Over and Under-Performers

We're now nearly a quarter of the way through the season so I thought it'd be a good time to have a look at who is under and over-performing their underlying stats so far this season. In this context, a player is over-performing if they have more goals/assists at this stage of the season than we would expect them to have given their underlying stats (shots, touches in pen box etc.), an under-performing player is one who has fewer than expected. In short, those who are over-performing have probably been lucky and are unlikely to sustain their good form over the season. Being lucky doesn't mean they are not good players, just that they're conversion rates are probably unsustainably high.

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Biggest Over-Performers

• Sturridge - You probably didn't need me to tell you he won't score 35+ this season, though 23+ is a more than realistic target and he's still a great FPL option.
• Remy - Has slipped under the radar in scoring 5 goals and has probably been fortunate to have done so.
• Suarez - Isn't going to average 1.5 goals a game, but could be pretty close to averaging 1 a game.
• Oscar - Mourinho's poster boy has perhaps been lucky in 4 early goals which has secured his role as Chelsea's number 10, he ranks behind Hazard for expected goals in our model.
• Van Persie - This is an odd one as many will say he's not in good form. His presence here is due to his penalty taking responsibilities, though historically he is one player who has always converted chances at a very high rate.
• Yaya Toure - probably won't score incredible freekicks all season, but still offers some goal threat.
• Lukaku - Another who over-performed last season as well, he seems to get very high percentage chances so may continue to over-perform the model.
• Brady - Another penalty taker giving him 'free' goals.
• Giroud - Same category as Sturridge, good value but is closer to scoring once every 3 games.
• Aguero - See RVP and Lukaku, could outperform the model all season.
• Ramsey - Despite scoring 5 of his 13 total league goals this year, he is only slightly over-performing. Ramsey isn't just a bandwagon, he is a solid FPL player.
• Baines - On freekicks and penalties so will probably do better than the model predicts.
• Soldado - Penalties again given the Spaniard an over-performing tag despite not hitting top form yet.

Biggest Under-Performers

• Walcott - Can consider himself unlucky not to have scored earlier this season, expect goals when h returns from injury.
• Townsend - The shot happy midfielder has delivered goals in the Europa League and for England but has been lucky to have only scored 1 in the league so far.
• Walters - The model rates Walters quite highly, he may be due a goal sometime soon, though Stoke's attack doesn't demand much attention.
• Fer - Similar to Walters, may contribute a few goals this season but there's little reason to consider him in FPL.
• Cisse - Perrenial under-performer ever since his first few months at Newcastle, out of the team now and there's not much to suggest he'll find his way back in.
• Mirallas - A hot pick in preseason, Mirallas hasn't quite delivered on promises but he remains a solid FPL pickup.
• Michu - The infamous 'regression to the mean' has hit Michu this year, he outperformed the model by 10 goals last year, even so we can expect his goal tally to increase soon.
• Adam - See Walters and Fer.
• Lambert - A bit of extra luck and Lambert would enter into the Sturridge and Giroud debate for best striker at the start of the season, should be a reliable source of points for the rest of the year.
• Eriksen - Known more for his creative threat, Eriksen may be unlucky not to have scored yet.
• Paulinho - I'm unsold on Paulinho, his stats are good but inflated by a few great games. He offers security of starts in a good attacking team though.

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Biggest Over-Performers

• Ramsey - While he may continue with a good goal threat, I'm not sure Ramsey is going to offer significant assists this year and certainly doesn't justify the 4 he has so far.
• Giroud - Has 4 assists so far and won't keep it up, but is the 2nd highest rated forward for creativity so far (behind Rooney)
• Mirallas - He's not getting goals but does have 3 assists, expect those numbers to reverse over the season.
• Pablo Hernandez - His underlying stats are good and Swansea create high quality chances so do not fear too big a drop-off here.
• Negredo - May be lucky with 2 assists so far, but with players like Aguero playing off him he'll continue to get assists throughout the season assuming he plays.
• Zabaleta - A brilliant fantasy prospect last year, Zabaleta has offered very little going forward under Pellegrini so far despite 2 assists.
• Enrique - See Zabaleta.
• Ozil- Do not be worried about slight over-performance here, Ozil's class means the chances he creates are always likely to be converted at higher rates.
• Silva- See Ozil.

