Posts filed under Sports statistics (1776)

Team Ratings for Round 1

Sorry about the delay in posting these predictions. I have never been really happy with my selection of parameters, so decided to do a massive grid search yesterday which ended up taking about 16 hours. That means this year I have shiny new parameter values for my predictions. As ever, remember the adage, “past performance is not necessarily indicative of future behaviour”.

The basic method is described on my Department home page.

Here are the team ratings prior to this week’s games, along with the ratings at the start of the season.

Predictions for Round 1

Here are the predictions for Round 1. The prediction is my estimated expected points difference with a positive margin being a win to the home team, and a negative margin a win to the away team.

From James Lee Gilbert on Twitter, a pie chart from WXII News (Winston-Salem, North Carolina)

This is from a (respectable, if pointless) poll conducted in North Carolina. As you can clearly see, half of the state favours the local team. Or, as you can clearly see from the numbers, one-third of the state does.

If you’re going to use a pie chart (which you usually shouldn’t), remember that the ‘slices of pie’ metaphor is the whole point of the design. If the slices only add up to 70%, you need to either add the “Other”/”Don’t Know”/”Refused” category, or choose a different graph.

If your graph makes it easy to confuse 1/3 and 1/2, it’s not doing its job.

From the twitter of the Financial Times, “Interactive: who is the better goalscorer, Messi or Ronaldo?”

I assume on the FT site this actually is interactive, but since they have the world’s most effective paywall, I can’t really tell.

The distortion makes the bar graph harder to read, but it doesn’t matter much since the data are all there as numbers: the graph doesn’t play any important role in conveying the information. What’s strange is that the bent graph doesn’t really resemble any feature of a football pitch, which I  would have thought would be the point of distorting it.

The question of who has the highest-scoring season is fairly easy to read off, but the question of “who is the better goalscorer” is a bit more difficult. Based on the data here, you’d have to say it was too close to call, but presumably there’s other information that goes into putting Messi at the top of the ‘transfer value’ list at the site where the FT got the data.

(via @economissive)

Team Ratings for the Currie Cup Final

The basic method is described on my Department home page. I have made some changes to the methodology this year, including shrinking the ratings between seasons.

Here are the team ratings prior to this week’s games, along with the ratings at the start of the season.

Performance So Far

So far there have been 42 matches played, 31 of which were correctly predicted, a success rate of 73.8%.

Here are the predictions for last week’s games.

Predictions for the Currie Cup Final

Here are the predictions for the Currie Cup Final. The prediction is my estimated expected points difference with a positive margin being a win to the home team, and a negative margin a win to the away team.

Team Ratings for the ITM Cup Finals

Here are the team ratings prior to the ITM Cup Finals, along with the ratings at the start of the season. I have created a brief description of the method I use for predicting rugby games. Go to my Department home page to see this.

Here are the team ratings prior to this week’s games, along with the ratings at the start of the season.

Performance So Far

So far there have been 74 matches played, 48 of which were correctly predicted, a success rate of 64.9%.

Here are the predictions for last week’s games.

Predictions for the ITM Cup Finals

Here are the predictions for the ITM Cup Finals. The prediction is my estimated expected points difference with a positive margin being a win to the home team, and a negative margin a win to the away team.

Team Ratings for the SemiFinals

The basic method is described on my Department home page. I have made some changes to the methodology this year, including shrinking the ratings between seasons.

Here are the team ratings prior to this week’s games, along with the ratings at the start of the season.

Performance So Far

So far there have been 40 matches played, 29 of which were correctly predicted, a success rate of 72.5%.

Here are the predictions for last week’s games.

Predictions for the SemiFinals

Here are the predictions for the SemiFinals. The prediction is my estimated expected points difference with a positive margin being a win to the home team, and a negative margin a win to the away team

Team Ratings for the ITM Cup Finals

Here are the team ratings prior to the ITM Cup Finals, along with the ratings at the start of the season. I have created a brief description of the method I use for predicting rugby games. Go to my Department home page to see this.

Here are the team ratings prior to this week’s games, along with the ratings at the start of the season.

Performance So Far

So far there have been 70 matches played, 44 of which were correctly predicted, a success rate of 62.9%.

Here are the predictions for last week’s games.

Predictions for the ITM Cup Finals

Here are the predictions for the ITM Cup Finals. The prediction is my estimated expected points difference with a positive margin being a win to the home team, and a negative margin a win to the away team.

Team Ratings for Round 10

The basic method is described on my Department home page. I have made some changes to the methodology this year, including shrinking the ratings between seasons.

Here are the team ratings prior to this week’s games, along with the ratings at the start of the season.

Performance So Far

So far there have been 36 matches played, 27 of which were correctly predicted, a success rate of 75%.

Here are the predictions for last week’s games.

Predictions for Round 10

Here are the predictions for Round 10. The prediction is my estimated expected points difference with a positive margin being a win to the home team, and a negative margin a win to the away team.

Team Ratings for Round 9

Here are the team ratings prior to Round 9, along with the ratings at the start of the season. I have created a brief description of the method I use for predicting rugby games. Go to my Department home page to see this.

Here are the team ratings prior to this week’s games, along with the ratings at the start of the season.

Performance So Far

So far there have been 62 matches played, 39 of which were correctly predicted, a success rate of 62.9%.

Here are the predictions for last week’s games.

Predictions for Round 9

Here are the predictions for Round 9. The prediction is my estimated expected points difference with a positive margin being a win to the home team, and a negative margin a win to the away team.

Team Ratings for the Grand Final

The basic method is described on my Department home page. I have made some changes to the methodology this year, including shrinking the ratings between seasons.

Here are the team ratings prior to this week’s games, along with the ratings at the start of the season.

Performance So Far

So far there have been 200 matches played, 117 of which were correctly predicted, a success rate of 58.5%.

Here are the predictions for last week’s games.

Predictions for the Grand Final

Here are the predictions for the Grand Final. The prediction is my estimated expected points difference with a positive margin being a win to the home team, and a negative margin a win to the away team.