A Beautiful Numbers Game

On Forbes - Premier League Table Predictions (Post Match Day 11)

2012-11-15T05:54:00.001-08:00

The Premier League has now completed 11 matches, which means they're slightly over a quarter of the way through the season. I took a look at each team's odds of finishing in each table position, and wrote a post at Forbes based upon my findings. Enjoy!

Sounder At Heart - Forget The Numbers: A View On The MLS Conference Semifinals

2012-11-15T05:51:00.002-08:00

Two weeks ago I was asked to write a piece for Sounder at Heart on the Sounder's chances of making it to the MLS Cup and my overall thoughts on the team. Previous to the post I had debuted my attempt at a predictive model that attempted to forecast who would make it to the end of the 2012 MLS Cup playoffs, which has been pretty much wrong this playoff cycle. In that piece I explained why I felt the Sounders were a long shot to make and win the Cup, and yet why I very rarely listen to the numbers when I enjoy watching the Sounders. Read the post if you want to see me take some very fair lumps and perhaps understand my love for the sport beyond the numbers.

On Forbes - MLS Knockout Round and MLS Cup Predictions

2012-10-31T13:57:00.001-07:00

My latest post for Forbes uses my MLS playoff model to predict who will win the knockout round matches this week, as well as the likelihood of each team winning the MLS Cup. Everyone knows that San Jose is the favorite to win it all, but what's their actual likelihood of winning the Cup? Who else is likely to win it, and what is the range of likelihoods each team has at winning the Cup? You will have to click on the link above to find out.

Posted with Blogsy

On Forbes - What is Champions League Worth To Arsenal?

2012-10-27T19:24:00.000-07:00

Many people laughed when Arsene Wenger declared at last Thursday's AGM that "fourth place was like a trophy" for the Gunners. In this post I explain why Arsenal can only compete for third or fourth place given their player expenditures, and the impact not qualifying for the Champions League would have on the club.

Appearance on the Soccer Perspectives Podcast

2012-10-27T19:22:00.002-07:00

This week I appeared on the Soccer Perspectives podcast to discuss my recent posts on how the MLS playoff format penalizes teams who participate in extra-league competitions like the CONCACAF Champions League and US Open Cup. My segment picks up around the 3 minute mark, and involves a 20 minute conversation with the podcast's host.

On Forbes - How the Two-Legged Conference Final Will Impact MLS Cup

2012-10-22T05:57:00.000-07:00

My latest post for Forbes examines how the 2012 changes to the MLS playoffs conference finals format will impact the likelihood of certain teams winning an MLS Cup. It uses data from the last nine MLS post season tournaments as input to a 10,000 run Monte Carlo simulation. The results quantify just how much of a penalty teams that play additional competitive matches via US Open Cup and CONCACAF Champions League will pay in the revised playoff format.

On Forbes - A Statistical Recap of CONCACAF World Cup Qualifying, Round 3

2012-10-18T06:50:00.003-07:00

Click here to see my latest for Forbes where I explain how much the US underperformed, how much Mexico, Costa Rica, and Honduras over performed, and make a few 4th round projections.

Nos Audietis Soccer Statistics Roundtable

2012-10-15T21:42:00.000-07:00

This past Sunday I participated in a soccer statistics roundtable on the Nos Audietis podcast. It was a great discussion with some of the top practitioners and writers of soccer statistics in the United States, and something I hope to be able to do again some day. Have a listen if you're curious as to my views on the general topic, who I see as overperformers, or generally just want to hear the voice behind all of those posts you may (or may not) be reading.

On Forbes: How the MLS Playoff Format Punishes Ambitious Teams

2012-10-15T05:59:00.001-07:00

My latest for Forbes looks at how the current MLS playoff format of using a two-legged aggregate goal format penalizes the teams within the league who look to build both their own and the league's stature by taking on the challenge of ancillary competitions like the US Open Cup and CONCACAF Champions League.

On Forbes: We’re Entering A Golden Age of Long Form Soccer Writing

2012-10-15T05:35:00.001-07:00

In the last month alone there have been three different soccer quarterlies that were either launched or published their latest issue. Learn how their publication suggests we're entering a golden age of long form soccer writing.

