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  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher-id">JDS</journal-id>
      <journal-title-group>
        <journal-title>Journal of Data Science</journal-title>
      </journal-title-group>
      <issn pub-type="epub">1680-743X</issn>
      <issn pub-type="ppub">1680-743X</issn>
      <publisher>
        <publisher-name>SOSRUC</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="publisher-id">120202</article-id>
      <article-id pub-id-type="doi">10.6339/JDS.201404_12(2).0002</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Research Article</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Predicting Match Outcomes in the English Premier League: Which Will Be the Final Rank?</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Louzada</surname>
            <given-names>Francisco</given-names>
          </name>
          <xref ref-type="aff" rid="j_JDS_aff_000"/>
        </contrib>
        <aff id="j_JDS_aff_000">Universidade de S˜ao Paulo</aff>
        <contrib contrib-type="author">
          <name>
            <surname>Suzuki</surname>
            <given-names>Adriano K.</given-names>
          </name>
          <xref ref-type="aff" rid="j_JDS_aff_001"/>
        </contrib>
        <aff id="j_JDS_aff_001">Universidade de S˜ao Paulo</aff>
        <contrib contrib-type="author">
          <name>
            <surname>Salasar</surname>
            <given-names>Luis E. B.</given-names>
          </name>
          <xref ref-type="aff" rid="j_JDS_aff_002"/>
        </contrib>
        <aff id="j_JDS_aff_002">Universidade Federal de S˜ao Carlos</aff>
      </contrib-group>
      <volume>12</volume>
      <issue>2</issue>
      <fpage>235</fpage>
      <lpage>254</lpage>
      <permissions>
        <ali:free_to_read xmlns:ali="http://www.niso.org/schemas/ali/1.0/"/>
      </permissions>
      <abstract>
        <p>Abstract: In any sport competition, there is a strong interest in knowing which team shall be the champion at the end of the championship. Besides this, the end result of a match, the chance of a team to be qualified for a specific tournament, the chance of being relegated, the best attack, the best defense, among others, are also subject of interest. In this paper we present a simple method with good predictive quality, easy implementation, low computational effort, which allows the calculation of all the interesting quantities above. Following Lee (1997), we estimate the average goals scored by each team by assuming that the number of goals scored by a team in a match follows a univariate Poisson distribution but we consider linear models that express the sum and the difference of goals scored in terms of five covariates: the goal average in a match, the home-team advantage, the team’s offensive power, the opponent team’s defensive power and a crisis indicator. The methodology is applied to the 2008-2009 English Premier League.</p>
      </abstract>
      <kwd-group>
        <label>Keywords</label>
        <kwd>Linear Model</kwd>
        <kwd>Premier Football League</kwd>
        <kwd>Simulation</kwd>
      </kwd-group>
    </article-meta>
  </front>
</article>
