March Mathness 2015: The Wrap Up


The champion has been crowned! After an eventful and surprising March Madness tournament, Duke has been named the new NCAA national champion.

A year of bragging rights goes to PUP paperbacks manager Larissa Skurka (98.6 percent) and PUP executive math and computer science editor Vickie Kearn (98.4 percent), who took first and second place in our ESPN bracket pool. Congrats to both! Check out all of the results here.

As we wrap up March Mathness, here are two final guest posts from basketball fans who used math and Tim Chartier‘s methods to create their brackets.

 Swearing by Bracketology

By Jeff Smith

My name is Jeff Smith, and I’ve been using Tim Chartier’s math algorithms to help with my March Madness brackets for several years now. I met Tim when we were traveling the ‘circuit’ together in creative ministries training. You may only know Tim for his math prowess, but I knew him for his creativity before I knew he was a brilliant mathematician. He and his wife, Tanya, are professional mimes, and his creativity is genius too.

Several years ago, he mentioned his method for picking brackets at a conference where we were doing some training together. He promised to send me the home page for his site and I could fill out my brackets using his parameters and formula. I was excited to give it a shot. Mainly, because I am part of a men’s group at our church that participates in March Madness brackets every year. Bragging rights are a big deal…for the whole year. You get the picture.

Also, I have two boys who did get one of my genes: the competitive edge. I sat down and explained the process. Because they did not know Tim, they were a little more skeptical, but I promised it wouldn’t hurt to try. That year, in a pool of 40+ guys, we all finished in the top ten. We were all hooked!

Since then, I have contacted Tim each year and reminded him to send me the link to his site where I could put in our numbers to fill out our brackets. Generally, the three of us each incorporate different parameters because we have different philosophies about the process. It has become a family event, where we sit around the dinner table; almost ceremonially, and we take our output and place them in the brackets. The submission is generally preceded by trash talking, prayer, and fasting. (Well, probably not the fasting, because we fill up with nachos and chips during the process.)

Jeff post

Men of March Mathness: Jeff, Samuel, Ben Smith.

This year, I was in South Africa on a mission trip during the annual ritual. Thank God for video chatting and internet access. Halfway across the world, we were still able to be together and place our brackets into the pool. It was such a wonderful experience. While my boys veered from the path, picking intuitively instead of statistically, I didn’t stray far. (I was strong!) If it wouldn’t have been for Villanova, whom I will never choose again in a bracket, I would be leading the pack. But, I’m still in the top ten of the men’s bracket at my church, with an outside shot of winning. In the Princeton bracket, I’m doing even better because I stayed away from the guessing game a little more.

I do not follow college basketball during the season. I’m from central Pennsylvania, and Penn State doesn’t have a good basketball team. So, I have no passion for the basketball season. Periodically, I’ll watch a game because my boys are watching, but generally, basketball season is the long wait until baseball season. (Go Pirates!) So, March Mathness has saved my reputation. It makes me look like a genius. Other guys in the group are looking at my bracket for answers. My boys and I are sworn to secrecy about the formula. The only reason I write this is because I’m sure none of them read this blog! But I’m thankful for Tim and the formula and the chance to look good in front of friends. I have never won the pool, however, if you factor my finishes over the course of the years I have been using Tim’s formula, I have the best average of all the guys.


 What Do Coaches Have to Do with It?

By Stephen Gorman, College of Charleston student


It’s that time of year again. The time of year when everyone compares brackets to see who did the best. But if your bracket was busted early, don’t worry — you’re not the only one. In fact, nobody came out of the tournament with a perfect bracket.

The unpredictability of these games is an inescapable fact of March Madness. This tournament is so incredibly unpredictable that some people are willing to give out billions to anyone who can create a perfect bracket; Warren Buffett is one of these people. So is he crazy? Or does he realize your odds of creating a perfect bracket are 52 billion times worse than winning the Powerball. In layman’s terms – if you think playing the lottery is crazy, trying to create the perfect bracket is insane.

However, once you can accept the statistics, predicting March Madness becomes a game of bettering you’re odds – and there are many predictive models that can help you out along the way. Some of these models include rating methods, like the Massey method, which takes into account score differentials and strength of schedule. In addition to this, there are weighting methods that can be applied to rating methods; these take into account the significance of particular games and even individual player statistics. However, I noticed there is one thing missing from these predictive models: a method that quantifies the value of a good coach. In order to take into account the importance of a coach, a fellow researcher (John Sussingham) and I decided to create our own rating system for coaches.

Using data available from, we made a system of rating that incorporated such factors as the coach’s career win percentage, March Madness appearances, and the record of success in March Madness. But before we implemented it, we wanted to justify that it was, indeed, a good way to quantify the strength of a coach. In order to do this, we tested the coach ratings in two ways. The first way being a comparison between how sports writers ranked the top 10 College Basketball coaches of all time and what our coach ratings said were the best coaches of all time. The second way was to test how the coach ratings did by themselves at predicting March Madness.

The comparison of the rankings are shown in the table below:

Rank Our Results CBS Sports Results Bleacher Report Results
1 John Wooden John Wooden John Wooden
2 Mike Krzyzewski Mike Krzyzewski Bobby Knight
3 Adolph Rupp Bob Knight Mike Krzyzewski
4 Jim Boeheim Dean Smith Adolph Rupp
5 Dean Smith Adolph Rupp Dean Smith
6 Roy Williams Henry Iba Jim Calhoun
7 Jerry Tarkanian Phog Allen Jim Boeheim
8 Al McGuire Jim Calhoun Lute Olson
9 Bill Self John Thompson Eddie Sutton
10 Jamie Dixon Jim Boeheim Jim Phelan

It is clear from the table above that there are striking similarities between all three rankings. This concluded our first test.

For the second test, we decided to use the coach ratings to predict the last fourteen years of March Madness. The results showed that over the last fourteen years, on average, coach ratings had 68.4 precent prediction accuracy and an ESPN bracket score of 946. As a comparison, the uniform (un-weighted) Massey method of rating (over the same timespan) had an average prediction accuracy of 65.2 precent and an average ESPN bracket score of 1006. Having a higher prediction accuracy, but lower ESPN bracket score essentially means that you have predicted more games correctly in the beginning of the tournament, but struggle in the later rounds. This comes to show that not only are these ratings good at predicting March Madness, but they stand their ground when compared to the effectiveness of very popular methods of rating.

To conclude this article, we decided that, this year, we would combine both the Massey ratings and our Coach ratings to make a bracket for March Madness. Over the last fourteen years, the combination-rating had an average prediction accuracy of 66.33 percent and an average ESPN bracket score of 1024. It’s interesting to note that while the prediction accuracy went down from just using the Coach ratings, the ESPN bracket score went up significantly. Even more interestingly, both the prediction accuracy and the ESPN Bracket score were better than uniform Massey.

This year, the combination-ratings had three out of the four Final Four teams correctly predicted with Kentucky beating Duke in the Championship. However, the undefeated Kentucky lost to Wisconsin in the Final Four. Despite this, the combination-ratings bracket still did well, finishing in the 87.6th percentile on ESPN.