On Forbes: Premier League Leaders & Laggards

2012-10-15T05:35:00.000-07:00

Another month of play has passed in the English Premier League, with a total of six games being played by the end of September. One of my latest posts for Forbes looks at the emerging story lines. Everyone knows Chelsea is doing well, but who else is overachieving? Conversely, who is underachieving besides those who are clearly at the bottom of the table? Click on the link above to find out.

On Forbes: More Than A Data Warehouse - An Interview With Infostrada Sports Group’s Simon Gleave

2012-10-10T20:35:00.000-07:00

I recently sat down with Infostrada's Simon Gleave to discuss that group's coverage of soccer, how they deploy their statistics via multiple media platforms, and how their involvement in many different sports beyond soccer provides a value proposition not found in many other statistics groups. Read my interview here.

On Forbes: What Soccer Can Learn From the NFL Referee Lockout

2012-10-10T20:31:00.003-07:00

A few weeks ago it was my Seattle Seahawks that demonstrated the absurdity of the use of replacement referees within the NFL. While some might have been laughing at the league, I suggested at the time that soccer can learn a thing or two from this experience. With high definition television and access to video on the internet there is no excuse for soccer to not look at modernizing its officiating. However, the sport and its leagues must be careful in the use of technology to avoid become more like a courtroom instead of a soccer pitch.

On Forbes: Are Happier Days Here Again for Arsenal?

2012-10-10T07:05:00.001-07:00

It's time to catch my personal blog up on a few of my posts over at Forbes. This first one examines the change in attitude at Arsenal amongst its players and fans. After what seemed to be a tought year of two summers and a slog of a season, things are starting to look up around The Emirates. There were no rushed purchases at the end of the last transfer window, the RVP deal seems to have been handled as best it could, the club now seems to finally be able to move on from the expectations that were attached to the likes of van Persie and Cesc Fabregas, and the new additions seem to be producing goals and wins for the team. There may be no better embodiement of this new optimism than the perpetually smiling Santi Cazorla. Have a read at the link above to find out why Arsenal may have finally turned a corner towards happier times.

Posted with Blogsy

On Forbes: The Continuing Challenges at Liverpool Football Club

2012-09-18T07:34:00.000-07:00

My latest post for Forbes examines the current struggles at Liverpool in a historical context. It's been a rough start to the new season for the Reds, but their new manager and only two-year-old ownership group needs to be given time to progressively rebuild a club that was on the brink of administration only two short years ago. Click on the link above to ready my justification for asking for such patience.

On Forbes - EPL Predictions and Reflections Through Week 2

2012-09-03T17:12:00.003-07:00

Prior to a week long vacation in August I made a projection as to the EPL 2012/13 table based upon Transfer Price Index Sq£ values. You may be surprised to see how the predictions compare to two other predictions from ESPN.com's writers as well as the Euro Club Index. I then followed up that post last week with a review of how the results of the first two weeks compared to the clubs' expected performance. Everyone knows that Spurs and Liverpool, amongst others, are struggling, but by how much? The second post attempts to answer that question.

On Forbes - Manchester City's Performance Analysis Department

2012-08-26T14:43:00.002-07:00

Prior to last week's vacation I cranked out a number of posts at Forbes on Manchester City's Performance Analysis department. The first two were a transcription of an interview with the club's head of performance analysis, Gavin Fleig. The nearly 6,000 words he and I exchanged provided a good bit of information on how the club uses analytics from the youngest youth sides all the way up to the senior first team. The third post outlined how the recently launched MCFC Analytics site is attempting to jump start the public sphere soccer analytics movement by making a good bit of Opta data freely available to the public that was previously available only via a fee. Have a look at all three posts if you're interested in understanding how last year's Premier League champions use analytics to stay on top and give something back to the soccer analytics movement at the same time.

Measuring EPL Player Performance and Value

2012-08-14T05:36:00.001-07:00

The following is a guest post by Dave Laidig¹.

Measuring 2011/12 EPL Player Performance

Soccer is known as the beautiful game, an art form expressed on grass fields instead of canvas. But the results-oriented nature of elite competition removes artistic illusions. Performance matters when literal fortunes are on the line. Teams invest a great amount of resources to identify and nurture players with the greatest ability to perform. They and their fans want to know: who is going to do the most to help the team win?

Historically, this assessment is made by wise old managers that are experienced in the game and are often players in their former lives, and by the legions of supporters who never fail to share their opinion. In the modern game assessments have begun to be quantified, allowing for more objective descriptions of player performance. This analysis tests whether a publically available performance statistic actually relates to winning, and considers the possible uses of that information.

