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  2. Log5 - Wikipedia

    en.wikipedia.org/wiki/Log5

    The name Log5 is due to Bill James [1] but the method of using odds ratios in this way dates back much farther. This is in effect a logistic rating model and is therefore equivalent to the Bradley–Terry model used for paired comparisons , the Elo rating system used in chess and the Rasch model used in the analysis of categorical data.

  3. Fixed-odds betting - Wikipedia

    en.wikipedia.org/wiki/Fixed-odds_betting

    If the figure quoted is negative, the moneyline odds are quoting how much money must be wagered to win $100 (this is done if the odds are worse than even). Fractional odds of 1/4 would be quoted as −400 while fractional odds of 4/1 cannot be quoted as a negative figure. Even odds Even odds are quoted as +100 or −100.

  4. Pythagorean expectation - Wikipedia

    en.wikipedia.org/wiki/Pythagorean_expectation

    Pythagorean expectation is a sports analytics formula devised by Bill James to estimate the percentage of games a baseball team "should" have won based on the number of runs they scored and allowed. Comparing a team's actual and Pythagorean winning percentage can be used to make predictions and evaluate which teams are over-performing and under ...

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  6. NFL Week 10 preview and picks - AOL

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  7. Statistical association football predictions - Wikipedia

    en.wikipedia.org/wiki/Statistical_association...

    Statistical Football prediction is a method used in sports betting, to predict the outcome of football matches by means of statistical tools. The goal of statistical match prediction is to outperform the predictions of bookmakers [citation needed] [dubious – discuss], who use them to set odds on the outcome of football matches.

  8. Odds - Wikipedia

    en.wikipedia.org/wiki/Odds

    Thus if expressed as a fraction with a numerator of 1, probability and odds differ by exactly 1 in the denominator: a probability of 1 in 100 (1/100 = 1%) is the same as odds of 1 to 99 (1/99 = 0.0101... = 0. 01), while odds of 1 to 100 (1/100 = 0.01) is the same as a probability of 1 in 101 (1/101 = 0.00990099... = 0. 0099). This is a minor ...

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