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    Weeks in Review III, 12/5-12/18

    by Ken Pomeroy on Friday, December 19, 2014

    I used to do this every day, then every week, and now it’s every two weeks. I’d like to do it every day, but I’d go crazy. So here are the last two weeks, reviewed:

    Public service message: But first, this message. This time of year people will often say something like “ predicts team X will win its next seven games” or something. But that’s usually not true! Just because a team is favored in its next seven games does not mean it is expected to go on a seven-game winning streak. It is very rare that is the case, actually. If a team was favored to win each of those games with a 51% chance, we’d expect then to go 4-3 because there’s a large chance of an upset in each of those games. Don’t confuse being favored in a bunch of games with being expected to win ALL of those games. Now the review…

    Biggest upsets

    3. Dec. 17: #336 Arkansas-Pine Bluff 61, #175 Houston 56 (OT, 8%). This one was especially fun because Houston was down 45-35 with just under five minutes left. Then the Cougars woke up and scored the next 10 and eventually withstood Tevin Hammond missing two free throws with six seconds left in regulation. So the game went to overtime and the Cougars got new life.

    A wise man once said, “you never get a second chance to make a first impression.” That man never said, “you never get a second chance to avoid an upset.” Because this was a case where Hammond’s misfortune at the line gave the Cougars another shot at avoiding embarrassment. However, Houston squandered that chance, too. This will be the best win a SWAC team gets all season, and this game serves as another reminder that changing coaches, even if you hire a big name like Kelvin Sampson, is often a painful process at first.


    Introduction to the PASR recruiting model

    by Jackson Fambrough on Monday, December 15, 2014

    Note: Making its debut on the site today is PASR (Predictive Analytics for Successful Recruiting), a model created by Jackson Fambrough using economic principles, that predicts where college basketball recruits will go to school. The predictions cover the top 150 recruits (as determined by Rivals) for future classes and will be updated approximately once a month. (The forecasts are linked from the player section of the team page for teams that are involve with at least one recruit. Or bookmark this link for future reference.) Jackson provides a description of the model below. You can contact him with your questions and comments at .(JavaScript must be enabled to view this email address) or on twitter @JackFambrough

    The theory for the model is based on an economic term called utility maximization. Utility, in an economic sense, means the satisfaction or happiness received from consuming a good or service. The model’s main purpose is to show which school will provide a recruit with the highest possible expected utility. Expected utility is divided into two different categories, short-term utility (the 1-4 years the recruit is in school) and long-term utility (the years after they leave the university).

    There are several factors that play a part in generating short-term utility, such as winning percentage. A recruit is more likely to go to a school with a higher winning percentage over the past five years because they want to be with a more successful program than a less successful one.


    On unbalanced conference schedules

    by Ken Pomeroy on Wednesday, December 10, 2014

    With many conferences increasing in size in recent years, there are fewer leagues playing a balanced conference schedule. Unfortunately, an unbalanced schedule introduces conference schedule strength as an additional variable that can influence the chase for a conference regular-season title. However, if this is keeping you up at night, it shouldn’t. It’s rarely that big of a deal.

    One way to demonstrate this is by looking at the conference record projections on my site (or anybody else’s). If an unbalanced schedule were a big deal, there would be inconsistencies between the order of the teams’ ratings and their projected record, given than most conferences have yet to start conference play. But there are very few of these. As of Wednesday, here are the inconsistencies between national ranking and projected record among conferences that do not play a balanced schedule…


    Play-by-Play Theater: Quickest individual 3’s

    by Ken Pomeroy on Monday, December 8, 2014

    Welcome to Play-by-Play Theater, the very irregular feature where I mine play-by-play data from the past five-plus seasons to discover the wacky things that happen in darkest corners of the college basketball universe.

    At the Maui Invitational, BYU’s Chase Fischer went on a 3-point shooting tear for the ages in the first half against Chaminade, making seven 3-pointers in a 5:10 stretch of the first half. Which begs an edition of Play-by-Play Theater to find the quickest 3-point barrages of all time. Or actually since the 2009-10 season, since that’s the beginning of the NCAA’s generosity in providing the universe with comprehensive play-by-play data for all schools.

    What follows is the shortest time to making a certain number of 3-point shots in games over the past five-plus seasons - keeping in mind I’m only looking at D-I on D-I action, which includes 28,306 games…


    Weeks in Review II, 11/22-12/4

    by Ken Pomeroy on Friday, December 5, 2014

    Hey everyone, here’s what you might or might not have missed over the past two weeks.

    Biggest upsets

    3. Nov. 29: #316 NJIT 84, #120 Duquesne 81 (8%). The Highlanders are still the country’s only independent, and therefore must earn an at-large bid to get into the NCAA tournament. Wins at Duquense help that cause. Except NJIT has already been swept by UMass Lowell, so they’re not going to be the first independent since DePaul in 1991 to make the tournament. They do have sophomore shooting guard Damon Lynn, who may well own the career three-point attempt record in two more years. He’s taken 79 in seven games this season, and in this game he took 11 3’s and made six to propel NJIT to the win.

    2. Nov. 22: #331 Appalachian State 65, #154 Virginia Tech 63 (8%). The top of the ACC appears to be stronger than any other conference, but the bottom of the league has some issues. At the same that the Hokies’ football team was dueling Wake Forest to a scoreless tie in regulation, App State went to Blacksburg and won on a rather, ahem, fortuitous shot by Frank Eaves.