The key component of this analysis is the performance measure². The Castrol Edge Rating, published by Opta, which assigns a score to players in all five of the major European soccer leagues was selected for this analysis³. In addition to the benefit of being publically accessible, this score is designed to reflect the individual’s overall contribution to winning and identify which players had the best season among the top five European leagues.

The Castrol Rating metric is based upon observations of game data in the 2011/12 EPL season and Opta’s application of an internal calculation incorporating many types of game events and relating them to winning games. While the exact formula for creating the statistic is the proprietary information of Opta, the important thing to know is that the number is intended to represent overall performance (and not just one aspect of the game like goals scored, or tackles, etc.). It should allow for meaningful comparisons between different players and positions.

A review of the Castrol Index scores for 2011/12 shows us that Arsenal forward Robert van Persie earned the highest rating for his work last season, with a rating of 962⁴. If the acclaim of sportswriters is indicative, van Persie deserved the top spot in the EPL. Scanning the top spots for each position, we see very recognizable players that are not likely to surprise most fans.

The top spots in the Castrol rankings provide few surprises, but the important decisions in soccer are usually more difficult than evaluating whether van Persie is a good player. Further on down the line players have a multitude of strengths and weaknesses, varying playing time, and may get lost in the crowd. Once past the top stars, assessing performance becomes more challenging.

Weaknesses of the Castrol Rating

Thus, we look to the performance measure for assistance in evaluating performance for the entire population of EPL players. However, our chosen measure has a weakness in describing performance for part-time players. Specifically, a player’s minutes are highly correlated with his Castrol Rating score (a correlation of 0.88). With such a strong correlation, the influence of playing time may drown out actual performance. Opta, the creators of the Castrol Index, admit that the scores of those players with insufficient playing time are punished, with the downward scoring starting with players at about 60% of the overall minutes available⁵.

Using the 60% standard as a guide, the relationship between playing time and performance scores above and below the 2070 minute threshold is studied (equal to 23 games of the 38 possible in the EPL season, or about 60% of the available minutes). For the 164 players with more than 2070 EPL minutes (the “2070+ group”), there is no significant correlation (a correlation of 0.019) between minutes and Castrol score. For the group below 2070 minutes (the “< 2070” group), the relationship remains strong (correlation of 0.89). Thus, it seems there is a threshold of playing time required before one can get an unbiased evaluation of performance.

Adjusted Index Scores

Consequently, the < 2070 group’s scores are adjusted so that an unbiased comparison can be made between them and the unbiased group of 2070+ minutes. An expected value for the < 2070 group (with a single regression equation) was created to determine the expected score for a given amount of playing time. Once whether or not a player’s Castrol Index score exceeded expectations could be calculated the question became by how much.

To evaluate this, the entire EPL population was divided into roughly a dozen equal groups, and the range of scores was compared around the average for each group. The range around the mean for our unbiased groups was set as the goal and the < 2070 groups were adjusted to have similar variability. Finally, the player’s relative performance in relation to their playing time was taken into account and they were put in the spot of a player with 2070 minutes – the cutoff for unbiased evaluation by the Castrol Index. In short, the goal of the adjustment process was to allow direct comparisons between the < 2070 group and the 2070+ group.

All in all, the adjusted scores are not related to minutes with a correlation of .019; which compares favorably to the correlation of 0.88 for minutes and the Castrol Index ratings. Further, the range of players’ scores is reduced since playing time no longer artificially discriminates amongst performance levels. Finally and most notably, the adjustment process unsettles some of the player rankings and provides a new perspective on performance.

When one turns to the individual players, the adjusted scores seem to better reflect conventional opinion as well. On its face, it is tough to argue that Cissé, Drogba, or Balotelli were not difference makers on the pitch. And with some players moving up due to the adjustment process, some players see their rankings fall in comparison. For example, Newcastle forward Demba Ba falls from 10th in the Castrol rankings to the 21st ranked forward under the Adjusted Index. Theo Walcott moves from the 21st Midfielder to 40th. Some may debate the movements of individual players, but the aggregate movement of the players in each position seems to square better with performance adjusted for playing time.

One should keep in mind that a good score on the index, or the adjusted index, does not eliminate normal variability in performance. One good year does not guarantee a standout performance the next. A low rating may have an explanation that soccer fans can readily identify with such as an injury, or playing out of position, or trouble acclimating to a new team. But a good performance is still a good performance, and awareness of a good performance, even if only for a limited period of time, is useful.