Biggest Under-Performers

• Snodgrass - another player tipped for a good FPL season, he's been unlucky not to have any assists yet, though Norwich are not a team warranting FPL investment at the moment.
• Townsend - If the model is correct then we could see an explosion from Townsend in an upcoming game.
• Walker - Currently sits with zero goals and assists despite getting forward a lot, I'd expect around 5 assists for the rest of the season.
• Oscar - Is the inverse of Mirallas here, expect a bit more creativity and a bit lower goal threat from Oscar for the rest of the season.
• Baines - Yet to record an assist but with set-pieces and Lukaku to aim for this should change soon.

Ending Notes

First, penalty takers are likely to over-perform on goals across the whole season, unfortunately I don't see a way of modelling how often teams will get pens (and if I could, they are too rare an event to predict), so this has to factored in post hoc.

Second, it's also important to note that many of the over/under-performers are only out by one goal/assist. A goal/assist this weekend would see most of the under-performers move in-line with their underlying stats, similarly a blank this week would bring most over-performers into line with the models predictions.

Player Rater GW9 Update and Average Time Played Inclusion

Hope the fantasy weekend was kind to you, here's the updated graphics:

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Comments Using the Player Rater Expected Points Model

Last week I highlighted Suarez and Aguero as elite attackers, and they duly delivered last week. They've gone up even further in the rankings, and these two players really do sit in a tier above all others. If you can fit both in your team then do so! Rooney also had a good week and has gone up the rankings, include him in your front three and you've got a deadly but expensive trio. Again, Lukaku, Benteke and Lambert offer cheaper options if you prefer. Sturridge, Giroud and Soldado delivered again, and they're worth holding, but if you need a new striker then do not overlook Suarez or Aguero. I also claimed RVP wasn't worth his price, and he duly delived a goal and assist to prove me wrong. He will outperform his stats consistently, but with Rooney keeping pace and Suarez and Aguero dominating, I still see little reason to consider him.

In midfield Ozil disappointed a little, Ramsey maintained his good stats, and there is little happening elsewhere. Silva looks a good buy, but isn't going to match Aguero for points. Despite a very quiet week, Hazard seems a better option than Oscar in the Chelsea midfield, I might write an article comparing the two later in the week.

I also backed Coleman who finally delivered a CS after an extended period without any points, he still does well for attacking threat. Debuchy scored over the weekend and jumped up among defenders, he has good attacking threat but I'd steer clear of Newcastle's defence for now.

New Slider - Average Time Played

You may have noticed a new slider on the graphics titled "Average Minutes", this is calculated simply as Minutes Played divided by Appearances. I received feedback saying that the model wasn't great because it was affected by those making sub appearances (such as Deulofeu ranking highest for expected goals per minute). You can now filter by those who average a certain number minutes, identifying those who do not just come of the bench at the end of games. Using this with the appearances slider should help you find those who are playing games, and playing lots of minutes in those games.

I'm considering integrating this metric into the model as well. The advantage of doing this is it allows us to better make comparisons between players. For example, Eriksen has 46% better production than Paulinho, but Paulinho averages 95 minutes a game, Eriksen only 68. Take this into account and the two players rate very similarly. Seeing as FPL is played on games rather than minutes, it makes sense. At the moment the model assumes every player will play the same number of minutes which clearly isn't true.

The problem is that I don't see a clear way to distinguish 2 players with the same average minutes. For example, say we have two players with identical stats and both average 60 minutes a game. But, one player starts every game and comes off after 60 minutes, the other plays the full 90 minutes, but is benched every 3rd game. There's a question over how to compare the stats of these 2 players, I could build in a measure of variance, but that assumes low variance (the player who plays 60 minutes every game) is desirable which may not be the case, especially with bench players who can come on.

I'd love to hear thoughts and opinions on this and what direction to take this in.

Blog Notes

Either today or tomorrow I should have a post out about which players are currently over and under performing their stats in assists and goals. The Team Rater to assess clean sheets is also in the works.

Player Rater GW8 Update

Sorry for this being a late post, but here's the updated graphic which includes GW8 stats:

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New Graphic - Expected Points

I also wanted to introduce a new graphic which shows expected points for the season so far. It only considers FPL points that are gained from goals and assists and the subsequent bonus points award for these. So things like appearances, clean sheets and bookings aren't considered at all. The calculation for expected points is:

Expected Points=(Points for Assists)*(Expected Assists)+(Points for Goal)*(Expected Goals).

