#MammothMonday: PUP’s pups sound off on How to Clone a Mammoth

The idea of cloning a mammoth, the science of which is explored in evolutionary biologist and “ancient DNA expert” Beth Shapiro’s new book, How to Clone a Mammoth, is the subject of considerable debate. One can only imagine what the animal kingdom would think of such an undertaking, but wonder no more. PUP staffers were feeling “punny” enough to ask their best friends:

 

Chester reads shapiro

Chester can’t get past “ice age bones”.

 

Buddy reads shapiro

Buddy thinks passenger pigeons would be so much more civilized… and fun to chase.

 

Tux reads shapiro

Tux always wanted to be an evolutionary biologist…

 

Stella reads Shapiro

Stella thinks 240 pages on a glorified elephant is a little excessive. Take her for a walk.

 

Murphy reads shapiro

A mammoth weighs how much?! Don’t worry, Murphy. The tundra is a long way from New Jersey.

 

Glad we got that out of our systems. Check out a series of original videos on cloning from How to Clone a Mammoth author Beth Shapiro here.

March Mathness 2015: The Wrap Up

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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

PUPSelfie2

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 SportsReference.com, 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.

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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.

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 marchmathness.davidson.edu. 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)

Calculus predicts more snow for Boston

Are we there yet? And by “there,” we mean spring and all the lovely weather that comes with it. This winter has been a tough one, and as the New York Times says, “this winter has gotten old.”

snow big[Photo Credit: John Talbot]

Our friends in Boston are feeling the winter blues after seven feet of precipitation over three weeks. But how much is still to come? You may not be the betting kind, but for those with shoveling duty, the probability of more winter weather may give you chills.

For this, we turn to mathematician Oscar Fernandez, professor at Wellesley College. Professor Fernandez uses calculus to predict the probability of Boston getting more snow, and the results may surprise you. In an article for the Huffington Post, he writes:

There are still 12 days left in February, and since we’ve already logged the snowiest month since record-keeping began in 1872 (45.5 inches of snow… so far), every Bostonian is thinking the same thing: how much more snow will we get?

We can answer that question with math, but we need to rephrase it just a bit. Here’s the version we’ll work with: what’s the probability that Boston will get at least s more inches of snow this month?

Check out the full article — including the prediction — over at the Huffington Post.

Math has some pretty cool applications, doesn’t it? Try this one: what is the most effective number of hours of sleep? Or — for those who need to work on the good night’s rest routine — how does hot coffee cool? These and other answers can be found through calculus, and Professor Fernandez shows us how in his book, Everyday Calculus: Discovering the Hidden Math All around Us.

This book was named one of American Association for the Advancement of Science’s “Books for General Audiences and Young Adults” in 2014. See Chapter One for yourself.

For more from Professor Fernandez, head over to his website, Surrounded by Math.

 

Photo Credit: https://www.flickr.com/photos/laserstars/.

Place Your Bets: Tim Chartier Develops FIFA Foe Fun to Predict World Cup Outcomes

Tim ChartierTim Chartier, author of Math Bytes: Google Bombs, Chocolate-Covered Pi, and Other Cool Bits in Computing has turned some mathematical tricks to help better predict the outcome of this year’s World Cup in Brazil.

Along with the help of fellow Davidson professor Michael Mossinghoff and Whittier professor Mark Kozek, Chartier developed FIFA Foe Fun, a program that enables us ordinary, algorithmically untalented folk to generate a slew of possible match outcomes. The tool weighs factors like penalty shoot-outs and the number of years of matches considered, all with the click of a couple buttons. Chartier used a similar strategy in his March Mathness project, which allowed students and basketball fans alike to create mathematically-produced brackets – many of which were overwhelmingly successful in their predictions.

Although the system usually places the most highly considered teams, like Brazil, Germany, and Argentina at the top, the gadget is still worth a look. Tinker around a bit, and let us know in the comments section how your results pan out over the course of the competition.

In the meantime, check out the video below to hear Chartier briefly spell out the logic of the formula.

Happy calculating!

LA Times Article with Tim Chartier

Davidson math professor, PUP author and bracketology expert, Tim Chartier, discusses the math behind March Madness with the LA Times.

chartierMathematician Tim Chartier has the best job on Earth once a year: when the NCAA men’s basketball tournament begins, so does March Mathness.

His telephone rings, he’s on the radio, he’s talking to ESPN, and for once he can explain what exactly he does for a living at North Carolina’s Davidson College.

“For the first time in my life I can talk about what I’m doing, on a higher level, and people understand,” Chartier said.

What Chartier does is use complex math to win the Final Four pool on a regular basis. How regular a basis? He’s been in the top 3%  of the 4 million submissions to ESPN’s March Madness tournament challenge, which is arguably the major league of sports prognostication.

“That’s when we said, whoa, this thing really works,” Chartier said of his brush with sports handicapping superstardom.

Blame it on tiny Butler College. Chartier’s math class was among those to recognize that fifth-seeded Butler was destined for the finals in 2010. That was the second year Chartier started making bracketology — the art and science of picking winners among 68 teams in a single-elimination tournament — part of his syllabus. That’s right: take Chartier’s course and you’ll be deep into basketball come March.

Source: Los Angeles Times, “March Madness puts Davidson math professor in a bracket of his own”  http://touch.latimes.com/#section/-1/article/p2p-74922641/

 

Skipping to the good stuff — who is going to win March Madness this year? At least according to the math?

So, who did Chartier pick? With a simplified Massey method (which gives his students a fighting chance), he agrees with Dick Vitale: Louisville wins it all, in this case beating Florida, then Indiana, which beats Gonzaga.

By the Colley method, the Final Four are Duke, Kansas, New Mexico and Miami, with New Mexico winning.

Which system will do the best?

“That’s the madness for us in the math!” Chartier said.

 

Read the complete article here: http://touch.latimes.com/#section/-1/article/p2p-74922641/

How did they create their brackets? Two Davidson students explain.

Maddie Parrish is senior Economics major with a Communications Studies concentration at Davidson College. She plays Division I field hockey.

Maddie Parrish - DCFH

March Madness. 65 elite NCAA Division I Basketball teams competing to win it all, the NCAA Tournament Championship. Every year fans from across the nation create brackets to predict who will ultimately be #1. I am one of those fans, and I’m excited to share my story. My name is Maddie Parrish and I am a senior Economics major with a Communication Studies concentration at Davidson College, a small, highly selective liberal arts school twenty minutes north of Charlotte, NC.  We are also the alma mater to such basketball phenoms as John Belk ’43, Terrence Holland ’65, Kenneth Wilson ’84, Mike Maloy, and Stephen Curry.  My hometown is Chester, VA, a suburb of Richmond and I have interests in economics, communications, sports, and many other topics. In the fall of 2012, I wrapped up my fourth and final season as a member of the Davidson Wildcats NCAA Division I Field Hockey Team. Being a student-athlete at Davidson has clearly shaped my college experience. It has made me who I am today by teaching me many lessons about dedication, respect, passion, heart, and life in general.

As a student-athlete, the pride I have in my school and its’ athletic teams is enormous. I am a huge fan of college basketball and I am close friends with many of the Davidson Basketball Team members.  Our boys just won the 2013 Southern Conference Championship for a second year in a row and the entire school is supporting them in their March Madness journey to the NCAA Championship. My personal connections and interest in Davidson basketball are my main reasons for completing a March Madness bracket this year.

I am an athlete, a sports-lover, and a passionate sports enthusiast. Although a rookie to Bracketology, I know that using mathematic strategies is the best way to create a successful bracket. Being an Economics major, math comes easily to me and I find it very enjoyable. This Spring I am taking Dr. Tim Chartier’s MAT 110 – Finite Math course here at Davidson in which we spend a good chunk of class time learning about linear systems and how to solve them. The concepts of linear systems are the key behind ranking the right teams in our bracket by using matrices and weighted values. In class, we learned about the Colley Method for sports ranking, which utilizes winning percentage to determine each team’s ranking. Another method of sports ranking is the Massey Method, which utilizes actual game scores in the regular season to determine each team’s ranking. With both methods, there is an opportunity to choose your own weighted values for specific times during the season. For example, it is possible to weight games that occurred in the beginning of the season less than games mid-way through the season and at the end of the season. If games at the end of the season are weighted more than 1 game, say each game counts as 2 games; the weight is capturing a team’s final push or momentum. A team’s momentum is explained by their ability to win games at the end of the season, which is admirable because the season is so long and competition may be very tough.

For my March Madness bracket this year, I am choosing to use the Colley Method because I am curious to use my newly learned knowledge from class in a life application and see how well it really works. I split the season into four even intervals, one for games at the beginning of the

season, one for games leading up to mid-way through the season, one for games in the second half of the season, and one for games at the very end of the season. I am creating my weights for each season interval based on the hypothesis that as a basketball team plays more games, it gains momentum and wins more frequently. I also am using the Davidson Men’s Basketball schedule results from this year to create my weights. In the first two intervals of the season, the team lost a good number of games. However, they have not yet lost a game in the third and fourth intervals of this year’s season. Using this intuition, I am weighting the first interval at 0.5/1 game, the second interval at 0.75/1 game, the third interval at 1.25/1 game, and the fourth interval at 2/1 games. This means that games played in the beginning of the season are only worth half of a game and games at the end of the season are worth two games. Therefore, if a team is winning more at the end of the season due to momentum then those wins will be worth more in my ranking method.

I understand that using the Colley Method may not factor in specific scores of games and because of this will not capture strength of opponents throughout the season. Yet, I am confident that using the Colley Method and the particular weights I have chosen will produce solid results. After the 65 teams (1 play-in) were announced on Selection Sunday, I filled in my bracket according my method rankings. Of course, I ranked Davidson higher due to the success of their season thus far and due to my personal bias. :)

As a student-athlete, I have always been interested in how we can harness the talents of individual teams throughout the nation and celebrate sports through common mediums such as love for the game, competition, and passion for your school. The NCAA Division I Men’s Basketball Tournament provides a venue for all of these values. It also allows for fans to express their passion for the game, pride for their school, and their intuitive math sense in a fun way. Using my intuition as an athlete and my knowledge of math, I have created a bracket that I hope will perform well during the March Madness basketball tournament. I am curious to see how it turns out and wish the best of luck to all of the teams who have the honor and privilege of participating in the tournament! Here at Davidson, we have a saying that runs throughout campus each day that follows “It’s a Great Day to be a Wildcat!” Hopefully, my bracket will sing this tune throughout the tournament! Go ‘Cats!

 

Kyle Snipes is a senior Math major at Davidson College. He is from Indian Trail, NC. He is a volunteer Younglife leader and a lifelong basketball fan. He will be spending this March Madness season cheering on the Davidson Wildcats!

Snipes

I have competed in bracket pools for a long as I can remember. In the past I have picked games based on what I know about basketball with a fairly high success rate. Since my senior year of high school, I have won at least one of the couple of pools that I have competed in. This will be my first year applying mathematics to my March Madness selections.

I will use ranking methods adapted from the Colley and Massey ranking methods. Since all NCAA tournament games are played at neutral sites, I will count road and neutral site games as a full game, while weighting home games as partial games to account for any homecourt advantage a team might have during the regular season.

I will weigh different portions of the season differently. Generally teams will play the toughest part of their nonconference schedule in preseason tournaments and standalone nonconference games early in the season. On the other hand, a team’s performance early of the season is less likely to be representative of their performance at the end of the season. Therefore, I will give games during the first quarter of the season a weight of 0.7. The second quarter of the season is still a bit early to be representative of a team’s performance come tournament time. Since there are generally fewer nonconference games during this part of the season, I will give these games a weight of 0.6. Teams begin playing the important part of their nonconference during the third quarter of the season. It is also the point in the season where teams poised to make a deep run in the tournament will begin hitting their stride. I will give the games during this quarter of the season a weight of 0.85. Teams that succeed during the last quarter of the regular season are the teams that will be hot coming into the tournament. I will give these games a weight of 1. I have noticed that teams that rely solely on winning their conference tournaments to get to the Big Dance will be burnt out by the time they play the next weekend. Furthermore, teams that have already secured a spot in the Big Dance may have more of an incentive to rest players and avoid injury than to perform to the best of their potential during their conference tournament, making these games even more illegitimate. Therefore, I will only use data from regular season games in my rankings.

One last idea I would like to implement into my ranking is to reward teams who go on long winning streaks as well as teams who are able to beat teams on long winning streaks. I imagine that this will help pick out teams who are able to win successive games, as they must do in the tournament, as well as the giant killers who are able to beat teams that are in the middle of a strong run. If I have the time, I will do this by incrementing a game’s weight by 0.05 for each game in the winning streak for whichever team comes into the game with a longer winning streak. I will cap this at a weight of 1.5 games to avoid over-rewarding strong teams playing in weak conferences in which long winning streaks are common. I plan on submitting three bracket– two using different ranking methods and one where I will synthesize the math with my intuition. I’m excited to see how my picks stand up against the rest of the country!

 

The Madness begins!

Don’t forget to join our ESPN bracket challenge group before Thursday, March 21st!

To learn more about March Mathness this year and to glean tips from years’ past, please visit the March Mathness site.

 
Use the widget below to explore Tim Chartier’s lectures on March Mathness and to find more advice on how to fill out your brackets this year.

[Video] New mathematical models help rank sports teams

But will these new mathematical models make sure my team is ranked higher? That is the truly important question.

For more on mathematical systems of ranking and rating, please see Who’s #1?: The Science of Rating and Ranking by Amy N. Langville & Carl D. Meyer. You might also want to peruse our March Mathness series of blog posts here where students put these mathematical models into action during March Madness. If your school is interested in participating in March Mathness next year, please contact PUP Math Editor Vickie Kearn.