I was mentally worn out by the end of the day. Great feeling.
  • This conference is a tremendous value. Admission was less than $500, in exchange for which you get to see the greatest minds in sports debate cutting edge strategy and analytics, and they are all accessible. If you ever wanted to ask ESPN’s John Hollinger a question about NBA analytics, this is the place to do it. People like Bill James wander the halls just like anybody else.
  • Jeff Van Gundy was a revelation today. Everything he touched was comedic gold. We’ve become familiar with his wit during the ESPN NBA broadcasts, but he was in fine form today, tossing out sardonic commentary at every opportunity. Everyone I’ve talked to has agreed that we all need more Jeff Van Gundy in our lives.
  • Just a few sports insights and possible recommendations, if you’ll indulge me. The great thing about sports analytics (for me) is that it’s REALLY easy for me to see the kinds of recommendations you might make based on the data.
    • One study of performance under pressure showed that the home team shoots free throws worse than usual in late-game, high-pressure situations, whereas the away team is unaffected. The reason, they hypothesized, is that the crowd tries to avoid distracting its own team in these situations by getting very quiet, which inadvertently allows the player to focus on the action of shooting, causing them to “overthink” the shooting motion. The away team has fans yelling and jumping during their free throws throughout the game, so there’s no real difference. Recommendation: Fans shouldn’t get silent during home team free throws late in the game.
    • Another study took the concept of plus-minus and broke it out by individual skills, making it possible to see how players impact their teams in very specific ways beyond top-level stats. They also demonstrated that some skills are synergistic, meaning that putting two players who excel in a certain area on the floor together make both players (and other team members) better in that area than they would be otherwise. The whole ends up greater than the sum of its parts. Recommendations: Find synergies and build rotations to maximize plus-minus in key areas. For example, put players who create turnovers on the floor together to get even more bonus turnovers.
    • Finally, a study attempted to show the relationship between  experience and playoff success; do teams require experience in order to succeed in the postseason, as is often assumed? The answer was no. Experience does not matter among players. Young teams fare as well in the postseason as experienced teams. However, coaches who have coached in the postseason before perform better in subsequent playoffs. Recommendations: Depending on your team’s situation, consider not overvaluing veteran leadership. Also, look for head coaches who have coached in the postseason (even if they haven’t won titles).

It was a very full day, but tomorrow looks great as well. Time for bed so I can fill my brain with more sports analytics tomorrow.

In which I defend the BCS (sort of)

Alabama-LSU

I’m not really defending the BCS, but I knew the title would grab some attention. Nobody defends the BCS.

I’m in favor of a playoff in college football. I also recognize that no system is ever perfect. March Madness snubs deserving teams every season, and some fan base is always up in arms over having to settle for the NIT. Major League Baseball just expanded its postseason field, either ruining the playoffs or suggesting that the previous format wasn’t quite right (depending on your preferences). Someone is always going to feel shafted, and championships don’t always tell us who the best team really is. I agree with my colleague, Mark, who said that the NBA is probably the closest to getting it right of any North American league.

Mad as hellLately, Twitter has been irate over the matchup in the BCS national championship this year. Undefeated LSU (13-0) is playing 11-1 (and SEC non-champion) Alabama. It’s not fair. It’s not fun. Suddenly, friends who hated Rick Reilly a few months ago consider him the peoples’ champion. I respect most of the arguments that I’ve heard against LSU-Alabama II, and I even understand most of them. But I don’t agree with any of them.

(NOTE: This has nothing to do with my feelings about Oklahoma State. I would love to have seen Oklahoma State have a crack at LSU, but not because they “deserve it” more than Alabama. Mostly, I just like Coach Gundy, I think it would be a good matchup, and I’m in favor of anything that might prevent the smug SEC from winning another title.)

What follows is a list of the most common points that I’ve heard against this national championship matchup, with some thoughts in counterpoint. Most of you are probably going to hate what you read. You will sit there foaming at the mouth and wondering how someone as stupid as I am is capable of enjoying sports. That’s fine. Please share your wrath in the comments and I will use them to enhance my self-disapproval. Here goes!

“BCS: Every game counts, except for LSU-Alabama on 11/5/11!”
This argument would make sense, if it weren’t the opposite of the truth. Think about it. It is because Alabama lost by three in overtime that we are even having this conversation. Do you think that we would be talking about the Crimson Tide if they had laid an egg against LSU and been blown out by 40 points? I certainly do not.

