At "once football" you can find many statistical informations about particular match or more matches for players and teams. This is an app for ipad and iphone. If moderators allows i'll put some pictures to see what is offered(many informations in few seconds)
No. What I was saying was: if there's a strong correlation between team salary and win/loss/tie record, and clubs 1 to 20 are all as bad at identifying soccer talent, it can not be concluded that "despite the lack of stats" any of them is actually "fairly adept" at "identifying the best soccer talent". If a select group of people all suck at something to the same degree, it doesn't mean they're actually good at what they suck at. Yes, one of the many interesting questions one could ask. I wish we had the data to answer questions like these.
Not quite what you may be after by I'm happy to try and add something (apologies if someone else has already added this or something like this from elsewhere): Data based on the English Premiership between 2003 and 2011 - data taken from here http://www.football-data.co.uk/ - can't remember specifically where they sourced it from originally: Home Team Goals Scored 0.152 * Home Team Shots On Target (of any kind - e.g. poor or good shot on target from any distance) + -0.244 * Home Team Yellow Cards + 0.214 * Opponent Team Yellow Cards (so the yellow cards effectively cancel each other out) + 0.072 * Home Team Corners All P Values are less than 0.02 R Squared is 0.9757 (I don't like the factors but I will take it short term) Standard Error = 8.112 You'd have to Monte Carlo it as you go along or something similar but it's a start Home Team Goals Conceded 0.131 * Opponent Team Shots (not Opponents Shots on Target) + -0.041 * Home Team Corners All P Values are less than 0.0004 R Squared is 0.971 (again I don't particularly like the factors but anyhow....) Standard Error = 8.751
My slight alternative to one of the formulas above (again I don't particularly like it, as you have to know the number of goals going forward, but maybe you can more closely correlate this to players within a club?) - it also I suppose allows you to project things from a point within the season based on current data making it relevant to current form? All data as per the above and the regression is done again on the 2003 through 2011 English Premiership Seasons: Factor trying to be determined: Home Team Goals Scored Two factors used: Home Team Shots on Target (as above of any kind) Strike% (percentage of successful shots on target - e.g. those that resulted in a goal - number expressed as a full percentage e.g. 26% not 0.26) 0.218*Shots on Target +228.567*Strike % +-50.004 (Intercept) All P Values are statistically significant at less than 0.000000001 R Squared is 0.982 Standard Error = 1.845 You could get a better R Square (0.986, Standard Error 1.79-ish) from using shooting % (shots on target from total shots), but it had a p value of .30 so I dropped it out.
Hey everyone, I've been reading a lot of the posts on this thread, and am fascinated by all of the good ideas that everybody has. I'm currently working on a project that predicts the outcomes of games in the big 5 European leagues http://www.bloombergsports.com/football/, and I think it pertains to a lot of what you all are talking about. This thread is great keep it going!
I would be interested to see more how individual statistics work into equation, to isolate a bit more the performances of each player. Such as stolen balls, passes intercepted, and % of passes completed (which I think it's a great indicator of player performance)
Good book review here ... http://www.nytimes.com/2012/10/24/b...oks&_r=0&gwh=7832E66ADD4FDBF228E8A9D4EF294BE0 The Signal and the Noise - Nate Silver
In the soccer world, Silver is known for developing espn's soccer power index. http://soccernet.espn.go.com/world-...8/ce/us/guide-espn-spi-ratings?cc=5901&ver=us http://soccernet.espn.go.com/spi/rankings?cc=5901
I have a metod e predicting league matches that usually works quite. I could try posting some predictions here.
Please do! Has everyone/anyone here checked out http://www.whoscored.com/ ? The sub-heading on the homepage says "Revolutionizing Football Statistics." Opinions, please.
Off topic, but Silver correctly predicted all 50 states in the 2012 US Presidential race (after going 49/50 four years ago). Obviously, many states are easy to predict, but not all of them. Also, I don't know how early he made his predictions, whether any needed later revision, etc.
Great site - thanks! Really fascinating, if expected, how Barca players swept the top 10, and 11 of the top 12 in overall passing accuracy. Lots of good data on that site.
Looking at this site... it saddens me that Fagner left my Vasco da Gama... he's right now one of the top defenders in the Bundesliga, and defending is his weakness!!
I was seriously thinking that something on those lines would be possible thanks to the internet. You crowd-source the data collection. Jon volunteers to count how many times player x gets the ball, Steve counts for player y etc. You start small and just track a few statistics for a few players and see if there are patterns or correlations to winning. With more volunteers, you can track more metrics, for more players. Everyone posts their data online.
There was a guy who did this, Kurt something? Kurt or Kirk and his last name started with a K? He had a bunch of people take like 10 minute chunks of (I think) USA World Cup games (definitely USA games) and do all that. I did it and it was so painstaking and such a pain in the ass that I vowed never to do it again. Baseball's Project Scoresheet was one thing (and now you can get all that data anyway). This was just too labor-intensive. And things like Opta do it all anyway (not that we ever see all that data).
As you mentioned, Opta will charge you handsomely for access to the data. Re: Your baseball experience, perhaps that was because you had too many metrics to track. Counting how long it takes a single player to pass on average or some other metric, perhaps even for just one half, seems more manageable?
I was wondering if there were any thoughts on the "chances created" and assists statistics out there. It's kind of hit me that these are frustrating stats to hear people reference in conversation. They same like a rough equivalent of RBI, old fielding percentage or even batting average in baseball. Are there statistics that break down these areas a bit further? Such as, good assists/chance creation or even just worthwhile chance creation? It seems like just knowing the last person to pass the ball to a goal scorer or shooter isn't the best way to actually determine who helped in creating a chance or a goal. Thanks
The MLS keeps up with key passes and assists but doesn't comply them anywhere. You have to search through all the chalkboards, which is pretty absurd, I know.
From a brief Q & A with Sunil Gulati ... http://www.themorningsidepost.com/2013/11/13/soccernomics-a-conversation-with-sunil-gulati/
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It seems as though football has more abstract statistics required to analyze the effectiveness of individuals compared to other sports. Also it seems as though it would be a lot tougher to compare the combined effectiveness of a group of individuals. Despite this hurdles I have programmed my own software that can simulate games with any possible group of ten players and a goalie. If you want to see the results of my simulations or learn more about the software go www.soccersimulator.weebly.com