Davidson student hangs onto 97 percent March Madness ranking

Are you still mourning the loss of your perfect bracket after the multiple upsets this March Madness season? Even before the Villanova and NC State match up on Saturday, 99.3 percent of brackets were busted. As experts deem a perfect March Madness bracket impossible, having a nearly perfect bracket is something to brag about. Today, we hear from David College student Nathan Argueta, who argues that knowing a thing or two about math can help with March Madness strategy.


March Mathness: Calculating the Best Bracket

First and foremost… I am far from a Math Major and, prior to this class, the notion that math and sports going hand in hand seemed much more theoretical than based in reality. Now, 48 games later and a 97.2% ranking percentage on ESPN’s Bracket Contest has me thinking otherwise.

In Finite Math, we have explored the realms of creating rankings for teams based on multiple factors (win percentage, quality wins, etc.). Personally, I also take into account teams’ prior experience in the NCAA Tournament. Coaches with experience in the Sweet 16, Final Four, and Championship Game (like Rick Pitino out of Louisville) also factored into my decisions when deciding close games. Rick Pitino has made the Sweet Sixteen for each of the past four years. With a roster whose minutes are primarily distributed amongst second and third year players (players who have had success in the NCAA tournament in the past couple of years) I found it difficult to picture Louisville losing to either UCI, UNI, or even the upcoming battle against upstart NC State (who have successfully busted the majority of brackets in our class’s circuit by topping off Villanova).

In theory, the quest to picking the best bracket on ESPN begins and ends with establishing rankings for each team in the contest. Sure there are four of each seeding (1’s, 2’s, etc.), yet these rankings are very discombobulating when attempting to decide which team will win between a 5th seed and a 12th seed or a 4th seed and a 13th seed. One particular matchup that I found extremely interesting was the one between 13th seeded Harvard and 4th seeded UNC. Gut reaction call—pick UNC. UNC boasts a higher ranking and has ritual success in the postseason. But hold on—Harvard had a terrific record this year (much better than UNC’s, albeit in an easier conference). The difficult thing about comparing Harvard and UNC, however, became this establishment of difficulty of schedule. I nearly chose Harvard, were it not for the fact that Harvard got beaten by about 40 points against UVA while UNC put up more of a fight and only lost by 10 points.

In order to pick the perfect bracket (which mind you, will never happen), categorizing and ranking teams based on their wins against common opponents with prior sports knowledge is imperative. My school pride got the better of me when I chose Davidson to advance out of the Round of 64 against Iowa simply because I disregarded factors like momentum, size, and location. Looking back, it is no wonder that Davidson lost by over 30 points in what many pundits were looking to be a potential upset match. While mathematically our team’s chances could have more than competed against Iowa, in reality our season was spiraling downwards out of control since the second round of the Atlantic 10 Tournament in which we hardly beat out a surprising La Salle team and got annihilated by an injury plagued VCU team that we shut-out just nine days before. Moral of the story… brackets will be brackets and while math can certainly guide you towards a higher ranking in your class pool, you can kiss perfection good-bye. This is March Madness.

Using math for March Madness bracket picks

The countdown to fill out your March Madness brackets is on! Who are you picking to win it all?

Today, we hear from Liana Valentino, a student at the College of Charleston who works with PUP authors Amy Langville and Tim Chartier. Liana discusses how math can be applied to bracket selection.

court chalk

What are the chances your team makes it to the next round?

The madness has begun! Since the top 64 teams have been released, brackets are being made all over the country. As an avid college basketball fan my entire life, this is always my favorite time of the year. This year, I have taken a new approach to filling out brackets that consist of more than my basketball knowledge, I am using math as well.

To learn more about how the math is used to make predictions, information is available on Dr. Tim Chartier’s March Mathness website, where you can create your own bracket using math as well!

My bracket choices are decided using the Colley and Massey ranking methods; Colley only uses wins and losses, while Massey integrates the scores of the games. Within these methods, there are several different weighting options that will change the ratings produced. My strategy is to generate multiple sets of rankings, then determine the probability that each particular team will make it to a specific round. Using this approach, I am able to combine the results of multiple methods instead of having to decide on one to use for the entire bracket.

Choosing what weighting options to use is a personal decision. I will list the ones I’ve used and the reasoning behind them using my basketball awareness.


Winning games on the road should be rewarded more than winning games at home. Because of that, I use constant rates of .6 for a winning at home, 1.6 for winning away, and 1 for winning at a neutral location; these are the numbers used by the NCAA when determining RPI. I incorporate home and away weightings when performing other weighting methods as well.


Margin of victory is another factor, but a “blow out” game is defined differently depending on the person. With that in mind, I ran methods using the margin of victory to be both 15 and 20. This means if the margin of victory if 15, then games with a point differential of 15 or higher are weighed the same. These numbers are mainly from personal experience. If a team wins by 20, I would consider that a blowout, meaning the matchup was simply unfair. If a team loses by 15, which in terms of the game is five possessions, the game wasn’t necessarily a blow out, but the winning team is clearly defined as better than the opposition.

In addition to this, I chose to weight games differently if they were close. I defined a close game as a game within one possession, therefore three points. My reasoning behind this was if a team is blowing out every opponent, it means those games are obviously against mismatched opponents, so that does not say very much about them. On the other hand, a team that constantly wins close games shows character. Also, when it comes tournament time, there aren’t going to be many blow out games, therefore teams that can handle close game situations well will excel compared to those who fold under pressure. Because of this, I weighted close games, within three points, 1.5, “blow out” games, greater than 20 points, .5, and any point differential in between as 1.


Games played at different points in the season are also weighted differently. Would you say a team is the same in the first game as the last? There are three different methods to weight time, as provided by Dr. Chartier using his March Mathness site, linearly, logarithmically, and using intervals. Linear and logarithmic weights are similar in the fact that both increase the weight of the game as the season progresses. These methods can be used if you believe that games towards the end of the season are more important than games at the beginning.

Interval weighting consists of breaking the season into equal sized intervals and choosing specific weightings for each. In one instance, I weighted the games by splitting the season in half, down weighting the first half using .5, and up weighting the second half using 1.5 and 2. These decisions were made because during the first half of the season, teams are still getting to know themselves, while during the second half of the season, there are fewer excuses the make. Also, the second half of the season is when conference games are played, which are generally considered more important than non-conference games. For the people that argue that non conference play is more important because it is usually more difficult than in conference play, I also created one bracket where I up weight the first half of the season and down weight the second half.


The last different weighting method used was incorporating if a team was on a winning streak. In this case, we would weight a game higher if one team breaks their opponents winning streak. Personally, I defined a winning streak as having won four or more games in a row.

I used several combinations of these various methods and created 36 different brackets that I have used to obtain the following information. Surprisingly, Kentucky only wins the tournament 75% of the time; Arizona wins about 20%, and the remaining 5% is split between Wisconsin and Villanova. Interestingly enough, the only round Kentucky ever loses in is the Final Four, so each time they do make it to the championship, they win. Duke is the only number 1 seed never predicted to win a championship.

Villanova makes it to the championship game 70% of the time, where the only team that prevents them from doing so is Duke, who makes it 25% of the time. The remaining teams for that side of the bracket that make it are Stephen F. Austin and Virginia, both with a 2.5% chance. Kentucky makes it to the championship game 75% of the time, while Arizona makes it 22%, and Wisconsin makes it 3%. However, if Arizona makes it the championship game, they win it 88% of the time. Furthermore, Wisconsin is predicted to play in the championship game once, which they win.