In college football, every loss is not created equal. Alabama proved that it belongs right up there with the best team in the nation by coming closer to beating LSU than anyone else. No, your real concern should be that round one of LSU-Alabama counted too much. If anything, people put too much stock in that game as a sign of Alabama’s superiority over everyone other than LSU. If you don’t want to see LSU-Alabama II, you should wish this game counted less.

And the coup de grace: If every game is supposed to count, shouldn’t Iowa State 37, Oklahoma State 31 a mere two weeks ago count, too? It’s easy to ignore that one when making this argument!

“We already saw this game, and it was boring.”
Look, you’re welcome to prefer a shootout, and Oklahoma State can definitely bring the offense. This is a matter of preference, though. Just because you didn’t like LSU-Alabama the first time around doesn’t mean that it shouldn’t happen again. It means that you didn’t like it. That’s as far as that goes.

Or maybe you just like variety. Variety is cute, but have I mentioned that we’re trying to decide a national championship? It seems backward to force a matchup in the name of variety when there is another matchup that ostensibly makes more sense (#1 versus #2).

I wasn’t bored, and I would watch that game again. That’s my prerogative, just as it is yours is to complain about a close game between the two best teams in the nation. (Sorry, I’ll tone down the passive-aggressiveness.)

“If Alabama wins, the ‘series’ with LSU will be tied, 1-1. We won’t have a clear champion!”
If you win the championship game, you are the champion. This really should not be disputable. You’re trying to say that it’s the entire body of work that makes a champion, which defeats the whole purpose of deciding the championship in a single game.

Rematches happen in championship games all the time in various sports. Why is college football the only one where a regular season game suddenly has the same efficacy as the championship game? To borrow an example that my friend Daniel Nielson used, if North Carolina beats Kentucky in the men’s basketball championship game this coming April, is anyone going to argue that they need a third game to determine which team is better? Absolutely not.

If we’re going to start insisting on tiebreakers, then I want to go back and play one for the 2008 Patriots, who beat the Giants to end their 16-0 regular season before losing to them a month later in the Super Bowl. (And don’t give me any “it’s-different-because-it’s-a-playoff” garbage. If you want to pretend that it’s a series, then be consistent. If “1-1″ isn’t decisive enough for you in college football, it isn’t decisive enough anywhere.)

If you win the rematch, you’re the champion. Whatever happens in the final game of the season is what counts.

“Alabama didn’t even win their conference!”
So what? The 2004 Red Sox didn’t even win their division. The 2009 North Carolina Tar Heels didn’t win the ACC tournament. In college football in 2011, is there a rule which stipulates that a national championship game participant must have won its conference? Oh, there isn’t?

“But it’s not fair!” Sure it is. It isn’t against the rules. Nowhere does it say that winning your conference gets you a leg up on the pile. I would be open to discussing just such a rule, but you can’t do it in the middle of the season.

Just be aware that if you institute this rule, it’s possible that you will have #1 playing #3 or even #4—what if the season had ended two weeks ago with LSU, Alabama, and Arkansas ranked #1, #2, and #3 respectively?—in the title game. Maybe you’re okay with that. Maybe you’re not. Either way, it’s something to consider.

Also, consider this: as conferences get larger, the odds of a legitimate contender not winning its conference increases. It simply becomes more likely that a single, massive body of teams making up a super-conference will contain more than one of the best teams in the nation. Maybe we aren’t headed toward the formation of super-conferences, but maybe we are. It’s a side note, but a compelling one.

“Did you even SEE what Oklahoma State did to Oklahoma?!”
I turned it off after Landry Jones’ second fumble, which made it 34-3 Oklahoma State. Yes, it was sheer domination. By my own logic (I weight late-season games far more heavily than early-season games), I have to agree that this outweighs Alabama’s trouncing of Arkansas in September. Oklahoma State was trying to send a message, and it sent one, loud and clear.

Unfortunately for OSU, also fresh in voters minds is a loss to an Iowa State team that finished below .500 in Big 12 play. I feel horrible for the kids at Oklahoma State, but you can’t blow a game (which you led 24-7 in the third quarter) against an utterly mediocre team on November 18 and expect to play for the national title just because you blew out a shaky Oklahoma team, which had been completely exposed by RGIII and Baylor two weeks earlier. The bottom line is that if voters had been sufficiently impressed by the last two weeks of Oklahoma State’s cumulative body of work, they could have voted Oklahoma State ahead of Alabama. They didn’t. In fact, 70% of coaches put Alabama ahead of Oklahoma State. 70%! And most of them had no skin in the game. Troy Calhoun put OSU fifth, and three coaches whose teams are not even remotely close to the championship race put them fourth (in addition to Nick Saban and David Shaw, both of whom obviously stand to benefit from their votes). Blame them if you’d like, but let’s not pretend their ambivalence makes no sense whatsoever.