Utility of the Adjusted Index

Using the adjusted formula, one can then locate players that have put in an objectively superior performance, but may not be as recognized due to a relative lack of playing time. For example, even with limited time on the pitch, the time spent by Ryan Giggs was impressive. With the adjustments, his performance score went from 570 to 730 under the Adjusted Index. The position rank goes from 62nd to 15th, a dramatic increase. And while the professionals will still need to predict how a player would fit in, and the likelihood for better or decreased performance; the ability to quickly highlight players that deserve extra attention can save time and increase the scout’s success rate. Ryan Giggs’ age may prevent him from going a full 90 minutes in each league match, but the data as re-envisioned does suggest that Manchester United should look to utilize him as much as physically possible.

Some may use the scores as an independent assessment of roles within a team. For example, Dimitar Berbatov has publicly expressed dissatisfaction with his time at Manchester United. His Castrol score is 241, good for 328th overall in the EPL and 58th among EPL Forwards. He has reason to argue that his poor showing is due to lack of playing time. In contrast, his Adjusted Index score is 687, which is 81st in the EPL and 22nd among EPL Forwards. In general, it is a decent showing for the amount time on the field he was granted. Perhaps the bad news for Berbatov is that he is still fifth among Manchester United Forwards, behind the adjusted scores for Rooney (837), Welbeck (804), Young (796) and Chicharito (708). Thus, we are not surprised that his pleas for more time have not been answered.

The Winning Formula in EPL

In this section, the objective performance data – i.e., the Castrol Index and the Adjusted Scores – is used to analyze the relative contribution of the different positions towards team success, and to model the value of players. Midfielders and Defenders have higher average Castrol Index scores, an initial suggestion that these positions might have more value for winning.

Considering forwards are the highest paid, investing in defenders may be a more productive use of resources. However, we have already discussed the Castrol Index scores relationship to playing time. And typical playing time differs among the positions because managers are more likely to pull forwards mid-game than their back line. Indeed, forwards average about 400 minutes less per season than defenders. With the Adjusted scores, which are unrelated to playing time, we see that forwards are higher on average, a result in direct contrast to the Castrol Index averages.

Position Ratings and Relationship

Using both the Castrol Index and the adjusted scores for EPL players, I set about replicating the Leinwand- Anderson analysis of MLS data⁶. Their analysis created a regression equation using a team’s average Castrol Index rating for each position and the team’s league points (i.e., a mathematical model roughly summarized as: a Constant + Fwd Rating + Mid Rating + Def Rating + GK Rating = Expected League Points). Replicating the analysis using EPL data resulted in an R2 value of .835, indicating the average position ratings for a team can explain a healthy 83.5% of the variability in league points. But for the individual elements of the equation, only the midfielder and goalkeeper coefficients are statistically significant in this model. Thus, strictly speaking, we would be unable to justify using the model for forwards and defenders.

Using the adjusted ratings instead, the R2 value was 0.857; which adds another 2% over the model using the original Castrol Index ratings. In this version, though, only goalkeepers were statistically significant. Consequently, the adjusted ratings were a slightly better predictor of team performance, but of less value for individual positions.

Regression Weighted by Playing Time

The next revision of the model sought to address a unique soccer feature of the regression equation. The Leinwand-Anderson equation treats Forwards, Midfielders and Defenders as equal units. But it is known that there are uneven numbers at each position depending on team formation and game situation. Thus, the equation was modified to account for the relative time contribution of each position. To do this, average position score was used from the first analysis, and weighted by that position’s contribution to the overall team minutes. For a mathematical illustration, the Tottenham forwards may have an adjusted index average of 738, and contribute 12% of the team’s minutes. The revised model would then report 0.12 * 738 or 88.56 as a value of that position's point contribution to the team.

By considering playing time with each position, the multiple regression equation for the position's adjusted point contribution was significant for Forwards, Midfielders, and Defenders, with a non-significant p-value of 0.13 for Goalkeepers. Thus, this model permits analysis of all field positions. In this model, forwards have a larger regression coefficient than midfielders, with both larger than defenders. This would support the notion that forwards contribute more to wins than other positions. Further, the R2 value was 0.887; which, by explaining 88.7% of the variance in league minutes, represents the model with the greatest explanatory power (compared to 0.835 for the Leinwand-Anderson model and 0.857 for the Leinwand-Anderson using adjusted index ratings).