The two teams Kentucky loses to in the Final Four are Arizona, and Wisconsin. During the final four, Kentucky has Arizona as an opponent 39% of the time, where Arizona wins 50% of those matchups. Kentucky’s only other opponent in the final four is Wisconsin, where Wisconsin wins that game only 5% of the time. On the other side, Villanova makes it to the final four 97% of the time, where the one instance they did not was a loss to Virginia. Villanova’s opponent in the Final Four is made up of Duke 72%, Gonzaga 19%, Stephen F. Austin 6%, Utah at 3%. The only seeds that appear in the Final Four are 1, 2, and one 12 seed, Stephen F. Austin one time.

During the Elite 8, Duke is the only number 1 seed that does not make it 100% of the time, with Utah upsetting them in 17% of their matchups. The other Elite 8 member is Gonzaga 97% of the time. Kentucky’s opponent in this round is Notre Dame 47% and Kansas 53% of the time.

In the Sweet 16, there are eight teams that make it every time: Kentucky, Wisconsin, Villanova, Duke, Arizona, Virginia, Gonzaga, and Notre Dame. Kansas is the only number 2 seed not on the list as Wichita State is predicted to beat them in 8% of their matchups. Kentucky’s opponent in the Sweet 16 is Maryland 39%, West Virginia 36%, Valparaiso 14%, and Buffalo 11%. Valparaiso is the only 13 seed predicted to make it to the Sweet 16. Villanova’s opponent is either Northern Iowa 61% or Louisville 38%. Duke appears to be facing either Utah 67%, Stephen F. Austin 19%, or Georgetown 14%.

Now, for the teams that make it into the third round. I’m not sure how many people consider a 9 seed beating an 8 seed an upset, but the number 9 seeds that are expected to progress are Purdue, Oklahoma State, and St. John’s. In regards to the 10 seed, Davidson is the most likely to continue with a 47% chance to move past Iowa, which is the highest percentage for an upset not including the 8-9 seed matchups. Following them is 11 seed Texas, who have a 42% of defeating Butler. For the 12 seeds, Buffalo is the most likely to continue with a 36% chance of beating Virginia. The 13 seed with the best chance of progressing is Valparaiso with 19% over Maryland. Lastly, the only 14 seeds that move on are Georgia State and Albany, which only happens a mere 8% of the time.

In general, Arizona seems to win the championship when using Massey and linear or interval weighting without home and away. This could be because most of their losses happen during the beginning of the season, while they win important games towards the end. Using the Colley method is when most of the upsets are predicted. For example, Stephen F. Austin making it to the championship game happens using the Colley logarithmic weighting. Davidson beating Iowa in the second round is also found many times using different Colley methods.

Overall, there are various methods that include various factors, but there are still qualitative variables that we don’t include. On the other hand, math can do a lot more than people expect. Considering Kentucky is undefeated, I presumed the math would never show them losing, but there is a lot more in the numbers than you think. Combining the various methods on 36 different brackets, I computed the probabilities of teams making it to specific rounds and decided to make a bracket using the combined data. This makes it so I don’t have to decide on solely one weighting that determines my bracket; instead, I use the results from several methods. Unfortunately, there is always one factor we cannot consider, luck! That is why we can only make estimates and never be certain. From my results, I would predict to see a Final Four of Kentucky, Arizona, Villanova, Duke; a championship game of Kentucky, Villanova; and the 2015 national champion being Kentucky.



Cinderella stories? A College of Charleston student examines March Madness upsets through math

Drew Passarello, a student at the College of Charleston, takes a closer look at how math relates to upsets and predictability in March Madness.


The Madness is coming. In a way, it is here! With the first round of the March Madness tournament announced, the craziness of filling out the tournament brackets is upon us! Can math help us get a better handle on where we might see upsets in March Madness? In this post, I will detail how math helps us get a handle on what level of madness we expect in the tournament. Said another way, how many upsets do we expect? Will there be a lot? We call that a bad year as that leads to brackets having lower accuracy in their predictions. By the end of the article, you will see how math can earmark teams that might be on the cusp of upsets in the games that will capture national attention.

Where am I learning this math? I am taking a sports analytics class at the College of Charleston under the supervision of Dr. Tim Chartier and Dr. Amy Langville. Part of our work has been researching new results and insights in bracketology. My research uses the Massey and Colley ranking methods. Part of my research deals with the following question: What are good years and bad years in terms of March Madness? In other words, before the tournament begins, what can we infer about how predictable the tournament will be?

One way of answering this question is to see how accurate one is at predicting the winners of the tournaments coupled with how high one’s ESPN score is. However, I also wanted to account for the variability of the level of competition going into the tournament, which is why I also looked at the standard deviation of the ratings of those in March Madness. A higher standard deviation implies the more spread out the playing level is. Ultimately, a good year will have a high tournament accuracy, high ESPN score, and a high standard deviation of ratings for those competing in March Madness. Similarly, a bad year will have low tournament accuracy, low ESPN score, and a low standard deviation of the ratings. This assessment will be relative to the ranking method itself and only defines good years and bad years solely in terms of past March Madness data.

I focused on ratings from uniformly weighted Massey and Colley ranking methods as the weighting might add some bias. However, my simple assessment can be applied for other variations of weighting Massey and Colley. I found the mean accuracy, mean ESPN score, and mean standard deviation of ratings of the teams in March Madness for years 2001 – 2014, and I then looked at the years which rested below or above these corresponding means. Years overlapping were those deemed to be good or bad, and the remaining years were labeled neutral. The good years for Massey were 2001, 2004, 2008, and 2009, and the bad years were 2006, 2010 – 2014. Neutral years were 2002, 2003, and 2007. Also, for Colley, the good years were 2005, 2007 – 2009; bad years were 2001, 2006, and 2010 – 2014; neutral years were 2002 – 2004. A very interesting trend I noticed from both Massey and Colley was that the standard deviation of the ratings of those in March Madness from 2010 to 2014 were significantly lower than the years before. This leads me to believe that basketball has recently become more competitive in terms of March Madness, which would also partially explain why 2010 – 2014 were bad years for both methods. However, this does not necessarily imply 2015 will be a bad year.

In order to get a feel for how accurate the ranking methods will be for this year, I created a regression line based on years 2001 – 2014 that had tournament accuracy as the dependent variable and standard deviation of the ratings of those in March Madness as the independent variable. Massey is predicted to have 65.81% accuracy for predicting winners this year whereas Colley is predicted to have 64.19%accuracy. The standard deviation of the ratings for those expected to be in the tournament was 8.0451 for Massey and 0.1528 for Colley, and these mostly resemble the standard deviation of the ratings of the March Madness teams in 2002 and 2007.

