spi_matches

The raw data behind the stories "Club Soccer Predictions"
<a href="https://projects.fivethirtyeight.com/soccer-predictions/">https://projects.fivethirtyeight.com/soccer-predictions/</a> and "Global Club Soccer Rankings"
<a href="https://projects.fivethirtyeight.com/global-club-soccer-rankings/">https://projects.fivethirtyeight.com/global-club-soccer-rankings/</a>.

datasets

Datasets and code published by the data journalism website
'FiveThirtyEight' available at <https://github.com/fivethirtyeight/data>.
Note that while we received guidance from editors at 'FiveThirtyEight', this
package is not officially published by 'FiveThirtyEight'.

Albert Y Kim

fivethirtyeight

Data and Code Behind the Stories and Interactives at
'FiveThirtyEight'

Albert Y. Kim

Chester Ismay

Jennifer Chunn

Meredith Manley

Maggie Shea

Andrew Flowers

Jonathan Bouchet

G. Elliott Morris

Adam Spannbauer

Pradeep Adhokshaja

Olivia Barrows

Jojo Miller

Jayla Nakayama

spi_matches function

A data frame with 10182 rows representing soccer matches and 13 variables:<dl class="dl-horizontal">
 <dt>date</dt><dd>The date that the match took place.</dd>
 <dt>league_id</dt><dd>A numerical identifier of the league within which the match was played.</dd>
 <dt>team1</dt><dd>One team that participated in the match.</dd>
 <dt>team2</dt><dd>The other team that participated in the match.</dd>
 <dt>spi1</dt><dd>The SPI score of team1.</dd>
 <dt>spi2</dt><dd>The SPI score of team2.</dd>
 <dt>prob1</dt><dd>The probability that team1 would have won the match.</dd>
 <dt>prob2</dt><dd>The probability that team2 would have won the match.</dd>
 <dt>probtie</dt><dd>The probability that the match would have resulted in a tie.</dd>
 <dt>proj_score1</dt><dd>The predicted number of goals that team1 would have scored.</dd>
 <dt>proj_score2</dt><dd>The predicted number of goals that team2 would have scored.</dd>
 <dt>score1</dt><dd>The number of goals that team1 scored.</dd>
 <dt>score2</dt><dd>The number of goals that team2 scored.</dd>
 <dt>xg1</dt><dd></dd>
 <dt>xg2</dt><dd></dd>
 <dt>nsxg1</dt><dd></dd>
 <dt>nsxg2</dt><dd></dd>
 <dt>adj_score1</dt><dd></dd>
 <dt>adj_score2</dt><dd></dd>
</dl>

Format

The raw data behind the stories "Club Soccer Predictions"
<a href='https://projects.fivethirtyeight.com/soccer-predictions/'>https://projects.fivethirtyeight.com/soccer-predictions/</a> and "Global Club Soccer Rankings"
<a href='https://projects.fivethirtyeight.com/global-club-soccer-rankings/'>https://projects.fivethirtyeight.com/global-club-soccer-rankings/</a>.

Match-by-match SPI ratings and forecasts back to 2016 — spi_matches

A data frame with 10182 rows representing soccer matches and 13 variables:<dl class='dl-horizontal'>
 <dt>date</dt><dd>The date that the match took place.</dd>
 <dt>league_id</dt><dd>A numerical identifier of the league within which the match was played.</dd>
 <dt>team1</dt><dd>One team that participated in the match.</dd>
 <dt>team2</dt><dd>The other team that participated in the match.</dd>
 <dt>spi1</dt><dd>The SPI score of team1.</dd>
 <dt>spi2</dt><dd>The SPI score of team2.</dd>
 <dt>prob1</dt><dd>The probability that team1 would have won the match.</dd>
 <dt>prob2</dt><dd>The probability that team2 would have won the match.</dd>
 <dt>probtie</dt><dd>The probability that the match would have resulted in a tie.</dd>
 <dt>proj_score1</dt><dd>The predicted number of goals that team1 would have scored.</dd>
 <dt>proj_score2</dt><dd>The predicted number of goals that team2 would have scored.</dd>
 <dt>score1</dt><dd>The number of goals that team1 scored.</dd>
 <dt>score2</dt><dd>The number of goals that team2 scored.</dd>
 <dt>xg1</dt><dd></dd>
 <dt>xg2</dt><dd></dd>
 <dt>nsxg1</dt><dd></dd>
 <dt>nsxg2</dt><dd></dd>
 <dt>adj_score1</dt><dd></dd>
 <dt>adj_score2</dt><dd></dd>
</dl>

Match-by-match SPI ratings and forecasts back to 2016

spi_matches: Match-by-match SPI ratings and forecasts back to 2016

Description

Usage

Arguments

Format

See Also