Where players get 3 points for an assist, plus some bonus points, and 4,5 or 6 points for a goal (depending on position) plus bonus points. The estimates for bonus points awarded are taken from this article. Again, the values are adjusted for minutes played.

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This graphic can now be found under the Player Rater tab along with the above graphic.

Comments Using the Player Rater Expected Points Model

Upfront there's an elite of 3 players I'd target: Suarez, Aguero and Benteke. Giroud, Sturridge, Lukaku, Rooney, Remy and Lambert fall in the next band and are also excellent choices. Bony and Eto'o would be in that category too if only their minutes were secure. RVP is ranked just 13th for strikers and I can't see him being worth his price tag.

In midfield there's an odd bunch, but Ozil dominates here, with Hazard, Michu and Silva also showing good production. Using the Goals and Assists visual above we see Ozil and Silva dominating in expected assists, they really are a class above. Mirallas, Ramsey and surpisingly Eriksen seem good mid-price options if you feel their places are secure. Amalfitano looks best of the budget bracket, though Januzaj's stats are worth paying attention to.

The highest rated defender is Kolorov, but his place is always in question. The highest rated and secure defender is Coleman, who ranks only just behind Barkley, showing how attacking he really is. Coleman's a great pick and hopefully a season keeper despite giving 4 points over 4 weeks. Ivanovic and Glen Johnson offer good attacking threat and are worth their price tags, while Swansea have a number of defenders worth considering.

Blog Notes

I hate to say I called it, but Townsend delivered on his stats this week with a deserved goal for Tottenham, with a rest midweek expect another start and more points.

I'm also working on a Team Rater which should show which teams are most attacking and most likely to keep clean sheets. These will be coming soon.

Fantasy NBA Player Rater

I know this is a football blog, but I'm a big NBA fan as well and with the season starting in a few days I've been getting ready for some fantasy drafts and came up with a simple model to rate players, and a nifty graphic to show which players might be worth picking up and which are currently being drafted too highly.

Quick disclaimer, this model uses ESPN's own projected stats which can be found here, so the model will only be as good as those projections are. If you disagree with those stats then let me know, but I've got faith that ESPN's analyst are some of the best out there (that provide data for free atleast). The projected stats were taken on the 23rd October.

Total Standardised Score

My model is built on a system of standardised score, where players performance in each scoring category is calculated as a value relative to the average. If a player is exactly average in one category then their score is 0, a positive score means they are above average, a negative score means below average. The score for each category is then summed up into one measure: Total Standardised Score. The advantage of this is it allows you to see the overall impact a player will have on your fantasy team. For example, a player might offer you a lot of assists, but if he's costing you elsewhere then is he beneficial to the team? Likewise, a player like Howard might cost you in FT%, but do his numbers elsewhere make up for this?

You can find more info on this method here, ESPN's system seems slightly more complex than mine, but I hope the use of mine is clearer.

Average Draft Position vs Total Standardised Score

Below is the graphic I wanted to post. Along the bottom you have the average position players are being drafted at in the ESPN game, I've selected the Top 100 as beyond the 10th round you'll be looking to flesh out your team and pick players that compliment those you've already drafted. Along the y-axis we have Total Standardised Score, the higher the better.

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Each data point is a player, mouse over and you can see who it is. The size of the data point is the standard deviation across all categories. Smaller circles imply production across all categories while large circles imply excelling in some categories but falling behind in others. For example, Dwight Howard has a large circle because of his high FG%, Blocks and Rebounds, but below average FT%, 3s and Assists. Paul George has a small circle because he contributes well in all categories.

The bands show the different rounds, assuming a 10 team league.

Finally, the graph is interactive, you can click on the positions below to highlight each in term.

Comments and Position Tips

The first thing to note is the negative relationship, so better players are going earlier, good start. More interesting is when we split players by position and see how the score deteriorates over the rounds.

Most strikingly, the standardised score for PFs does not differ much throughout the first 10 rounds, Kevin Love is not rated much higher than Derrick Favors who is going 7 rounds later. The shallowness of the best fit line shows how there is not a great dropoff at the PF positon.

On the flip side, the SF position does deteriorate through the rounds, there's a top 6 (James, Durant, Anthony, George, Batum, Smith) then a huge drop off.