After this assessment, I wanted to figure out what defines an upset relative to the ratings. To answer this, I looked at season data and focused on uniform Massey. Specifically for this year, I used the first half of the season ratings to predict the first week of the second half of the season and then updated the ratings. After this, I would use these to predict the next week and update the ratings again and so on until now. For games incorrectly predicted, the median in the difference of ratings was 2.2727, and the mean was 3.0284. I defined an upset for this year to be those games in which the absolute difference in the ratings is greater than or equal to three. This definition of an upset is relative to this particular year. I then kept track of the upsets for those teams expected to be in the tournament. I looked at the number of upsets each team had and the number of times each team gets upset, along with the score differential and rating differences for these games. From comparing these trends, I determined the following teams to be upset teams to look for in the tournament: Indiana, NC State, Notre Dame, and Georgetown. These teams had a higher ratio of upsets over getting upset when compared to the other teams. Also, these teams had games in which the score differences and rating differences were larger than those from the other teams in March Madness.

I am still working on ways to weight these upset games from the second half of the season, and one of the approaches relies on the score differential of the game. Essentially, teams who upset teams by a lot of points should benefit more in the ratings. Similarly, teams who get upset by a lot of points should be penalized more in the ratings. For a fun and easy bracket, I am going to weight upset games heavily on the week before conference tournament play and a week into conference tournament play. These two weeks gave the best correlation coefficient in terms of accuracy from these weeks and the accuracy from March Madness for both uniform Massey and Colley. Let the madness begin!


The math behind March Madness

It’s almost that time again. The beginning of the March Madness basketball tournament is a few days away, and here at PUP, we cannot wait!

We’re marking our calendars (find the schedule here) and going over our bracketology, with a little help from PUP author Tim Chartier.

To kick off the countdown, we bring you an article from the Post and Courier, who checked in with Dr. Chartier about how numbers can be the best strategy in bracketology.

College basketball fans seeking to cash in on March Madness need to turn on their calculators and turn off their allegiances.

That was the message Dr. Tim Chartier, a math professor at Davidson and published author, brought to cadets at The Citadel on Monday night.

“The biggest mistake people make in bracketology is they go with their heart no matter what the data says,” said Chartier, who has made studying the mathematics of the NCAA basketball tournament part of his students’ course work at Davidson. “They just can’t let a certain team win or they just have to see their team do well.

“It’s hard not to do that, because that is part of the fun.”

Chartier has made it easier for the average fan to use math in filling out their own brackets at the March Mathness website The site will get a lot of traffic after the NCAA tournament field is announced on March 15.


Read the full article on the Post and Courier website.

Dr. Tim Chartier is a numbers guy, and not only during basketball season. He likes to show students how math can apply outside of the classroom. How can reposting on Twitter kill a movie’s opening weekend? How can you use mathematics to find your celebrity look-alike? What is Homer Simpson’s method for disproving Fermat’s Last Theorem? Dr. Chartier explores these and other questions in his book Math Bytes.

(Photo courtesy of Davidson College)

(Photo courtesy of Davidson College)


As Dr. Chartier and others gear up for basketball lovers’ favorite time of year, PUP reminds you to mark your calendars for these key dates.

Check back here soon for more hoop scoop!

• Selection Sunday, March 15, ESPN

• First and Second Rounds, March 20, 22 or March 21, 23

• Greensboro Regional, March 27, 29, Greensboro Coliseum (Greensboro, North Carolina)

• Oklahoma City Regional, March 27, 29, Chesapeake Energy Arena (Oklahoma City, Oklahoma)

• Albany Regional, March 28, 30, Times Union Center (Albany, New York)

• Spokane Regional, March 28, 30, Spokane Veterans Memorial Arena (Spokane, Washington)

• National Semifinals, April 5, Amalie Arena (Tampa Bay, Florida)

• Championship Game, April 7, Amalie Arena (Tampa Bay, Florida)

How are we doing after the round of 32?

John_Hussey[1]Sportscaster-John Hussey

The first weekend of the NCAA tournament was as surprising as ever, with Florida Gulf Coast’s sweet 16 appearance topping the list. FGCU put the largest dent into my bracket knocking out Georgetown, which eliminated a team from the finals for me, essentially ending what chance I had at a good score. Even though the game was a big upset, it wasn’t “entirely” a shock. Going into the tourney, I knew that FGCU had a win over Miami on their resume and Georgetown’s Princeton offense makes them susceptible to low scoring games, which makes them vulnerable. There is a reason that Georgetown lost to South Florida this year.

Out West, I had the right idea picking against Gonzaga in the second round–I just picked the wrong team in Wichita State. In the South, the basketball gods must really love Florida. This is the second straight year that Florida gets to play a 15 seed in round 2 or later. For perspective, Florida has now played a 14, 11, and 15 in their first three games, while #1 seed Kansas has played a 16, 8, and now a 4. Talk about luck of the draw for the Gators! I wish someone would have told me that would happen!

I had a near miss with Illinois over Miami (FL), which really torched my East Region. It will be interesting to see who wins that Indiana/Syracuse matchup down in Washington DC. I’ll be in attendance to see what happens.

Overall, with three Final Four teams alive (and my champion), the first weekend wasn’t a completely disaster. But it was pretty close!


vickie_kearn[1]Math Geek-Vickie Kearn

This was definitely a weekend of hits and misses for me. There were some big surprises from a math point of view, especially FGCU, Oregon and Ole Miss. However, I still have 7 of 8 teams scheduled to go to the Elite Eight (assuming they survive the Sweet 16). Although I was sad to see my math off track, I did love seeing some personal favorites (Temple and Lasalle) and underdogs (FGCU) go further than I expected.

After riding high the first day of play my sister, who made her picks based on the color of the team jerseys, is rethinking that strategy. Her color is blue and she did pick Duke so she may be flying high again soon.

The Sportscaster versus the Math Geek

John Hussey and Vickie Kearn both work at Princeton University Press. John is the assistant sales director and national accounts manager and Vickie is the mathematics editor. We thought it would be fun to see how they filled out their March Madness brackets. The conversation that follows took place on March 20 at our PUP offices. To get things started, we asked a single question: How did you fill out your bracket?

Vickie: You may have figured out I am the math geek. After getting my math degree at the University of Richmond, I taught math for 8 years and then ventured into publishing math books. Although I am a huge sports fan, my true love is football. I didn’t watch basketball until we began March Mathness a couple of years ago. Now I will be glued to the TV for the next few weeks. I really don’t know much about the game at all but I love watching the numbers and the great upsets, especially those we have seen so far this year.

Now to my bracket. Because of the many upsets this year, I decided to ignore the seeds.

I looked at four things when I filled in my bracket:

1. Strength of schedule (pulled from RPI). I gave this figure a weight of 1.
2. Winning percentage for the regular season earned a weight of 1.
3. The sum of the posts season wins over the past three years plus the coach’s winning record with their current team also got a weight of 1.
4. Then each team received the following bonus points.

-One point if they were the leader in their conference in the regular season.
-One point if they are a major team and if they are in a tested basketball conference like the ACC, Big East, and Big10.
-One point if they won their conference championship season
-One point for the leaders in points per game/rebounds per game/scoring offense and scoring defense

Bonus points are weighted as 2 because they reflect how the teams were playing at the end of the season.

John: What about style of play?

Vickie: I don’t know that much about basketball, I’m in March Madness for the math. I’m interested in the data and stats.

