At least the visiting Big Ten team has a week to acclimate to the time zone.) Over the last ten years, our method has predicted the winner in 62.4% bowl games (196 of 314 games). (Well, the Rose Bowl might be a home game for USC. College football bowl games are a convenient test set since these games are played at neutral locations. The fraction of times this team actually wins gives an accuracy for the algorithm. This predicted point spread gives one team a higher likelihood of winning the game. The prediction really means that there’s a 50% chance Michigan beats Virginia Tech by more than 6 points, while there’s a 50% chance Michigan wins by less than 7 points or loses. For example, Michigan will beat Virginia Tech by 6.7 in the Sugar Bowl.Ĭlearly, this prediction is wrong, since Michigan can’t win by a fraction of a point. The difference in the ratings of two teams gives a predicted margin of victory at a neutral site. Predicting a margin of victory for each game From 2009 through 2011, the Broncos finished the season in the top 5 of our rankings. Accounting for strength of schedule is the only way to compare Boise State with more well known teams like Alabama and Texas.Īnd our numbers like Boise State. Boise State remained on the national radar despite playing in a lesser known conference with weaker opponents. They burst on the national scene with a win over Oklahoma in 2007 Fiesta Bowl. These ratings determine our rankings.Īs an example of why strength of schedule matters, consider the Boise State college football team. The result is a rating that gives a predicted margin of victory against an average team in the league. Our algorithm adjusts this raw margin of victory for schedule strength. A good team that plays a weak schedule could have a higher margin of victory than a top team that plays a difficult schedule. It’s difficult to rank teams by this raw statistic. As a simple example of sports numbers, consider a team’s margin of victory, or points scored minus points allowed per game. Our algorithm takes sports numbers and adjusts them for strength of schedule.
Let’s look at 10 things you should know about how this works. Our methods have been developed specifically for sports, and they can answer questions such as whether your team will win its next game or who has the best passing offense in the country. It takes this unstructured mass of numbers and outputs rankings that provide sports insight. Our sports analytics uses mathematics and computers to make sense out of this data. There have been over 1100 meaningful international soccer matches over the last 4 years. In 2011, college basketball teams in Division I played over 5400 games. With each game comes a final score, a box score with statistics such as fumbles lost, and a description of what happened on each play. In 2011, college football teams in Division I played 1430 games against each other.
And there’s a mountain of sports numbers. The Power Rank crunches numbers to better understand sports.
0 kommentar(er)