There's a good spread of Centres and Point Guards throughout the Top 100, so take them as you can. Though again there's an elite group of 4 PGs (Curry, Paul, Irving, Williams) who would all make good first round picks. The depth at PG in the NBA means you can still pick up a good PG as late as late as the 7th in someone like Bledsoe.

SG is an odd position, there's Harden, who should be drafted Top 5 if you can, then a huge drop off. Wade is an option, but his playing time will surely be down, and Bryant is an unknown. After that otherwise I'd let this position slide to the 7th and get someone like Mayo or Oladipo if your happy to take a rookie.

Overall I'd target one of the top SF or PG first, then look for a C, then worry about the PF and SG spots last. Though of course it depends on your pick, if you can take Harden 3rd then Alridge at 18th, do it.

Player Tips

Just some quick tips on who is being overlooked so far and who is worth leaving till later rounds.

Pickup:

• Kemba Walker - gives you everything you need at PG and is probably going late because of the team he plays for rather than his stats
• Paul Millsap - doesn't hurt you in any category and excels in Steals and Assists for a big man
• Jeff Teague - solid pickup as your first bench option
• Jimmy Butler - quickly rising up through the ranks in the last few days and with good reason. Great production across the board.

Pass On:

• Marc Gasol - great player, but probably overvalued in the 1st. Howard and the two Al's are better options.
• Brook Lopez - sits well below the trendline for centres, blocks aren't enough here.
• JR Smith - will end up hurting you with poor FG% and little defensive contribution.

Risk:

• Derrick Rose - former MVP in the 2nd round? Big question over fitness but could be a steal.

Wrap Up

I hope this post has been interesting to someone, I'd love to hear some feedback on my first NBA post. If anyone's interested I'll post the spreadsheet up for people to download.

Player Highlight: Andros Townsend

Following his impressive England displays and involvement in a bizarre changing room incident, Andros Townsend is on the name of many lips. Many fantasy football managers are also eyeing up Townsend as a cheap (currently priced at 5.5) route into Tottenham's impressive attack. With the likes of Soldado and Eriksen not yet delivering the FPL points expected of them, the case for considering Townsend is stronger still. Midfield is also an area which is not living up to FPL expectations, so many are looking for a differential. This post will have a quick look at how the Player Rater model values Townsend and will be a good example of how the model can be used.

Player Rater Model - Spurs Options

First let's have a look at the PR Model for all of Tottenham's players. Below is a graphic of the PR Model just for Tottenham players. The size of the data point is minutes played and the colour is position (dark orange for forwards, orange for midfielders and light orange for defenders).

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Note, some players have a negative expected goals value, this is clearly a problem in the PR model, but it is a problem of small data sizes, with only 7 games being played. I expect these issues will work through as more games are played. Those with a negative expected Goals have had excessive shots off target which the model doesn't like, but a single shot on target will move any of players into a positive expected goals.

We see that Townsend is one of the best options according to the model, offering significant assist and goal threat. Only Sigurdsson offers a slightly higher expected goals value, while Eriksen offers a far more creativity for only a little less goal threat. Townsend therefore looks a great option within this Spurs attack. In fact, if he were to start and finish all of Spurs games, we might expect 10 goals from him this year. That is a massive if though, and is the problem with picking up Townsend: rotation. So far his position has been secure, and looks likely to be over the next few weeks, but with a fully fit squad there is Lamela, Lennon, Chadli and Sigurdsson all vying for Townsend's place. Even if Townsend were to nail down his role in the team with good performances, we can expect him to be rotated a lot with Europa League games in mind.

Not only that, looking at the graph we see there are plenty of good options in the Spurs midfield, if Sigurdsson were nailed on he would probably be a better choice, Eriksen promises to contribute many assists although at a higher cost, and Paulinho has more modest but solid stats and a seemingly secure place (though he has Sandro, Dembele and Capoue to compete with). Soldado is still a good option as well, though he might be one to steer clear off in the short term until he finds some form.

A note, I see many other sites favouring Paulinho over Eriksen, and I wanted to offer a word of caution that Paulinho's stats are inflated by 2 standout games against Cardiff and Swansea. He had 5 SoT over those 2 games, but only 1 across the other 5!

Another quick note from this graphic is how little threat Vertonghen is offering, yet how high the reputation of him as an attacking defender is. He is more likely to pick up Bonus Points than Walker, but I'm not sure that alone justifies his higher price over Walker.

Player Rater Model - Midfielders

The below graphic shows the Player Rater model I introduced here, but with only midfielders show. Townsend is highlighted.

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What's startling is the player that Townsend is nestled under: Michu. A hot pick among FPL players and last years FPL poster boy, Michu has almost identical Expected Goal and Assists values to Townsend, highlighting Townsend's incredible production so far this season. In fact, only Ozil, Walcott, Eriksen and Michu are expected to have got more points so far this season and offer a guaranteed place in midfield. With only a single assist so far this year, Townsend seems to have been very unlucky not to have acquired more points.

Conclusion

Considering Townsend alone though, his underlying stats are fantastic*, he is a direct and often selfish player and for fantasy football this is fantastic. A word of warning though, if he is to keep his place in his team he will probably have to reduce the number of shots he takes, reducing his appeal.

The positives are his underlying stats, his good form for club and country, and a somewhat secure starting role for the short term at least. The negatives are the rotation that will come with a fully fit squad and the question of whether Townsend has the quality to convert his productivity into FPL points.

The verdict? He makes a great short term punt with huge upside, and if he nails his place down through good performances he'll be bargain of the season. Otherwise, long term, he is probably best avoided despite his stats, unless your happy to see the frequent 1 point bench appearances as he comes on for 10 minutes at the end. There are also better options in the Tottenham midfield, namely Eriksen or even Sigurdsson if he continues to start. Paulinho is a good alternative too and comes with less risk.

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*I'd love to post his stats but I do not have the rights to. I strongly encourage you to head over to the excellent Fantasy Football Scout and sign up as a member, where you'll have access to Opta's data. It costs £15 for the year, but if your interested in football stats it's fully worth it. I am not affiliated with FFS in anyway and have not been asked to post this, I'm just a huge fan of their site.

Explaining Yellow Cards in the Premier League

For this post I'm going to look at an often overlooked aspect of fantasy football: yellow cards. We often chase those elusive goal and assist points but pay little attention to those -1 points from cautions, only taking action when a player is suspended. This post seeks to explain yellow cards and see if there's any players this year we might want to avoid.

The Yellow Cards Model

Using data from the 2012/13 Premier League season I built a regression model to try and explain what factors determine how many cards a player picks up. I choose to focus on yellows alone because straight reds are too rare an occurrence to explain and are just as likely to be given for unforeseen events (Hazard's ball boy incident) as for bad tackles. Cautions are usually given for reckless fouls (though are also awarded for diving, unsportsmanlike behaviour etc.) and so are better suited for analysis. After playing around I settled on a model where I regressed yellow cards received on 3 variables: errors leading to chances, fouls conceded and tackles.

The estimated model is:

YellowCards=0.161errors_leading_to_chance+0.086fouls_conceded+0.018tackles

(All variables are significant at a 5% level, the intercept is not)

For the lay person, this equation allows us to calculate how many cards we might expect a player to receive given how many errors, fouls and tackles they've committed. For example, Fellaini made 95 tackles, commited 81 fouls and had 3 errors, so we expect him to pick up 9.16 YC over the season. He actually received 9.

The correlation for the model is 0.79 (R²=0.62, so 62% of the variation in yellow cards can be explained by the model).

Below is a plot of expected yellow cards vs actual yellow cards. We see a strong positive relationship, which is encouraging for the model.

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Comments on the Model

The model is not revolutionary, it says the more tackles, fouls and errors a player concedes the more cards they are likely to pick up. It does however give exact estimates of how these variables translate to cards.
Some first impressions:

• Overall the model shows a good fit and an expected yellow card translate almost 1:1 to a received yellow card.
• There's a lot of variation, but this to be expected since we are only really explaining yellow cards awarded for fouls and challenges. There's also variation between referees strictness, as well as variation within each referees to award cards for a given challenge (a ref might see two identical tackles but only give a YC for one and not the other).

The model is also useful for identifying those who are anomalies in the model and have an excessive avoidance/attraction (clean/dirty) to cards.

Avoiding Cards (received fewer cards than expected):

• Routledge, Berbatov, Diame, Kone, Ba, Sessegnon, Arteta, Oscar.

• These are players who are either excellent at making tackles, or only commit minor fouls. It may also be they are good at getting away with fouls! There's also a large element of luck here. They seem to be more attacking players so their fouls are more likely to be minor infringements. They are also players with good reputations, so referees may be letting them get away with more.