John: To get an understanding of my approach, here’s my background: I went to Syracuse University for sports broadcasting. I have friends that still work in sports. My picks are based on a personal study of the game; I watch about 20 hours of sports/week and college basketball is my favorite. My picks are similar to Vickie’s, but from a different point of view. I’m not distinguishing between conference tournament and how a team plays through the stretch of the season. I’ve been watching teams play and deciding on style of play. For example, if one team tends to make a lot of 3-pointers and they’re up against a team with a strong zone defense, the zone defense is not going to do well. Where things get tricky is making decisions about Syracuse. Since that’s my team I’m pretty biased. When you watch teams extensively, you have seen them in the good times and bad but the bad times stick in your mind. For example, Kansas’ loss at TCU or Michigan’s loss at Penn State. I also know a lot about upset histories. This year there are no #1 seeds in my final bracket because this year no one team dominated. The possibilities are wider this year…could be a five seed that wins.

Vickie: I only have one #1 seed in my final 4. We both picked #2 seed Duke as the 2013 champion.

John: Player experience is also a big factor. Some game style doesn’t translate into a tournament setting. Duke is a great team, but sometimes flakes out super early. They lost to Lehigh last year but they make lot of deep runs. It’s interesting that Miami is in Vickie’s final 4 but I have them flaming out in the 2nd round. They’re too reliant on 3pt shooting. They’re not an intelligent team and play up and down.

What does the math say the biggest upset will be in the first round?

Vickie: New Mexico State over St. Louis is a 13 over 4 and San Diego State over Michigan is a 13 over 4. California over UNLV is a 12 over 5.

John: Any upsets in your Elite 8? No major upsets but I do have 2, 3, and 4 seeds.

Vickie: No major upsets but I do have 1, 2, 3, and 4 seeds.

John: I don’t have any top seeds in my final four because they have been losing lately, but the math is backing up the top seeds.

Vickie: But here’s the real question: will we beat the president?

John: Obama takes the smart, safe approach to the bracket. Historically he has been very good, because he is conservative in his picks and doesn’t bet on upsets. Generally that’s a good way to go. This year is going to be odd since the tops aren’t doing so well. It really could be a 5, 6,or 7 that wins. Nothing crazy based on the math?

Vickie: No, but that doesn’t mean I wouldn’t like to see an upset.

John: Gonzaga has a great RPI, but they’re not ranked high. Their defense metrics must be off . They have a great winning percentage but not necessarily the RPI.

Vickie: But seriously, will we beat the president?

John: He’s playing smart and safe. I want to win, but in an interesting way. It’s a little riskier when you don’t have any #1 seeds in the final 4.

Vickie: Well it’s interesting how similar our brackets are even though we had different strategies! I just got a text from my sister who picked her teams by the color of their uniforms. Blue is her color so she also picks Duke to win this year.

In case you are wondering, the odds of having a perfect bracket are 9.2 Quadrillion to 1. Good luck and have fun.

Q & A with Colin Stephenson and Neil Goodson

In 2008, Davidson College seniors, Colin Stephenson and Neil Goodson, used math to fill in their bracket and ended up ranking in the 100th percentile at a rank position of 834 in ESPN’s Tournament Challenge. Read about their experience below.


Q: What class were you taking when you created your brackets? How did the idea of creating brackets with math algorithms arise?

Neil: The original research project came out of an elective course I took that focused on topics in operations research, which is an area of mathematics that focuses on the application of mathematics to solving complex problems in the real world problems.  The class was a small group of graduate and undergraduate students, and we were all guided by the professor, Amy Langville.  Knowing that Colin and I had an interest in sports, Amy encouraged us to conduct our research for the class in the area of sports ranking.  Amy had already put effort in this topic as well as previous students, so we had tremendous resources available to us and were able to hit the ground running.

Colin: Our assignment was to use algorithms to solve real world problems.  Amy recommended sports ranking models to us.  It sounded perfect to combine one of our favorite sports, college basketball, and math.


Q: How did you break down tasks in your work?

Neil: The research project started in January at the onset of the Spring semester, so we had just a few months before March Madness began.  Our research process required us to study existing methods, apply them to various past seasons and the current one, discuss results with our class and see how we can improve upon existing methods.  Colin and I quickly learned to divide tasks to our strengths.  I would spend time coding certain methods, and Colin would backtest previous year’s data.  Both of use would scramble to present results to our classmates and professor each week.  The class was structured so we could all brainstorm collectively on where to head next and that helped us move forward with our project.

Colin: First we wanted to understand current ranking models.  Some were already being used in sports and others were being used for ranking things other than sports.  Neil and I also thought of factors we considered to favor teams to go further in the tournament.  We wanted to find ways to incorporate our own ideas as amatuer braketologists into our models.  We decided to focus on weighting win/loss records depending on when they were played before the tournament.  We both feel strongly that wins and losses in late February and March mean much more than those in November through January.  The “hot” teams going into the single elimination tournament usually seem to go further.


Q: Did you create one bracket or several?

Neil: We created several brackets.  We wanted to test various weighting schemes for each rating method.  For example, we had several variations of the Massey method and several others for the Markov method.  In total, I believe we tested over 30 brackets for that tournament.

Colin: We created 30 or more brackets.  We also tested them against the 4 previous years’ results in the NCAA tournament.


Q: Can you describe which methods were successful? Did you have a sense of which would be most successful?

Neil: The most successful results were the methods that placed more weight on games occurring later in the season.  Most sports fans would agree that this is a no brainer.  What is interesting though is that we found that you can place too much weight on the end of the season as well.  If you were to emphasize the conference championships in a model for instance, you probably would not do very well.  So there is a trade-off between teams that have played well consistently throughout the season and ones that have positive momentum going into the post-season play.

Colin: The Colley and Ken Massey models that we weighted logarithmically worked the best for us, exponential weighting also worked well.  We thought those models would work well because they were already used in sport ranking.  We also thought that log and exponential weight would be best because the games closer to the end of the season get gradually more important than the last.  They also did the best while testing previous years.


Q: What data went into making your predictions? scores? dates? anything else?

Neil: Our rating methods took into account each head-to-head match-up in Division I basketball, the point spread for each of those games, and when they were played.  Strength of schedule also played an important factor for some of the methods. The major differences arose between the mathematical techniques used to rank the teams given this vast web of conference and non-conference match-ups throughout the season.


Q: What kind of excitement did you experience during the tournament? Were you ever on a leaderboard? What did it feel like to be in such a high percentile?

Colin: The tournament excitement was awesome.  After all our preparation and work we were able to sit back and watch basketball for a couple weeks.  When Neil went on NPR the morning before the first games he told them a couple upsets our models were showing.  I think all the ones he told ended up happening.  It was also great to go on national live tv on the CBS Early Show.  We were live on the Davidson campus the night they were playing Kansas.  When we let them know we had Kansas winning it all, then we got boo’d out of the building.  The best models were in the 100th percentile on  They were doing better than any bracket I had ever put together myself.  They were also beating all of my friends, so I had bragging rights with them.  Kansas ended up winning in the last seconds of the championship.  Neil and I went crazy when it ended the way it did, one last second missed shot and we would have been well out of the 100th percentile.