Oklahoma State’s blowout of Oklahoma was impressive, but it wasn’t enough to overcome a major slip that only happened 15 days prior.

“Alabama had their chance and failed!”
So did Oklahoma State. They failed to Iowa State, and Alabama failed to LSU.

- – -

I’d also like to point out that I’m picking on Oklahoma State because I find them to be the only even remotely compelling alternative to Alabama. Here are two other teams that Rick Reilly suggested, along with reasons he is wrong:

Stanford: Laid the egg against Oregon that Alabama did NOT lay against LSU. Too injured to pose much of a challenge to LSU.

Boise State: To steal another point from Daniel, for how long are we going to allow Boise State to schedule one good-but-not-great big name team in week one and then use that as the only real arrow in their quiver in BCS discussions? It’s wonderful that they beat Georgia, but they really didn’t do anything else worth writing home about. You want to put that in the national championship game? Really?

Everyone else has two losses, except for Houston, and my contempt for Case Keenum and his wildly inflated numbers is well known.

Just so we’re clear, here is what I would like to see out of college football, in order of preference:

1.) Some sort of playoff. It’s time to settle this on the field, not because I believe we’ll ever be able to say conclusively “which team is better,” but to get as close as possible to that point.
2.) Revert to the pre-BCS days when you might have 2-3 bowl games that impact the national championship discussion but you’re often within a #1-versus-#2 matchup
3 through 1,390.) Anything else. Seriously.
1,391.) Stick with the current system.

But this year, we’re stuck with the current system, and the system did what it is supposed to do: it gave us #1 LSU and #2 Alabama.

(Now go ahead and tell me in the comments I’m an idiot. I can take it. To paraphrase Coach Gundy, “COME AFTER ME!! I’M A MAN!! I’M 30!!”)

Analyzing the NBA and college hoops: Not so different after all?

Every basketball season, we can count on a few things: Duke will be a top 10 team, LeBron James will disappoint his fans in the postseason, and basketball lovers everywhere will argue about whether pro basketball or college basketball is superior.

(For the record, I hate this debate. It seems terribly unproductive; if you don’t like college basketball, turn it off. If you hate the NBA, watch something else. This isn’t a standards war; arguing for the NBA doesn’t mean that college basketball will go away, nor does defending the college game impact the NBA in any way.)

Jimmer FredetteHowever, I’ll tell you that I’m a college basketball guy. I love March Madness more than I love the NBA playoffs—there’s no better stage for David-versus-Goliath matchups than the NCAA Tournament. I love the passion of the players and the insanity of the student fans. (You can’t storm the court in the NBA.) I love knowing that at least some of these players are getting educations while playing hoops, and that they walk around campus just like anyone else. I love that you can tune into two teams you’ve never seen before and learn about them and their players, and then weeks later see one of those teams celebrate at center court after punching a ticket to the Big Dance. I love figuring out who is the best of the 346 Division I teams despite the fact that disparities in conference difficulty and the learning curve of college ball make this nearly impossible. (I love that tonight they played a game on the deck of an aircraft carrier while the NBA continued its labor talks.)

But that’s just me.

Here’s why I sat down to write: I started to discuss this topic with Twitter friend @Neildos (who, for the record, is one of the smartest basketball fans I know and happens to prefer the NBA) earlier tonight, and the conversation led me to wonder about the data backing (or not backing) some of the common arguments on the pro-NBA side. One of the standard points against the college game is the terrible shooting and the lack of athleticism compared to the NBA. I won’t debate the second point; the NBA has the benefit of cherry picking the best of the best, which is why someone like Jimmer Fredette, who dominated in college, is expected to struggle to beat NBA point guards offensively (and stay with them defensively).