    1. Nov. 28: #300 Delaware State 72, #91 Wake Forest 65 (7%). While there’s a certain sense of anticipation that surrounds a season with a first-year coach, the fact is that it’s usually a rough year for a program under a new leader. Both these teams are experiencing that to some degree this season. But still, this is not a game Wake Forest should lose even if the players had to coach themselves. The Demon Deacons were coming off a 24-point win over Mount St. Mary’s. Delaware State was reeling from a 50-point loss to Iona. But the Hornets won in a game that wasn’t even that interesting at the end.


    The ACC/Big Ten Challenge bar chart

    by Ken Pomeroy on Monday, December 1, 2014

    The battle to determine which conference is the second-best in the land tips off tonight. A total of 14 games will be played in the ACC/Big Ten Challenge over the next three days. As is customary, I simulated the challenge a million times based on my ratings to determine the chances of each conference winning the event.

    The last two seasons have ended in a tie and the powers-that-be have yet to adopt my tie-breaker of aggregate free throw percentage, so more ties are possible. ( officially recognizes the Big Ten as last season’s winner) The good news is that with more games, the chance of tie decreases.


    Week in Review I, 11/14-11/21

    by Ken Pomeroy on Friday, November 21, 2014

    This is the weekly column where I take a look at least-likely comebacks, biggest upsets, and other extremes in the college hoops universe over the past week. There’s also a dash of Alan Williams news and other random thoughts. Just read it.

    Public service message: Currently, Division-I teams are 129-0 against teams not in Division-I. These 129 games are real in the sense that they count in a team’s record, but they are not real in the sense that they mean anything. Based on the 100% winning percentage, the outcomes of the games aren’t in doubt, and even if they were, there is no evidence that the NCAA’s Men’s Basketball Committee cares about the outcome or even that they were scheduled in the first place.

    For whatever reason, it is tradition to count the stats from these games in the historical record. So when Minnesota scores 109 on Franklin Pierce (Alan Alda must be crying) or Tennessee Martin holds Champion Baptist to 29, these get counted in team and individual stats just like any other game. This despite the fact that these contests are often classified as exhibitions for the opponent. Because these games are complete shams, I don’t count the stats from these games anywhere on the site. If you are looking for individual or team shooting numbers, the data on my site may not match the “official” stats that will show up in media guides and other on-line sources. But don’t let that hold you back. Let’s work together to fight the pollution of Division-I stats with these quasi-exhibition games.

    Now, let’s look at the extremes from the past week according to my computer…


    The slowest season(?)

    by Ken Pomeroy on Monday, November 17, 2014

    You can’t make many sweeping judgments three days into the season, especially with so few compelling games being played. Favorites in my system have gone 168-20 so far, which is not testimony to the greatness of my preseason ratings, but that a simple preseason rating algorithm can easily predict winners with so many mismatches on the early schedule.

    However, there has been one interesting development: This could be the slowest-paced season that college hoops has seen. The previous record for patience was set just two seasons ago. Of course, last season we had the sweeping crackdown on contact with the ballhandler and a block/charge interpretation that was friendlier to the offense, with an intent to reverse the trend of lower scoring in the game.

    Early last season, I was stoked that coaches, fans, media, and officials had accepted this new approach in the college game. Fouls were called in bundles, pace and scoring increased significantly, and to my surprise the reaction wasn’t completely negative. We could all look forward to the day when fewer fouls were called as players adjusted to the new paradigm.

    Fewer fouls were called as the season progressed, just as it happens in any season, but then came March. And the postseason tournaments were played at a pace significantly slower than the previous season. This season, the sport is picking up where it left off with what is probably the slowest-paced start to the season in the sport’s history. (We obviously don’t have data going back far to test this, but realistically, only some years in the early 80’s are possible competition.)


    What I did this summer

    by Ken Pomeroy on Thursday, November 13, 2014

    With the season upon us, I thought I’d take some time to summarize some of the new information available I put on the site over the summer. If you’ve paid close attention to my twitter feed, then these aren’t new. But most people don’t, so here goes.

    - Conference historical summaries. If you want a clearer picture of how fast a conference has played at since 2002 or how many wins it has taken to win the league title, the conference historical summary is your place. It also provides a useful reference for membership changes. (Accessible by clicking All on the conference standings page.)

    - Souped-up lineup info. If you were around at the end of last season, you saw that I posted the most frequently used lineups for each team on the team page. I’ve added some visual markup to those which depict the usage and perimeter shooting tendencies of each player.


    The first annual #ShootersClub

    by Ken Pomeroy on Wednesday, November 12, 2014

    Who’s going to be the best three-point shooter in the land this season? If you can predict that, you can call yourself very good at predicting things although I would call you very lucky. I don’t have any special powers here, but I thought it might be fun to put together five shooters that would shoot very well this season. So well that it would be difficult to come up with another five-man team that would beat these guys.

    True to my hermit-like nature, I didn’t consult a bunch of coaches or scouts to come up with this list. I used each player’s shooting numbers over the past two seasons to predict their three-point percentage this season, all from the comfort of my basement. The numbers I used were three-point, two-point, and free throws made and attempted. The three-point and free throw numbers are indicative of a player’s shooting touch. The two-point numbers probably pick up on a mix of shooting touch and size, or at least ability to get off a shot.

    So did you make team? That’s a dumb question, because chances are you don’t play college basketball and you probably suck at three-point shooting. But these five guys do play and they can’t stop and won’t stop making shots.


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