Neil: I have always enjoyed March Madness every Spring, but working on this project brought the excitement to a whole new level.  After spending so much time in the lab crunching the data, I couldn’t help but constantly check how each model was performing when each tournament game ended.  Since we submitted all of our brackets to the ESPN Challenge, we could instantly get a sense of how each stood compared to the 4+ plus other brackets out there.  For most of the tournament, our best models were consistently in the 95th percentile and we ultimately finished in the 99.9th percentile with our best models.  For me, it felt great to see the long hours of writing code, crunching data, and presenting research results payoff with winning brackets, but honestly even if we hadn’t been as successful, I would have enjoyed the project just as much.  In that case there would have been so much else to try.  I might never have wanted to graduate!


Q: Were you surprised about anything in the tournament? Were you surprised by how well or poorly certain methods performed? Were you surprised by the media attention you got?

Neil: Every year there are always upsets in the tournament, so of course some of those came as a surprise to me.  I was also surprised at how well we did in picking the upsets.  My feeling on upsets is that there are two kinds.  Some upsets happen truly because some teams are less recognized in their ability throughout the season.  Maybe it is because they are in smaller divisions or had a few notable losses and the pundits wrote them off.  Other upsets happen because the best team had a bad day, but if they were to play the same team again, would probably win.  I think the algorithms do a good job handling the first type of upset.  I am not sure anyone can do well consistently picking the second.

I was definitely surprised by the media attention.  When I heard that there may be some media interest in our story, I was thinking we may get a write up in the local paper.  I was shocked when I had a voicemail from a producer at NPR and then the CBS Early Show.


Q: So far, no one has ever submitted a perfect bracket to the ESPN Challenge. Do you think this is possible, at least for a math algorithm?

Colin: I bet someone will eventually get a perfect bracket one day.  It would take a lot of luck for them.  I would like to think we could use math to get a perfect bracket, but it would also take a lot of luck.  A lot comes down to the fact the NCAA selection committee puts together the bracket on Selection Sunday.  The rest is about the unpredictabilty of the human element.  The unpredictability is what draws so many people to watch the tournament.

Neil: It is just as possible for an algorithm as it is for any human being.  Without a doubt, it will take a tremendous amount of luck for either.  That is what makes March Madness so much fun.


Q: Have you tried making brackets in subsequent years? How did the methods do? Did you make any changes?

Neil:  I have continued to use the models in subsequent tournaments and they have continued to do well.  Well enough to win a pool here and there.  I have been using the same methods we used in 2008.  I would love to continue to tinker with them, but there is never enough time.

Colin: We have used our best performers every year since then.  The following year my dad, uncles, aunts, brothers, coworkers all wanted a copy of the magical bracket.  Of course I gave them out, and of course it failed miserably.  The next year I kept it to myself, and I won my office pool.  Last year I gave it out to everyone who asked, and it bombed again.  So this year, it will be kept a secret again.

How are we doing? Checking in with our March Mathness teams

Out of 6.5 million entries, the participants in the March Mathness group of the ESPN Tournament Challenge are doing very well. One third of our group is in the top 20%. Following are summaries from some of those in our group. They describe how they designed their brackets and how they are embracing the excitement of the tournament. The methods mentioned are described in the recently published Who’s #1? By Amy Langville and Carl Meyer.

More reports from our student teams:


Calley Anderson

Calley Anderson is a sophomore English Major with a Film and Media Studies Concentration at Davidson College. She is from Memphis, Tennessee. She is in the 86.1 percentile after the round of 32.

To me, it’s actually pretty shocking that I’m doing so well. I’ve done brackets several times before, but I guess the application of linear algebra gave me an extra kick. That, and the fact that this time around, it was for a class, my decisions were based on the mathematical rankings more so than my personal and emotional thoughts of teams. I used the Colley method (given to our class by Dr. Chartier) and separated the season into 4 parts. If my memory serves me correctly, I weighted Part I as 1/4, Part II as 1/2, Part III as 1, and Part IV as 2. From there, after I put all the teams in the brackets by their mathematical ranking, I used a small amount of personal intuition and changed a few (most notably having Memphis beat St. Louis because it’s my hometown team).

I never thought that my bracket would actually get this far, especially after all of the upsets that occurred in the Round of 32. After taking 2 major hits due to these upsets, I thought that my bracket had reached the end. Being a sports fan in general, I wanted my bracket to have real potential this time around. Most of my previous brackets had Memphis returning to the Championship or going rather far regardless of their season. Everyone else seemed to just fall into a random place, with exceptions for teams that I liked that year. This year, I didn’t let my school or home team influence my decision as much.

Math, however, is far from my favorite. We never really seem to get along. This bracket would be the first case in which I have applauded any type of math as being useful. That’s one of the great things about Dr. Chartier; he takes regular, terrible math and makes its useful and interesting. For this brief moment, I get to be proud that something involving math did me some good. More importantly, this is math that I actually cared about and strived for success with. Math, sometimes, can be awful. But other times, with the right application, it can be fun!

All in all, this has been one of the most memorable experiences in terms of March Madness that I’ve ever had. The intensity that I felt with each game, rather than just a select few, was new but exciting for me. I even went to the lengths to install the Bracket Bound iPhone app so that I wouldn’t miss any game or change in my bracket standings! I feel rather optimistic that I can hold onto my top spot in our class. If I can make it through a round of the most unpredictable upsets, then I can make it to the finish. Even if I don’t, I can still be proud of my short reign of success. I’ve got math on my side and, sometimes, it’s pretty hard to beat that.


Jonah Galeota-Sprung

Jonah Galeota-Sprung is a junior Math Major at Davidson College. He is from South Orange, New Jersey, and he enjoys birdwatching and pickle making. He is in the 79.0 percentile after the round of 32.

Which method did you chose and why?

I ended up using the Colley ranking method with a cotangent weighting function. The choice of Colley was pretty arbitrary, but I chose the cotangent weighting function because I figured I needed a pretty bizarre bracket if I was to have any chance of doing well, given the unpredictable nature of the tournament. We’ll see how far that idea gets me.

Who do you predict will be in the final 4?

Mr. Colley and the cotangent function predict Kentucky, Florida State, Michigan State, and UNC in the Final Four, but they don’t speak for me personally–I’m seeing a Davidson/’Zags final clearly written in my tea leaves.

Things looked good for about half a day. I was on top of the pool, beating the president and my math professors and about 99 percent of the country, too. Dreams of cash prizes and maybe the Fields Medal for cotangentially managing to predict the VCU and Colorado upsets filled my head. I could practically taste the gold on my tongue (the first thing I do when I receive medals is lick them, just to be sure).

Before long though, it all fell apart. I’ve been told things have a tendency to do that. Pesky NC State kept winning, and peskier Missouri had been knocked out in the first round. The un-predictions piled up, and over the course of a weekend half of my Elite Eight was out of the tournament and my national champion had lost to a six seed.  I was able to take some consolation in the fact that Duke was among the casualties, but that did little to assuage the pain I felt when I looked at my bracket shot through with red holes.

There’s always next year.


Barbara Sitton

Barbara Sitton is a junior at Davidson College. She plays on the Davidson Division I women’s basketball team and is a huge basketball fan. She is in the 86.1 percentile after the round of 32.