Considering which equations are the best fit for the 2011/12 EPL data; the trends are that weighting the ratings with minutes is better than a straight position average, and that the adjusted scores are better than the Castrol Index. Of these options, the weighted-adjusted model is the best fit, which mirrors the conclusion reached for the MLS data⁷.

Applying the Model to Individual Examples

Although this mathematical model shows each position’s contribution to league points, the model is clumsy for team use. Contracts are determined player by player, and not by position group. Thus, in order to make the equation useful, the regression equation coefficients need to reflect the value of one player. Consequently, it was determined forwards accounted for 16.4% of all league minutes, midfielders 38.9%, defenders, 35.4% and goalkeepers 9.2%. With eleven players, it was calculated how many "players" were assigned to a particular position group. Using forwards for example, this position had 1.8 players' worth of league minutes applied to this position's regression coefficient.

As a result, the estimated impact of inserting a field player with a higher adjusted index score on the team's league points can be calculated. Recalling our model, the forward position group had the highest contribution to league points being about 1.5 times the contribution of midfielders. But when comparing a single player to a single player, the value of a forward was three times greater than that of a midfielder: due in large part to the midfielder group consisting of more players than forwards.

Which Positions Are Most Important in the EPL

However, value of a player is not only defined by one’s contribution to wins, but also in the scarcity of that talent. If there were dozens of van Persie clones seeking transfers to EPL teams, the teams would rightly concentrate on other areas to improve their team (after picking up one of the van Persie clones on the cheap). To illustrate, the adjusted index scores was revisited to provide some examples for the value of each position by considering the benefit of an identical player upgrade for each position. Specifically, what is the value of replacing a median position player with the 80th percentile player for one full season at that position?

Upgrading from a median forward to an 80th percentile forward (represented by F. Torres) would expect to yield an additional 18.68 league points. Upgrading from a median midfielder to an 80th percentile midfielder (S. Pienaar) would expect to yield an additional 4.21 points. And upgrading from a median to an 80th percentile defender (L. Baines) would expect to yield an additional 3.03 points. While the hypothetical 50th percentile to 80th percentile upgrade ranges between 70 to 100 points, the equation indicates that this hypothetical upgrade would have a much larger impact if it was a forward upgrade.

Team-Specific Use of the Model

For another use of the model, a team may weigh the benefits of a transfer on league results by applying the difference between a desired player and the current incumbent. For example, Clint Dempsey is listed by Opta as a midfielder and has an adjusted score of 742. Dempsey played nearly every minute of the EPL season for Fulham in 2011/12. If Dempsey, and his minutes, replaced an average Liverpool Mid (633), then Liverpool would expect an additional 6.1 league points under the model. In a person for person switch, Dempsey in place of C. Adams (and at Adams lower level of minutes) would lead to an expected additional 3.33 points. Still a benefit, but a smaller effect due to Adams higher performance level (650) and the lessened impact due to an assumption of lesser playing time.

If Arsenal considered acquiring Dempsey, the same process can be applied using team-specific data. Dempsey replacing an Arsenal average Midfielder, and with Dempsey’s 2011 minutes, would lead to an expectation for an additional 2.63 points for Arsenal. Should Dempsey replace Theo Walcott and his minutes, Arsenal would expect an additional 3.33 points. Consequently, the value of Dempsey varies depending on the team making the assessment and the intended use. The model would explain some of the varying assessments of value, and is flexible enough to make some adjustments for playing time and role.

And in a pinch, a team’s evaluation staff can insert an “expected” performance level for an unknown (i.e., one can say the target can fulfill a “John Terry” role, thus insert Terry’s adjusted value of 720 into the equation). Alternatively, again relying on technical expertise, one can use a high and low benchmark provided by the staff to create a range of expected performance for a new player (e.g., the staff may conclude the target’s ceiling may be Dempsey (742) and likely no worse than Scholes (686)). Applying the predicted range can provide feedback on whether the transfer costs are worth the expected performance gain and risk. Finally, it’s worth pointing out that although the model relies on the Castrol Index as the basic metric, this analytical process can be repeated with any available continuous variable that a team believes predicts team results.