However, I take some exception to the first point, which is a staple of any anti-college argument. Here’s some data on shooting percentages, all from the 2010-2011 college and NBA seasons:

  • The San Antonio Spurs led the NBA in three-point percentage at 39.7%. Northern Arizona led the NCAA at 42.5%. Limiting our comparison to “major” conference teams (which you’re more likely to see on TV than Northern Arizona), Ohio State led at 41.3%. This is likely due in part to the fact that the college three-point line is three feet closer to the basket.
  • 13 college teams had three-point percentages higher than the Celtics.
  • The median college team (Northwestern State) shot 34.5% from beyond the arc, compared to 35.5% for the median NBA team, the Philadelphia 76ers. The worst college team, the Niagara Purple Eagles, shot just 27.5% for three, compared to an NBA low of 31.6% from the Toronto Raptors.
  • Boston led the NBA in field goal percentage at 48.6%. Kansas led college ball at 51.4% Six college teams out-shot the Celtics.
  • The median college teams (most notably Arkansas and tournament darling Florida State) shot 43.6%. The median NBA team, again the 76ers, shot 46.1%.
  • The worst college team from the floor was Alcorn State at just 36.9%, which is terrible. The worst NBA team (Milwaukee) crushed this, coming in at 43.0%.

I started with three-point and field-goal percentages because they’re a better way of analyzing the effectiveness of an offense than raw points per game numbers. That’s especially true when comparing one version of the game which is 48 minutes long, with 24-second shot clocks, to a version which is 40 minutes long with 35-second shot clocks. But perhaps an even better starting point is the Points Per Shot metric, because this blends all three methods of scoring into a simple measure of efficiency: how well are you able to turn shots into points?

  • Denver led the NBA in this category, at 1.33 points per shot. The median teams averaged 1.21, and the last place team (Milwaukee) came in at 1.15.
  • The top college teams annihilated Denver’s 1.33 points per shot. In fact, no fewer than 49 college teams had PPS numbers matching or higher than the Denver Nuggets.
  • In fact, the median college teams, of which there are several, beat the NBA median, coming in at 1.26 points per shot.
  • The worst college teams are far, far worse than the worst NBA teams in this measure. Little USC Upstate registers a 1.04.

A final point of analysis here concerns the complaint that the college game has a 35-second shot clock, which potentially makes each possession up to 11 seconds longer than an NBA possession. In other words, NBA fans hate the pace of the college game. They believe it is too slow. Let’s find out. Keep in mind that the NBA game is 48 minutes, whereas the college game is 40 minutes.

  • The NBA shot clock allows each team a minimum of 60 possessions, assuming that they use every second of every possession, whereas the college game allows 34 possessions. Despite this, NBA teams average about 80 shots per game. College teams average around 54 shots per game. This means that NBA teams use possessions at a rate of 1.33 times the minimum speed. College teams use possessions at a rate of 1.58 times their minimum.
  • What does that mean in real terms? NBA teams, on average, use about 18 seconds per possession. College teams use roughly 22 seconds. Certainly a difference, but not a huge one.

So what do I make of this?

  • The range of offensive skill (i.e., the difference between the best teams and the worst teams) in college basketball is greater than it is in the NBA. This makes sense when you think about games between SEC powerhouses and tiny schools from small towns which often end in scores such as 104-53. This also seems logical when we consider that the NBA is made up of the best college players; even the 12th man on the worst NBA roster was, at worst, a solid contributor in college. This means that, night in and night out, the NBA is “more competitive.” Spreads are smaller.
  • Most importantly, college offense is not nearly as bad as NBA fans would like to believe. There are fewer shots per minute in college due to the longer shot clock (1.4, versus 1.67 in the NBA), but this should not be confused with poor shooting ability. In reality, the average college team misses less than one more shot per game than the median NBA team would miss given the same 40 minute game and a 35-second shot clock. So you can argue that NBA players are more athletic, and you can argue that there is more parity in the NBA, but unless you think you’re going to notice one additional missed shot every game and a half, it’s really unlikely that you’ll notice an actual difference in offensive skill between college and the NBA.
  • This final one is a bit subjective, but having seen the data I believe that the 35-second shot clock is overrated as a detractor from the college game. Yes, college teams spend four more seconds per possession, on average, than NBA teams do. But NBA fans often make it sound like college teams are using all 35 seconds, whereas the NBA gets to the rim immediately. That’s not the case. It’s 22 seconds per shot versus 18 seconds, and that just isn’t significant in my mind.

Ultimately, this is all about preference. Most of the reasons why I prefer college basketball have less to do with the product on the floor than they do with the environment surrounding it. (And it’s not because I come from a college town; Boston generally couldn’t care less about college basketball, and they love their Celtics.) I do enjoy the NBA and there are times when I stop and think how much I love that flavor of basketball, but if I were stuck on a desert island with one brand of ball, I’ll take college and love it. As long as I can take some buffalo wings with me to the island.

Now it’s your turn. Are you an NBA person, or a college basketball person? What draws you to one or the other?

For more on this:

Is Data Ruining Sports?

Who would you rather have: Tris Speaker or Ty Cobb?

Jason Whitlock says that this question cannot be discussed; it can only be answered, thanks to the popularity of the book-turned-movie Moneyball, and sabermetrics, the advanced statistics that baseball fans and writers can now apply to the game as a lens through which to understand and contextualize the game. (Cobb had a better career OPS+, 168 to 157, so I guess he was better.)

someecards.com - Let's see a movie about a baseball genius who leads his team to winning one playoff series in 14 years

Whitlock argues that data is sapping the fun out of the sports. Little Timmy can’t enjoy the game of basketball anymore because nothing is left open to interpretation; there is a “right answer” to every question. Kobe versus MJ. Wilt versus Russell. Jason Whitlock believes it’s not even worth discussing anymore; some pencil-necked geek will inevitably come up with an empirical correct answer.

The problem with Whitlock’s argument is that it absolutely cannot be proven without resorting to data. On what basis does he believe that sports are being ruined for fans? What led him to this conclusion, other than his own personal distaste for advanced statistical measures? Here is some data to suggest that Jason is wrong.

If fans can’t enjoy sports anymore, because of data, how come ESPN keeps seeing excellent ratings for football, baseball, and basketball? When the Yankees played the Red Sox on August 7, it was the most viewed baseball broadcast on ESPN since 2007. The Patriots-Dolphins on Monday Night Football last week “delivered a 10.3 overnight rating, the second highest opening-game rating since ESPN started airing MNF in 2006.” Why are people watching instead of just watching the players’ statistics change in real time, since data has ruined sports?

If fans can’t enjoy sports anymore, because of data, how come attendance in the NBA has not slipped? It has stayed essentially level—around 21 million, near the cumulative total max capacity of all NBA arenas for 41 home games per team—since at least 2004, which is as far back as my NBA attendance data goes. Mr. Thompson and I did some rudimentary analysis of trends in NBA data. Fans aren’t staying home, and they’re not why the NBA is locked out. They’re having fun and enjoying the beauty and the drama of sports. (Data cannot tell you with certainty whether Kobe is going to hit that fadeaway at the buzzer to beat the Spurs; it can only tell you what the odds are.)

If fans can’t enjoy sports anymore, because of data, why is Major League Baseball reporting revenue increases year over year? As MLB reported after last season, the past seven seasons (2004-2010 inclusive) “are the seven best attended seasons in MLB history.” This coincides with the Moneyball era nicely, as the book was published in 2003. MLB revenue in 2010 approached $7 billion for the first time, putting it at around a 6% increase over 2009.

See, in order to prove that Moneyball and Sabermetrics have ruined sports, you’d need to show the world that they are having some sort of quantifiable negative effect. Jason absolutely cannot do that. His argument boils down to fear of needing to defend a position with more intelligence than “well, I just like Kobe Bryant better than Michael Jordan.” The reason people hate data, in sports just as in business, is that it raises the level of conversation and forces them to think more critically about the world.

Jason says we like data because we lack the ability to understand sports viscerally or strategically. I’m not sure what he means. (Oh no, I’m so buried in my data that I can’t tell what defense the Patriots are playing! Is it the 4-3 or the 3-4? Is that called a “blitz?” I can’t tell because, you know, I’m too nerdy to understand football.) This argument is ridiculous. It’s the same thing we hear in analytics for certain dyed-in-the-wool creatives who feel that data is an insufficient way to understand their “art.”

He says, “I saw Player X, and I know he was good, so therefore he’s good.” I’m afraid that’s unrealistic, Jason. See, you have biases. There are things you prefer in players, but that others might not. Errors or flaws you might not see, but that others do. You might see Brett Favre’s greatest game but miss his 20 game-ending interceptions because you were out getting coffee. This is even more likely to be true if your teams or your favorite players (or, if you’re in marketing or UXD, your favorite content/layout/design) are involved. You need data in order to look at the world on an even plane. You think that’s where the fun ends. I’d say that’s where the fun begins.

Ty CobbLet’s go back to Speaker and Cobb. Their advanced statistics are remarkably similar. You could legitimately make a case for either one. Sure, Jason; I suppose a nerd could come to you and say that Cobb had a higher OPS+, and that therefore there is no argument to be made for Speaker. Baseball fans don’t think that way. Speaker won four World Series with the Boston Red Sox; Cobb never won a World Series. Cobb was a terrible leader—perhaps the worst in sports history. His teammates utterly despised him. Yet, baseball fans are far more likely to know Ty Cobb. He was one of the first five inductees in the baseball Hall of Fame, and one could legitimately argue that he was the greatest natural hitter of all time. He is one of two players to accumulate more than 4,000 hits over his career. Despite all of this, there is a strong argument to be made that Speaker, even with his lower OPS+, would be a better player to build around. There is plenty about sports that cannot be quantified, Jason. Data just makes us think a little bit more about the nuances of the games we love.

Here’s another, more current example: Justin Verlander of the Detroit Tigers. A whole bunch of people believe that Verlander, by far the best statistical starting pitcher in baseball in 2011, should be the American League Most Valuable Player. Verlander has a Wins Above Replacement (WAR) of 8.5, which means that if you were to imagine that Verlander were replaced by an average starting pitcher, the Tigers would have won 8.5 fewer games. That is a massive number of wins to attribute to a single player. It’s the best in the league. If you define “value” in baseball as “wins,” you can definitely see how Verlander might be the MVP. But there are plenty of intelligent, knowledgeable Sabermetricians (myself included) who would accept the argument that the MVP should be someone who is on the field every day, playing in nearly every game (whereas starting pitchers only see action every fifth game). It’s a topic of conversation and debate on sports radio regularly. Fans love discussing it, even fans like me who know how statistically dominant Verlander has been. Where would the Yankees be without Curtis Granderson this season? Or the Red Sox without Jacoby Ellsbury at the top of their lineup? You can make legitimate cases for any of these players, each of whom (surprise!) excel in various statistical categories. Could it be that there is more to the MVP race that pure statistics? But Jason, I thought you said that there were no discussions allowed anymore!

I think Jason Whitlock is scared. He is scared that Hall-of-Fame voting in professional sports will someday be reduced to plugging numbers into a computer and seeing who the best players were. (This would guarantee someone like Todd Helton a spot in Cooperstown.) I don’t think anyone, even the great Bill James, would advocate such a hard-line stance. Eric Peterson made this point earlier this month, and I think it was prescient of him to make the distinction, since we’re going to be hearing these anti-data arguments more often as data usage grows, in both sports and business: we like to be data-informed, not data-driven. It’s important for me to know that Ryan Howard’s numbers don’t justify his massive contract, but that doesn’t mean I wouldn’t want him clubbing home runs for my team. (Perhaps that’s the difference between me and the seemingly data-driven Billy Beane, who still hasn’t won the last game of the season.) When I have data to help me understand what I’m seeing, I can put things into context. I can “relationalize” teams, players, and individual plays in new and exciting ways. Yes, Jason, data helps me and many others enjoy sports more than if it were completely up to our eyes.

I think Jason is also is scared that he can’t articulate why he loves John Elway other than “I like him.” I’m not sure why you’re scared, Jason. It seems easy to defend the fact that, even though Peyton Manning has eight more points of career completion percentage, and Tom Brady has a better postseason record, and Dan Marino has more yards, your boy Elway was a winner. He was a better leader than most of those quarterbacks, numbers be damned. Leadership matters, Jason, and it’s not quantifiable, so you’ve got your argument. You’ve got your discussion. And that doesn’t even touch on the physical aspects of Elway’s game that made him special (such as his arm). I could counter by talking about Tom Brady’s decision making, which also isn’t a statistic. (It isn’t just completing the pass that matters; it’s completing the best pass to the best possible target. This will never show on the stat sheet.) At that level—the Montana/Young/Marino/Manning/Brady/Elway level—you’re splitting hairs anyway. We nerds can say, “objectively, so-and-so is the best of all time.” You’re welcome to make a point that isn’t accounted for in the numbers. I don’t see how that should impact your enjoyment of the game or of discussions about the game, other than to make you think.

Maybe you don’t want to be forced to think. If that’s the case. . . tell me, who is ruining the vibrant discussion of sports, you or me?