I’ve only had a little experience with brackets. Before, I chose teams from instinct, it was just for fun. But this time, I used the Colley ranking system to rank teams and predict the outcomes of the games. For the men’s tournament, I predicted Kentucky, Michigan State, UNC, and Ohio State to be in the final four. For the women’s tournament, I predicted Baylor, Stanford, Maryland, and UConn to be in the final four.

I am truly impressed with the way my bracket has held up, although there has been a lot of madness in the NCAA tournament already! I actually have 2 brackets in the group, which I will distinguish as bracket #1 and bracket #2. Bracket #1 has been the most successful so far, and it is in the 86.1 percentile. Some of the biggest upsets have been all of the 12-15 seeded teams who have beaten the 2-5 seeded teams: VCU beating Wichita State, Lehigh beating Duke, USR beating Temple, and Ohio beating Michigan. I’m pretty excited to see what will happen during the Sweet 16!



Paul Britton

Paul Britton is a senior Math Major and Philosophy Minor at Davidson College. He is a campus tour guide and a member of the Sigma Phi Epsilon fraternity. He is from Castle Rock, Colorado and is ranked in the 86.1 percentile after the round of 32.

My family always sponsored a bracket pool and I started participating when I was 8 or 9 years old. I have done at least one bracket, and often multiple brackets, every year since then.

I submitted 2 mathematically based brackets into the PUP pool this year. The first bracket used the Massey rating method with a piecewise game weighting where I divided the season into thirds and weighted the last third of games at .75, the first third at .5, and the middle third at .25. The first third corresponds to the non-conference schedule, which is an indicator of a team’s talent compared to the rest of the country, and is also indicative of games they will face in the tournament itself. The most recent third is the second half of the conference game slate, which is a strong indicator of a team’s recent performance, and thus was weighted more than the other two segments

The second method was an (imperfect) attempt to weight the teams based on their performance according to Dean Oliver’s “4 Factors of Winning,” which you can read about here: Essentially, I gathered statistics on Field Goal percentage and Turnover percentage on offense and defense, and additionally on Rebound rate and Free Throw percentage, then weighted these factors according to Oliver’s specifications. I would have liked to adjust for strength of schedule, but couldn’t figure out an effective way to do so, so I left the initial rankings as they were.


Sport Science host, John Brenkus, gives his take on March Madness

Math editor, Vickie Kearn, interviews John Brenkus, host of ESPN’s Emmy Award–winning show Sport Science. You can follow John and his commentary throughout the tournament at

VK: We have 9 high school and college math classes across the US completing brackets for our March Mathness group on ESPN. They are all using different algorithms to predict their winner. However, we all know that statistics aren’t everything. What are some of the factors that are important to a team’s performance in the tournament from a sport science perspective? What are some of the key things that will make the difference between moving forward and going home?

JB: It is important to also consider where the team is playing. Through research we have found domes are louder than regular arenas because the parabolic curve of the ceiling directs sound waves toward center court. So teams with fans that travel well may have an advantage, particularly in a dome. We’ve also found that arena height affects shooting percentage. Because players rely on peripheral cues, a higher arena will usually result in a lower field goal percentage. Experience, talent and coaching are also important factors between moving forward and going home.

VK: Each year it seems a surprising team makes the NCAA tournament and actually performs really well. Last year it was VCU which lost to Butler in the semifinals. Do you have any thoughts on who might exceed expectations this year?

JB: VCU just won its conference tournament, and because of the team’s experience from last year, they have a shot at making another run. I think whichever team wins the opening round matchup between VCU and Wichita State is very capable of making a deep run. Also, Belmont is going to be a tough out for anyone. Offensively, the Bruins are great. They are in the top five in points per game and assists. They will give Georgetown all it can handle.

VK: Are there any teams that you think might under perform?

JB: Number one overall seed Kentucky has a tremendous amount of talent, but the Wildcat’s youth may present a problem in the tournament. Winning the tournament requires a blend of talent and mental toughness, and it will be interesting to see how Kentucky’s youthful talent handles the pressure.

VK: For many of the mid-major schools, the only way to make the tournament is to win a conference tournament. Davidson is in this year because they won the SoCon tournament. Duke knew they were going to the dance before the ACC tournament. Did they have anything to gain by winning the tournament?

JB: Of course, they have a banner to gain by winning the conference tournament. College kids usually want to leave their mark, and one way to do that is to win their conference tournament.

VK: Players will get hurt as the tournament progresses. Although I am sure it depends on the type of injury and its severity, how important is the decision to put in an injured player? Suppose you are in the championship game and you are in double overtime?

JB: That is really case-dependent. Injuries to the head (like a concussion) are obviously more serious and a doctor should determine playing time. Other injuries, however, require a consensus decision between player, coach and medical staff. Another factor to consider is that, when a player gets injured in a big game, their epinephrine, or adrenaline, kicks in. This may cause the player to have a fight-or-flight response and play through the pain unfazed.

VK: During the tournament a lower seed team could do really well and have to play a lot of games in a short period of time. What can they do to pace themselves?

JB: In the NCAA tournament, it is all about preparation. Teams that are well trained for endurance will be much better conditioned for the grind of the tournament.

VK: Schools with major basketball programs like UNC and Kentucky have little trouble recruiting. But for a mid-major school, doing well in the NCAA tournament can really help in recruiting the following year. Since this fame may be short-lived, what should a coach look for when recruiting the next season’s team?

JB: I think the most important aspect when recruiting for any team is getting a guy with a good work ethic. All of these kids are extremely athletic and filled with talent, but it’s usually the players who take the time to prepare that end up becoming great.

VK: Although we are encouraging people to use math to select their brackets, there is always that special something that is tossed in, whether it is asking your dog to help you pick or selecting schools that have the most red-headed players, or just all the schools you wish you had attended. I know you must have heard of some crazy ways to select brackets. What are some of your favorites?

JB: On Sport Science we had a chicken fill out a bracket. It didn’t do so well, guessing only 30 percent of the winners. We also brought in 100 people to our lab and had them fill out an empty bracket. Guessing based only on seed numbers, they did better than the chicken, and guessed 60 percent of the winners over the last 25 years…without even knowing the names of any of the teams!

VK: Will you fill out a bracket? Do you have a special method you use?

JB: Through testing, we have discovered that every method has flaws. When picking based on a team’s color, we found teams with blue jerseys have won 68 percent of the national titles in the last 25 years. The mascot with the highest championship winning percentage is a mammal, which has won 48 percent of the national titles over the last 25 years.  Our consensus crowd bracket has fared pretty well, guessing 60 percent of the winners over the last 25 years, and in 2007 specifically, our crowd of 100 random people picked 75 percent of all winners even though they filled out blank brackets with only the seed numbers listed.

About John Brenkus
John Brenkus has spent the last decade studying and popularizing the unique characteristics of the world’s greatest athletes. A co-founder of BASE Productions, he co-created the groundbreaking series Fight Science for the National Geographic Channel and serves as the on-air host, co-creator, and executive producer of ESPN’s Emmy Award–winning show Sport Science.