Limitations of the Data, and Next Steps

This data is based on one season of EPL data. And while the process yields similar results to the MLS analysis, the fact remains that any decisions for EPL players is based on 20 observations (the EPL teams of 2011/12) summarizing the play of over 500 players. Even with strong relationships, the addition of future data will only improve the model. For example, with one season’s worth of data, the variability of a player’s performance is not captured. Two players may have the same average performance rating for the season – but teams may value a player with large highs and incredible lows differently than a player that puts in the same performance game after game. This model does not account for that variation. Further, with the adjusted scores, the relationship to playing time is minimized. However, a player that can remain at a high level over a whole season should rightly be more desirable than a player with a solid run over five or six games. The published Castrol Index attempts to take playing time into consideration, but this model does not for the reasons given above. Thus, while there are benefits to this analysis, one would still need to make their own subjective adjustment for playing time, based on their experience and judgment.

With the caveats aside, an imperfect model does not make the model useless. This is an attempt to determine the value of players based on relationships found in the data. If one uses the adjusted index scores as a quick screening tool, the obligation to follow-up and evaluate the player remains. The screening tool is not meant to replace good scouting, only to efficiently assign resources so that a scout’s hit rate might increase.

Further, when one considers whether a potential replacement player would contribute to winning, the cost of that player (which is not part of the EPL model) needs to be considered against team resources and roster-wide performance consequences. Obviously money matters, but the model creates an analytical framework – based on data – to decide whether a club are getting sufficient value for their money (in additional points). It provides a unique independent data point worthy of consideration.

The hope is that this analysis adds to the debate, and supports the incorporation of analytical processes in team decision-making.

Footnotes:

¹Dave Laidig is a corporate attorney responsible reviewing and negotiating contracts. Prior to attending law school, he indulged his quantitative predisposition by earning a Masters in Psychology, focusing on research methods, statistics, and measuring human factors. He resides in Minnesota and is a season ticket holder for his Minnesota Stars FC.

²In addition to the performance metric, the calculations also require basic player information such as player name, team name, position and minutes played. This information is widely reported by many media outlets. For this analysis, however, I used the player info associated with the Castrol scores and the playing time data available by subscription from the EPL Index. See http://www.eplindex.com/.

³See http://www.castrolfootball.com/

⁴The Castrol Rating also includes European competition, which is weighted slightly more than league games. The Castrol Index is meant to determine which European players had the best year, and the authors of the index determined that performance in European competition should be emphasized, which is a reasonable determination for that purpose. Here, we offer an analysis of league results, which renders the Castrol Index a less-than-perfect performance measure for teams with extended European campaigns. However, imperfect data may still be useful, and the analysis continues.

⁵See the FAQ section for the Castrol Index.

⁶Available at http://www.soccerbythenumbers.com. This calculation relies heavily on the work of Benjamin Leinwand and Chris Anderson as I attempted to replicate their work, and then extend to new areas. I appreciate those willing to share results with the public, allowing for debate to improve and continue.

⁷See my earlier analysis of MLS data, “Objective Player Analysis, Part 2”, at http://footiebusiness.com/2012/04/10/objective-player-analysis-part-ii/

On Forbes: Identifying the Over & Under Performers in the Men's Olympic Soccer Tournament

2012-08-13T12:01:00.001-07:00

My latest post at Forbes quantifies which national teams were the biggest over and under performers at the recently completed Olympic men's soccer tournament. There are the standouts during group play (Senegal, Brazil, Honduras), an evaluation of whether or not Team Great Britain actually realized a home pitch advantage, and a breakdown of how the Mexican squad beat the Brazilians.

Posted with Blogsy

On Forbes - E Pluribus Sounders

2012-08-06T05:59:00.000-07:00

Over at my Forbes blog I have spent the last three weekdays rolling out a three-part series explaining why Seattle Sounders FC have achieved record US attendance figures. The first post explains the unique history of soccer in the Seattle area, and how the NASL Sounders built a special connection between the city and the Sounders brand. The second post tells the story of how semiprofessional players kept the sport alive in the city without the draw of top flight soccer, and how the Sounders FC organization laid the groundwork for success before the team played its first game. The third-and-final post provides an explanation of how Sounders FC found unique ways to appeal to both old school Sounders fans and newer fans of the international game. It also attempts to answer the question of “can this be replicated elsewhere?” Have a look if you're interested in learning more about how the best-attended US soccer club achieves such success.

