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Incorporating Analytics: Make Sure Your Bracket Doesn’t Bust Next Year

Each March life seems to stop for fans and non-fans to fill out brackets and watch basketball. Starting each Selection Sunday, the search for the perfect bracket begins and as of 2017 tournament -it is still alive. Between 60 million and 100 million brackets are filled out each year by guessing, gut, sports knowledge, and analytics. According to most sports websites, the chances of picking the perfect bracket are in the neighborhood of 1 in 2 billion. Yet, each year the perfect bracket seems to be a little closer in reach. In the 2017 tournament, an individual broke the record with 39 correct straight picks, but Purdue’s win over Iowa State on Saturday ended the streak.

Now that every 2017 bracket is officially busted, it’s time to start planning for your 2018 bracket! Below are some ideas from industry experts on how to incorporate analytics into your picks.

“Four Factors Score”

A common thought process in basketball analytics identifies four key elements which correlate most closely with winning games. Former Sacramento Kings and ESPN Director of Analytics Dean Oliver coined these the Four Factors of Basketball Success — shooting, turnovers, rebounding and free throw proficiency.

Each of these factors hold varying weights, and we can apply them to determine a team’s likelihood of success, in this case within the NCAA Tournament. Using a model that measures these factors — eight total stats when accounting for both a team’s offense and defense — we’ve unofficially created a “Four Factors Score” and an adjusted ranking for each team in the Field of 68 to help pick the bracket.

Offensive and Defensive Effective Field Goal Percentage (weighted 40 percent) — a shooting percentage which adjusts for a 3-pointer being worth more than a 2-pointer.

Offensive and Defensive Turnover Percentage (weighted 25 percent) — an estimate of turnovers per 100 possessions.

Offensive and Defensive Rebound Percentage (weighted 20 percent) — an estimate of the percentage of available rebounds a team grabs.

Offensive and Defensive Free Throws Made per Field Goal Attempt (weighted 15 percent) — how often a team gets to the free throw line and how often they convert.

Taking each school’s national ranking out of 351 in each category and reversing it (top team gets 351 points), then applying the weighted rate, gives you what we’ll conveniently call the Four Factors Score, or 4FS.

Full article text available via Sporting News, 3/16/17.

Forecasting The 2017 NCAA Tournament

Live win probabilities

Our interactive graphic will include a dashboard that shows the score and time remaining in every game as it’s played, as well as the chance that each team will win that game. These probabilities are derived using logistic regression analysis, which lets us plug the current state of a game into a model to produce the probability that either team wins the game. Specifically, we used play-by-play data from the past five seasons of Division I NCAA basketball to fit a model that incorporates:

  • Time remaining in the game
  • Score difference
  • Pre-game win probabilities
  • Which team has possession, with a special adjustment if the team is shooting free throws.

Excitement Index

Our March Madness “excitement index” (loosely based on Brian Burke’s NFL work) is a measure of how much each team’s chances of winning changed over the course of the game and is a good reference for picking the best games to flip to. The calculation is simple: It’s the average change in win probability per basket scored, weighted by the amount of time remaining in the game.

Elo Ratings

Otherwise, the methodology for our men’s forecasts is also largely the same as last year. But we’ve developed our own computer rating system — Elo — which we include along with the five computer rankings and two human rankings we used previously.

Our methodology for calculating these Elo ratings is highly similar to the one we use for NBA. They rely on relatively simple information — specifically, the final score, home-court advantage, and the location of each game. (College basketball teams perform significantly worse when they travel a long distance to play a game.) They also account for a team’s conference — at the beginning of each season, a team’s Elo rating is regressed toward the mean of other schools in its conference — and whether the game was an NCAA Tournament game.

Full article text available via FiveThirtyEight, 3/13/17.

 

To learn more about how the BWF Insight team uses analytics tools like forecasting and predictive analytics to assist fundraising shops all around the world, check us out on the web at BWF Insight.

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