Davidson College basketball coach, Bob Mckillop, explains March Madness from an inside perspective

The Davidson Wildcats beat Western Carolina 93-91 in the Southern Conference Tournament on March 5 and received an automatic bid to the NCAA Men’s Basketball Tournament. The following interview between Vickie Kearn (VK), Princeton’s math editor and Men’s Basketball coach, Bob McKillop (Coach), reveals what lies ahead for them in March Madness and how getting a high ranking after the tournament helps in recruiting new players.

Vickie Kearn: Congratulations on winning the Southern Conference Championship. It was a fantastic finish. What is the pressure like having to win in double overtime?

Coach McKillop: The experience of what we just did is draining and  exhausting  because of dealing with three successive games, three successive preparations, and three days of anxiety. To even put yourself into the position of thinking about what is the first round  game…’s impossible. You want to smell the roses, you want to celebrate what you have accomplished. It’s like climbing Mount Everest and getting to your first peak and trying to get onto the next peak without getting a deep breath. We are getting a deep breath right now and we’re fortunate that our post season tournament is a week prior to selection Sunday and we have a couple of days to  reenergize. With the pressure of our tournament reenergizing is so valuable.


VK: How are you preparing for the next game?

Coach:  I believe it is a 12 month journey for every program in America.

As soon as their season ends the previous year, they begin planning, players and coaches, to get back to the tournament. That’s the end-game.

It’s the ultimate goal, so your 12 month journey can either continue or it comes to a crushing end as you stare at another 12 month journey.  At the end of your season, you don’t look at the next day after your final game, you look at the next year.

To expend 12 months of thought, effort, and energy and see it come to a crushing finish, there is quite a finality about it.  The objective joy is to have this journey continue. Winning the Southern Conference tournament is just a step in the process, but at least it is a step up.

It is like a stairway to heaven but if you don’t get on to that first step it’s a dramatic drop.


VK: Davidson had to win the Southern Conference tournament to make it into the NCAA tournament. What about teams that have an automatic bid and will be a part of the NCAA tournament whether or not they win their division. Do coaches tend to keep their best players on the bench so they won’t risk being hurt before the NCAA tournament?

Coach: You could look at it from the standpoint of are you content with yesterday’s glory or do you want your journey to continue.  And for some people they are just happy to have reached this level. They are just happy to get into the tournament and if you are just happy to get into the tournament you are going to be facing a very quick exit.  You must think you can accomplish more and you must understand this is just the first step of the journey. This is the only way you can mentally prepare yourself to continue in the tournament.

Basketball is a game of rhythm. Any time you interrupt rhythm, you invite chaos. Continuity is so important. I will give you a typical season-type experience. You have a key player who is hurt. He is able to play in a game but he is not 100%.The temptation is to put him on the court because you need what he is when he is healthy, but in reality it might be better not to play him because he is hurt.  He is not 100% so he is not going to be in the rhythm that is necessary for the team to have rhythm.  We experienced that with Stephen Curry back in 2009. Stephen hurt his ankle very badly on a Saturday and we had an important game the following Saturday.  He wanted to play but he wasn’t 100%. We played him but he did not play with his usual rhythm and of course we lost the game. I think rhythm is a big factor for individuals as well as collectively for the team.


VK: Now that the brackets have been revealed, are there any teams you hope to play?

Coach:  No. If I start  thinking about who I would like to play I am going to have  anxiety about preparing and what I want  to do right now is prepare my team to be the best they can become. One of the joys of teaching is to teach your team to get better-not to prepare a team exclusively for one opponent.


VK: Do your coaching strategies change from round to round? I imagine playing in the first rounds is quite different than when you made it to the Elite 8 for example.

Coach: I don’t have a lot of experience at that.  But I believe the rhythm of the season becomes the rhythm of the post season and that’s the lesson I learned from the Elite 8 year.


VK:  As you move forward does the confidence of your players increase or do they get more nervous?

Coach: Absolutely. The confidence is accentuated by the perception that surrounds the whole tournament by the people associated with your program as well as the exposure in the media. A team that has the fortune of winning receives even more exposure from the media and there is a change in the perception of alums and fans and all of  a sudden, their inspiration, their  energy, their embrace now feeds the team’s own appetite so it becomes a bit more inspired. People who were just there for the ride are now thinking this ride may be taking us somewhere.


VK: In addition to promoting sports and math, we are kicking off the publication of Who’s #1? by Amy Langville and Carl Meyer. The book is all about rating and ranking of all kinds of things but this month we are mostly concerned with basketball. When your team made it to the Elite 8 and ended the season ranked #9 in the ESPN/USA Today poll, did it make a difference in your recruiting?

Coach: Absolutely. We had a presence on the national stage instead of the regional stage. It was an identification and that identification also became associated with Stephen Curry who was like a Pavarotti for us-a once in a lifetime performer.  The combination of what we did in the Elite 8 year plus the presence of a national star in Stephen Curry tremendously impacted our recruiting.  And what’ is interesting  is that the current junior class that we have  which is a potent part of our team were recruited  after the 2008 season.


VK: Has your success in 2008 continued to help in recruiting?

Coach: Fame is fleeting. Big programs like Duke and Kentucky can do it every year but it is more difficult for a mid-major program.


VK: How did the student body react to your success in 2008?  I remember that the board of trustees provided funding for tickets, transportation, and lodging for any students who wanted to attend the Sweet 16 and Elite 8 games.  Did the students take advantage of this offer? Did your success make a difference in attendance at basketball games the following season?

Coach: Over 65% of the student body went to see us play in the Sweet 16 and Elite 8 rounds. It really pumped up home attendance the following season.

Fans were lined up outside before the game and others were scalping tickets.  Our current attendance is about 80 -85% of what it was after the Elite 8 year.


VK:  Every year a team receives a lot of attention for surprising everyone with their play. Huge upsets also occur in the tournament. Who do you think the surprise of the season will be?

Coach: I can answer that in a general way. There usually is a team that performs really well even when they are not expected to. In 2006 it was George Mason, in 2008, Davidson, Butler the past 2 years and Virginia Commonwealth University last year. The pressure on mid-major programs to reach the level of these teams is extraordinary. That is also true for higher level conferences. The feeling is, if they can do it, why can’t you?

Administrators, alums, fans expect that their team can make it to the Final 4. They know it can and does happen. The pressure has increased tremendously.


VK: We have 9 high school and college math classes across the US completing brackets for the March Mathness site on ESPN. They are all using different algorithms to predict their winner. However, we all know that statistics aren’t everything. What are some of the factors that are important to a team’s performance?

Coach: The important elements are collective talent, experience, and confidence and the mental toughness to perform with consistency. There are ebbs and flows in a team’s success but these are the vital factors.




This is Bob McKillops’ 23rd season with the Davidson Wildcats. To read more about him see



Math Improves March Madness Predictions: Tim Chartier Interviewed on Inside Science

Inside Science Television spoke with Tim Chartier about how math can be used to predict the winners of March Mathness. They also provide additional resources for those who wish to learn more or teach this in their classrooms.


Tim notes in the interview that: “To do well in bracketology, you need to know how teams will do earlier. It’s often those teams that are very difficult to predict and those games that often our methods are picking up.”

He also reveals that, using data available at the time of the interview, his methods currently predict Kentucky will be the winner. Does that match up with your bracket?

You can view the complete article and the video here: