Greg Newman is currently at the top of the March Mathness ESPN Tournament Challenge leaderboard with two separate brackets and is ranked 131,052 out of 6.5 million brackets. That means that only 2% are doing better than he is. Greg is a senior Political Science major at Davidson College who spends a lot of time working on Computer Science/Mathematics. Last summer he interned at ESPN and he continues to work for them while in school. We asked him to describe how he picked his brackets this year.
Greg Newman on his “picks” for March Mathness
I think I would fall into a category of liking both math and sports but, since I have been obsessed with sports since I was three and work at ESPN, I think I’m more of a sports fan. I have two brackets that are doing very well. I joined your group with the second one and think I will explain them separately.
My “Picks as an analyst” Bracket:
As the name suggests I made picks as an analyst with little math. I did use “simple math” (by simple I mean something that I could explain to someone who never took Calculus but has basic knowledge of probability theory).
The major advantage to this method is the ability to look at match-ups. I would compare the traditional basketball statistics (points, rebounds, strength of schedule) and would do this for each match-up. I also used my own head when picking (this was both an advantage and a disadvantage). Having seen many of these teams play I had an idea of teams that would do well or would not. However, I had not seen all these teams play and did not have full data information.
This was the bracket that took the most time for me to complete since I was using math and my own opinion while making it. For an example of how watching a team can deceive you, I would talk about Missouri. I had seen them play a few times and they always looked very good. In this bracket I had them getting into the elite eight. As most will know, they lost in the first round to Norfolk State (in a huge upset). I had not watched any Norfolk State basketball and did not know how balanced their offense was (in the game against Missouri they had four players score in the double figures).
My “Harvard” Bracket:
At this point I feel like I should note that I do not attend Harvard nor does it have anything to do with Harvard doing well in the tournament (it had them losing in the first round, which they did).
This was very mathy. I had looked into many different methods including Colley, Massey, LRMC, Pythagorean ratings, Power rankings, S-Curve rankings, ELO and a bunch of other “saber metric” like ratings and rankings. The reason I called it “Harvard” was that it is based off of the Harvard College Sports Analysis Collective blog. Specifically, I looked at their “Survival bracket.” I really liked how they used numbers/analytics to try to make “intangibles” tangible. An example would be tournament experience, which experts agree is important. You can look at past tournament minutes play and say it correlates (and I would say correlates pretty well) with experience. It also had a ranking for consistency, which is hard to measure but incredibly important.
The idea of survival is also very important and is crucial to the success of this bracket. Even with the crazy upsets (that this bracket did not get) all of the elite eight teams are still playing. This means that my PPR (Points Possibly Remaining) is very high at 1280 and means that this bracket could possibly end up doing even better (since many people have lower PPRs) at the end of the tournament.
Tips in selecting a bracket:
Pay less attention to seeds/history.
A committee chooses seeds and we can’t always figure out why a team is given the seed. The art of “bracketology” is something entirely different and hard to understand. At some point a number 1 seed will lose to a 16 seed (even though it hasn’t happened yet). Coming into the tournament 2 seeds were 104-4 against 15 seeds (96%), this year they are 106-6 (95%) but does that mean number 15 seeds have a better shot next year? Also, even if you magically figure out what seeds will advance there are four of each seeds!
Don’t try to be perfect.
A perfect bracket is hard! Of everyone in the ESPN bracket, everybody had at least two wrong after the first round. The current leader had six incorrect picks. Don’t worry about being perfect, chances are nobody else will be either.
Rankings are good but Ratings are better. Some people just looked at rankings. Many of the teams were rated very closely, so a team ranked five spots ahead of another may not be a sure win.
What I wish I did:
I really focused on getting the most right, not highest percentile. I wish I had tried to pick the upsets (almost) nobody else picked. This would make me seem very smart, help me in brackets with different formats and possibly given me an advantage. If 95% of the country has team A beating team B but my model was team A only has a 60% chance, it would probably make sense to pick team B (note: I probably would not pick team B to advance further as to minimize the penalty and because neither team seems as good as everyone else thinks).
Tried another style of tournament
I like that each round is worth the same number of points (so each game as you get further in the rounds is worth more points). I wonder how well different models would work in different bracket scoring systems.
Saved/Organized all of my data better
I got a lot of data and all of it around the same time. I’m not sure that I will even be able to find all of it after the tournament is over.
Made more brackets
I made ten brackets in total. I would have made so many more with each method individually and different combinations of all of them but scoring them myself was not something I had time for.