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    A look back on last season’s preseason ratings

    by Ken Pomeroy on Monday, November 10, 2014

    The anticipation for preseason ratings is an interesting thing. People like to talk about the projections, poke holes in them, figure out why their team is underrated. But obviously, no team is bound by the shackles of its preseason forecast. Oregon State is predicted to finish last in the Pac-12 by most robots (and humans, for that matter), but nothing is stopping the Beavers from running the table in conference play.

    I guess if you want to get technical, a lack of talent might be a significant obstacle for them. But the robots will not be. If Oregon State wins its first four conference games, the robots are not going to hire Shane Stant to visit the Beavers’ locker room. In that sense, the ratings are irrelevant.

    However, there is good reason to have some interest in preseason projections. For most programs, the forecasts are a reasonable estimate of what neighborhood a team will reside in this season. There were four systems that made comprehensive preseason forecasts last season. Here’s the average error in forecasting regular-season conference wins for each of them…


    Which two teams last lost longest ago? (‘14 edition)

    by Ken Pomeroy on Tuesday, November 4, 2014

    Which two teams have gone the longest without losing on the same day? You might not care but regardless, I feel I have an obligation to tell you. Your indifference only motivates me to continue to track this fact with the intensity of 1000 red suns. If you’re new here, you can check out past editions of this post like the one before last season and the one that started it all in November 2012. After reading those, if you don’t care, then you may want to see a doctor and make sure your heart is functioning, because it might not be.

    As it happens, the answer to this question is the same as it was last year at this time. The last time Ohio State and Kansas lost on the same day was February 19, 2005. I don’t know how rare it is for the top streak to survive a full season since this is only the third year I’ve done this, but I expect it’s rare. I can say that with confidence because the reigning pair now has nearly a two-year advantage over the next-longest streak. I can also say that with confidence because of the ten-longest streaks entering last season, just two survived. Here is that list from a year ago…


    The value of the preseason AP poll, 2014 edition

    by Ken Pomeroy on Monday, November 3, 2014

    With the release of the first AP poll last Friday, it’s time for a refresher on the historic value of those rankings. The preseason AP poll is not going to tell you exactly how the season will play out, but given the poll has a long track record, we can use history to tell us the chances of a team ranked in a specific position getting a particular seed in the NCAA tournament.

    If you’re familiar with my work, you know by now my support for the preseason poll, and this will seem repetitive. But the data below is updated to include last season, so this is not a complete waste of your time.

    Last year, two teams ranked in the preseason failed to make the tournament: #17 Marquette and #21 Notre Dame. That’s better than normal. Since the poll expanded to 25 teams in 1990, an average of 3.7 ranked teams per year have missed the field altogether. Kentucky’s appearance in the NCAA tournament kept a perfect streak alive for the preseason’s #1 team. Every #1 team has made the field since it was expanded to 64 teams in 1984-85.


    Preseason ratings 2015

    by Ken Pomeroy on Tuesday, October 28, 2014

    By now, you’ve noticed the preseason ratings have been posted. Thanks to all that have stopped by the past 24 hours. My server thought it was March on Sunday night. (h/t to Matt Norlander for the tweet that generated the traffic. I usually enjoy flipping the switch and watching twitter spread the word organically over the course of a few hours, but since Norlander spilled the beans approximately five minutes after the site turned over, I got an immediate firehose of traffic.)

    I’ve discussed the formula in some detail in previous seasons and it hasn’t changed much in the five years I’ve been doing this. Here are some semi-random thoughts on them.


    Introducing Court Intelligence

    by Ken Pomeroy on Monday, September 29, 2014

    In recent months, I have received numerous emails from coaches inquiring if there is a tool available that will track advanced stats for their teams. In the past, I have responded with ignorance since I haven’t had the need to do this myself. But those days are over and I can now respond with knowledge.

