The SEC Tournament is set to tip-off Wednesday evening when the South Carolina Gamecocks take on the Mississippi State Bulldogs. While that game won’t have much on the line, many teams have everything to play for during the conference’s annual tournament. Teams including Kentucky, Alabama, Ole Miss, and Tennessee are all fighting for their NCAA Tournament lives one week before the actual madness begins. While the games are a number of days away, predictions on how things will shake out are already out in full force. Whether it be on Twitter or a legitimate news source, many people have differing opinions on who the victor will be.
One set of predictions often examined during tournament time are Ken Pomeroy’s computer predictions, more specifically his “Log5″ forecasts. The Log5 method uses a team’s winning percentage in order to predict their percentage chance of advancing to a specific round. While those predictions are excellent, they don’t predict the score of games that far in advance. Also, they haven’t been released yet. Given that I’m impatient, I used my own mathematical formula and paired it with Pomeroy’s data to predict scores of the SEC Tournament.
First, you should note my formula isn’t the exact same as Pomeroy’s, so it’ll be slightly different from what his system would predict. However, it usually comes within 1 or 2 points of his forecasts. Secondly, these predictions are based off how strong (or weak) the teams are currently. As the tournament progresses, score predictions will change depending on how teams play. Finally, to ensure maximum accuracy, Vanderbilt was given a semi-home court advantage over Arkansas and Kentucky was awarded the same advantage against Arkansas and Missouri. So without further delay, here are the mathematical predictions for the SEC Tournament.
The numbers above a team’s name indicates a score in the previous round. For example the “65-61″ over South Carolina in game four indicates the game one score prediction.
[powered by WordPress.]
Bill Keightley Report : Never to be forgotten.
9 queries. 0.363 seconds