Attracting Cards (received more cards than expected):

• Perch, Whitehead, Collins, Williamson, Caldwell, Suarez, N'Zonzi, Shawcross,  Lowton, Scholes.

• Again, luck plays a huge part here, but all these players seem to have a reputation for being 'determined' tacklers. Perhaps the fouls they commit are more likely to result in cards, or maybe refs are quicker to punish them, probably a bit of both. Suarez stands out in particular, his cards for diving causing the problem here. Again, we are only really explaining cards from tackles here and not dives, unsportsmanlike behaviour, excessive celebrations etc.

From these two groups we see that defenders appear to be underestimated in the model, while attackers are overestimated. Simply, a foul or tackle committed by a defender is more likely to draw a yellow card. This is understandable given the nature of fouls attackers will commit, and their position on the field when committing them. I'd love to be able to split the data by position and see if this is true, unfortunately I don't have that data available.

Applying the Model (Use for FPL)

We can then take this model and what we've learnt and apply it to this years data and see who is most likely to have picked up cards this year. This is going to be the application of the model to FPL. Looking at expected yellow cards is going to give a better view of those card-prone players than looking at cards themselves which are more likely to be affected by random variation so far this season. The graphic below shows the 50 players with the highest expected cards, along with their number of cards they've actually picked up.

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(Note, the values aren't adjusted for minutes, they are totals)

We see Wanyama sitting pretty at the top with 2.138 expected YC, he's been rewarded 2 so the model looks good for this year too. Van Wolfswinkle has been lucky not to receive a YC so far (though remember we said that the model overestimates cards for forwards). Most important to fantasy interests are Ramsey, Noble and Zabaleta, who are on course to pick up 10 YCs over the season, making them dangers at reaching the 1 game ban for 5 yellows. Rooney also ranks highly, though I wouldn't worry about him picking up enough for a ban. Ivanovic at 16th is also interesting, we know yellows negatively affect BPS, so Ivanovic's propensity to cards gives even more reason to favour Terry who seems a bonus darling so far this year.

Conclusion

In conclusion, we can create a pretty good model for explaining how defensive work translates into yellow cards. For the small amount of data I have I'm fairly happy with the results, despite large variation in the data. However it's clear the model underestimates defenders and overestimates strikers, fouls committed by defenders are more likely to pick up yellows. If I develop this model I'll look more closely at that. The model must also be complemented with knowledge about players tendencies and temperament to offer a better overall explanation of yellow cards.

As for FPL, it's worth checking these charts to see if your transfer targets or current players are likely to pick up cards and use that as part of your decision making.I hope those with models that forecast FPL points might be able to build this into their model, and those with bonus points model's might factor it in as well.

This is my first real attempt at an article, so I'd love to hear comments below or via Twitter @The_First_Touch.

Edit (08/11/13)

It turns out that Mark Taylor has already written a brilliant and in-depth piece on How Fouls Turn into Cards and I highly recommend you head over and read his article.

The Player Rater Model

This is a visualisation of a model I'm working on which calculates how many goals and assists we might expect a player to have given their underlying stats (shots, shots on target, key passes etc.). I'll delve into the model itself as the blog develops but I wanted to post this graph to give you an idea of the content you might find here.

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The graph shows a plotting of expected goals and expected assists, adjusted for minutes played. Each data point is a player, the club badge showing who they play for. To the right you have a set options which allow you to filter the data and I encourage you to experiment with it. For example, if could look purely at Arsenal's midfielders and discover that Özil is the most creative, while Walcott carries the greater goal threat.
Essentially, as you move to the top right, your getting into the elite fantasy football players you should be targetting.

Some players are excluded so if there's anyone missing you'd like to see then let me know.

You can now find this at all times under the Player Rater tab.

Welcome Post

Hello and welcome to the blog!

I've been meaning to set up this blog for a while, and have got a whole host of ideas of what to write about. The blog will mainly focus on fantasy football topics, but will also cover football in general, from tactics, to positional studies, and to team reviews. However all post will have a strong statistic and analytic focus, it will be number heavy! However I'll try and make sure explanations can be understood by all. I'm by no means a stats expert, but I do have a background in econometrics (statistics for economics), so I have some grounding in statistical theory. I hope some find this blog of interest, and that discussions about analytics in football can be started from it.

This blog is very much a work-in-progress, so don't be surprised to see many changes at the minute.

The best place to stay in touch is on twitter: @The_First_Touch