    The Court Intelligence app powered by is now available for your iPad and allows you to track all the action during a game (or by reviewing video). Give it to an eager assistant coach or volunteer and you’ll have a gold mine of data at game’s end. The app can track various tempo-free stats associated with any player combination (individual through five-man combination) and aggregate them over a whole season. If you have the time, you can track opponents games as well to get an idea of what is working for them.


    Studying whether to foul when tied, Part 3

    by Ken Pomeroy on Thursday, July 24, 2014

    This is the third and final part of my series of whether to foul when the game is tied and the shot clock is off. If you missed part 1 and part 2, don’t worry, you’re joining us just in time. The payoff was this guide to when the strategy of fouling is justified.

    Maximum free throw percentage to implement fouling strategy
    Win probability     FT% threshold  
    Pre-game    OT     1-and-1  2-shot
      .900    .756       58.2    39.9
      .800    .671       62.2    44.7
      .700    .607       65.4    48.8
      .600    .552       68.4    52.9
      .500    .500       71.4    57.3
      .400    .448       74.4    62.0
      .300    .393       77.9    67.6
      .200    .329       82.4    74.8
      .100    .244       88.2    84.2

    For example, if we estimated that a team had a 40% chance of beating its opponent before the game started, that team would be justified in fouling a free throw shooter worse than 74.4%.



    Studying whether to foul when tied, Part 2

    by Ken Pomeroy on Saturday, July 19, 2014

    In Part 1, I went over some of the relevant win probabilities to consider for the strategy of fouling when the game is tied and the shot clock is off. If one assumes that any missed free throw is rebounded by the defense, then the strategy of fouling would be recommended in the majority of situations. Assuming perfection is a bad way to evaluate strategies, though. This is why some analyses of fouling up 3 tends to show a large advantage for fouling when history suggests that advantage is small (or none at all). Or that attempting to get the 2-for-1 at the end of a half is beneficial, but not as much as one might think.

    Factoring in the possibility of an offensive rebound to this analysis makes it somewhat more complicated, but it’s necessary to determine the merits of fouling. My examples will all use the single bonus situation. Not surprisingly, the math is much more favorable for fouling when the offense is in the single bonus since the possibility of making zero free throws increases.


    Studying whether to foul when tied, Part 1

    by Ken Pomeroy on Sunday, July 13, 2014

    Late in the 1983 national championship game, heavily-favored Houston held the ball with a little over a minute remaining in a tie game. In the pre-shot clock era, Houston had the opportunity to hold for the last shot. N.C. State head coach Jim Valvano implemented what would be considered a controversial strategy today, ordering Dereck Whittenburg to foul Alvin Franklin with 1:05 remaining, instead of playing defense and hoping to get to overtime.

    Neither member of the CBS broadcast team, Gary Bender or Billy Packer, criticized the idea. Actually, the normally disagreeable Packer was fully supportive of the strategy. And he should have been. Franklin was a 63 percent shooter from the line, and—spoiler alert— I’ll show the math that supports that Valvano gave his team a better chance of winning by giving the foul, assuming Franklin truly had a 63 percent chance to make his free throws.


    Offensive rebounding data dump

    by Ken Pomeroy on Wednesday, July 2, 2014

    If it’s the middle of summer and you’re obsessing about trends in offensive rebounding, then you’re either me or some sort of lunatic. I was initially concerned about a very specific aspect of offensive rebounding for an upcoming feature, but along the way I decided to look at the different things related to offensive rebounding that one can mine from play-by-play data, and that led me to what you are about to see.

    This isn’t going to be the most glamorous piece of analysis, but if there was a good time for an offensive rebounding data dump, this is it. Now for some facts regarding those second chances…


    Conference history pages

    by Ken Pomeroy on Monday, May 19, 2014

    You can now find a conference history page linked on each conference’s page next to the years list. While we tend to speak about the state of the game in terms of averages across Division-I, each league is an ecosystem in itself, with its own long-term norms distinct from the rest of the college hoops world. The Southland plays fast, the Big Ten plays slow, the Summit makes a bunch of shots, the SWAC doesn’t, and the SEC is not the place for those that fear rejection.


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