On Forbes - Soccernomics and Wisdom of Crowds Predictions for Men's Olympic Soccer

2012-08-03T11:53:00.001-07:00

A week ago I posted my predictions for the likely outcome of the group play stage of the men's Olympic soccer tournament. The overall predictions were based upon a compilation of the Soccernomics model as well as four other sources across the soccer writing community. The result was a "wisdom of crowds approach that got six out of the eight quarterfinalists correct, as none of the sources used foresaw Uruguay's and Spain's failures to make it through to the knockout stages. I'll return to this topic at the conclusion of the tournament to provide a numerical look at which teams over and underachieved versus expectations.

Posted with Blogsy

On Forbes - FootballrRating.com's Attempt to Move Us Toward A Unified Theory of Soccer

2012-08-02T13:05:00.001-07:00

I am still catching up on being way behind on cross posting from my Forbes account. A few weeks ago I had the privilege of interviewing the team at Chimu Solutions that is responsible for building the FootballrRating.com site. The site is based upon a player rating system developed in the aftermath of Euro 2008 by a group of Northwestern University researchers, and now those researchers are working with Chumu Solutions to monetize the model. This post profiles the model's background as well as the group's ambitious efforts to make the model useful to clubs and agents while also understandable to the casual user who may be looking for an edge in their fantasy soccer league. Have a look at what they're working on, and see if you can supply some feedback to them on the site's user interface or how they evaluate players. That's the goal of their work - take the risk of putting a model out there, and collect the critical feedback needed to improve it.

Posted with Blogsy

On Forbes - Why Arsenal Must Spend £120M To Compete For Championships

2012-08-02T12:55:00.001-07:00

I am still catching up on a number of posts that I have made at other sites lately. This post explained why no matter how much of a genius Arsene Wenger may be, Arsenal must spent nearly £120M to compete with the Manchester Uniteds, Machester Cities, and Chelseas of the world. It was more a post that served as a response to one particular critic's quibbles with data I provided for a post at 7AMKickoff.com. Read on if you'd like to understand a bit more about my statistical models and philosophy, as well as how far behind the competition the Gunners really are.

Posted with Blogsy

The 2011/12 Update to the All-Time Best Managers Versus the m£XIR Model

2012-07-26T12:40:00.003-07:00

I am way behind in cross posting my material to my own blog, so this update is nearly two weeks in coming. Over at the Transfer Price Index blog I posted an update to the all-time manager over and under performance versus the m£XIR model that integrates the managers' performances during the 2011/12 season. In addition to an overall ranking I also provide the first post-Abramovich ranking to study to identify who's out performed the model in the "financial doping era" of the league.

Some of the biggest changes from the 2010/11 ranking include:

Kenny Dalglish falls out of the elite Top 10% of managers with last year's performance at Liverpool. His record is actually to financial expectations if his pre-Abramovich record is excluded and only his Liverpool-era management statistics are used.
Roberto Mancini's championship with Manchester City earned him enough points to move him into the top three managers of all time. In the post-Abramovich era he ranks fourth overall.
Claudio Ranieri's single season with Chelsea in the post-Abramovich era is good enough to give him the top overall spot of all managers who have overseen at least 38 matches since the 2003/04 season.
Arsene Wenger is worth an average of 18 points a season to Arsenal in the post-Abramovich era, and last season he outperformed the m£XIR model by 14 points.

Click on the link above to read even more, and find out where every manager who has at least 38 matches to their record sits in the history of the Premier League.

On Forbes: Why Arsenal Should Give Robin Van Persie the Divorce That He Wants

2012-07-05T10:36:00.001-07:00

It's been a trying 24 hours for me as an Arsenal fan. The inevitable has happened - RVP is leaving the club. The statistician and economist in me knows this was inevitable, and that RVP will likely never have another run of form like he did the last season and a half. The romantic in me wants to believe the opposite, and the fan in me is angered that yet again we have lost our premier player for the second year running. There can't be any other conclusion that our club's aspirations are much lower than they were in the past.

As a way of coping I penned a two page analysis of why Arsenal should look to sell RVP this summer rather than hold on to him another year and have him leave on a free. He's toxic goods around the club right now when it comes to player and coach relationships, and he still has nearly £20M in transfer value to be realized. Arsenal need to think logically during these tumultuous times. The only logical conclusion is to sell him now rather than hold out romantic hope for some sort of reconciliation.