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Where "SCORING1" and "SCORING2" are the score ratings of the two teams, and "scale" is the score scaling factor (4.2 for football, 1.8 for baseball, 2.15 for basketball, 0.8 for hockey, and 0.7 for soccer). X = ( rating - opponent +/- home field ) * F The SCORING rating is an indication of whether the team tends to be involved in high- or low-scoring games. (Using the 'predict score' form on the web site gives 64.8%, the difference resulting from rounding.)Ī calculation that is more complex is the prediction of game outcomes, which is done using the factor inside CP above as well as the team's scoring ratings, SCORING. Had the game been played at Maine, the odds would have been nearly 50-50, emphasizing the importance of neutral venues for championship games. Calculating CP(0.389), one finds a 65.1% chance of Minnesota winning a rematch. From the 2002 hockey ratings, Minnesota's predictive rating is 1.177 and Maine's is 0.993, while the home field factor is 0.205.
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Below is a table of some sample values.Įxample: A rematch of the 2002 NCAA hockey championship game, Maine at Minnesota. The difficulty with calculating this is that CP(x) is not a trivially-evaluated function.
![power rankings sports calculator power rankings sports calculator](https://s3media.247sports.com/Uploads/Assets/594/116/10116594.jpeg)
Where ngames1 and ngames2 are the number of games played by the two teams. I will skip the math and merely note that this uncertainty changes the equation above to: As mentioned above, there is a nonzero uncertainty in the team ratings, with the 1-sigma uncertainty in a team's rating equal to 1/sqrt(ngames). Where "rating" and "opponent" are the team's rating and the opponent's rating, and "home field" is listed at the bottom of the ratings. Score = CP ( rating - opponent +/- home field ), The odds of a team winning is calculated as: (For interest, there is also a CGI script that will show a plot of the game-by-game team strength as a function of time during the season.) A form at the bottom of the rankings page will call a CGI script that will do the calculations below the information here is just for reference. Specifically, these ratings do not account for injuries to key players, nor do they account for specific matchups in the games. The obvious disclaimer applies to this - although I have done the best possible, there is no guarantee as to the accuracy of predictions. One is the odds of a team winning a game against an opponent the other is the expected final score. From these ratings, you can determine two things. As indicated by the name, the predictive rating is the best of my ratings in its predictive power.