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Analysis In Action: Part Four – Information On The Fly

There have been countless articles/webinars/etc. about performance analysis when the processes are clear – But what about when you have to act on the fly? When opponents change & adapt to you in new ways which you haven’t seen before – Leading to parity or your own side being left completely off guard?

In the first article of the return of Analysis In Action, I thought I’d write about an area of performance analysis writing that has been largely underserved for those interested in the topic. Over the course of the season, your workflows and processes that are consistent are, without a doubt, an analyst’s main bread and butter. However, there will be plenty of moments live in flow of a match (or pre match) that your work will be made much, much more difficult due to the presence of one key factor – The opposition. Sometimes they will play a new formation, start players who you haven’t seen before, or just generally play a different style.

It’s obvious that this area of football analysis is not covered that much – It’s difficult! As well, it’s much less clear to define/spell out, even for experienced practitioners. Ultimately, courses in university (or certifications) can give you the tools to do 90% of the job, but the other 10% requires first hand experience. Hopefully, this non-exhaustive piece will give you an insight to two of the most difficult things to overcome in analysis when your workflows and preparation are thrown as massive spanner in the works: When the opposition are completely unrecognisable to what you saw in your scouting reports, and as well how to deliver information that changes the game in your favour – Either when a match is a stalemate, or you are being dominated.

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Performance Analysis Guide: How To Contextualise Your Tactical Analysis

When working in football – Whether it’s coaching/analysis/etc. Outside of the general technical skills required to do your job at a high level, the most important (and useful) attribute one can have is the ability to communicate your information effectively and in a way which is actionable and effective. I’ve spoken on this topic a number of times via my Twitter account, but was mostly inspired about this from a conversation I had with good friend Jon Mackenzie on his now sadly defunct podcast (fittingly named A Podcast About Tactics) Within the various roles I’ve been fortunate enough to hold, utilising these skills makes the difference between effective work & that which is laboured/taxing/and out-right not providing insight. 

There are various ways to provide effective feedback: Whether it be through your basic technical workflows (having information in a timely fashion, the ability to work with different software, etc.) or how you tailor your work for the needs of your players & staff. My conversation with Jon covered the latter of these, specifically the tactical information. 

There are an unlimited amount of things an analyst can cover within the actual “on the grass” side of things – Build up, final third finishing, individual player roles, etc. and all of it doesn’t exist in a vacuum: There is an another side the team (either your own or the opponent) on the pitch who changes much of what a team tries/is able to do. Because of this, presenting the information to cover all of this in a way that makes sense is invaluable. In writing this, I will hopefully be able to break it down for you – Allowing you to do similar within your own workflows.

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Getting The Most Out Of Training Sessions With Effective Analysis

When it comes to analysis, it’s easy to be blinkered and focused on the outcomes. In the context of high level sport, this is obvious: The match. Watch games, find flaws & strengths, and then draw conclusions from there. Make no mistake – matches and competition are where you can garner the most efficient data-points from. However, when you take a step back from it all, how much of a team’s week is oriented in this way? i.e. playing games? Not much. Within a typical schedule, there will be 1-2 matches, 1 full rest day, and other 5 will be training: The balance and allocation of resource/workflows is all off.

Coaches and their support staff take great effort into designing training sessions on the pitch, but the actual diagnosis of the effectiveness of training and the growth of the team/individual is an afterthought. How, as an analyst, can we help change that by increasing our outputs in these settings and bridging the gap between practice (where much of development is made) and competitive fixtures (where this development is shown). This article is just that : A “how-to” of sorts to that presents ways to maximise training workflows and outputs gathered from practice.

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How to Make your Strikers Play Like Erling Haaland, Part Two

When a striker walks on the world’s stage at 6’4″ and nearly 200 pounds, we don’t tend to comment on how they tenderly caress the ball. It’s monster trucks and mayhem, a demolition derby of hold-up play and headers, but never fine-tuned gambetadorial silk. That is—until now.

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Reassessing Goalkeepers (Again): How Much Do They Influence Shooting?

Reassessing Goalkeepers (Again): How Much Do They Influence/Affect Shooting?

Introduction

Goalkeeper metrics and advanced data are still far from perfect, that’s not entirely news. It wasn’t until a few years ago that basic metrics such as save percentage were the barometer for what determined good goalkeeping – Save a lot of shots, and voila! That’s a good goalkeeper. However, with a lot of basic aggregation statistics that provides tons and tons of issues for evaluating players. For example: Mark Flekken of Freiburg, currently has a higher save percentage than Manuel Neuer. While the Freiburg stopper is a good player, are we led to believe that Neuer is worse than he is? Even metrics like goals conceded per 90 are conditioned by tons of external factors (team strength for one) and are not indicative of individual quality. 

SInce these days, we’ve now moved onto more advanced metrics/models which help better grasp how goalkeepers perform: Post shot expected goals, goals saved above average, etc. are just some basic examples of these. They help contextualize more information on the goalkeeper (their position, habits in goal) as well as the information of the demands placed on them by the shot (shot height, end location of the shot, etc.) rather than simple “accumulation” statistics. With all this information in our grasp, and readily available for analysis, how do we link this higher level of data/analytics with traditional coaching habits and ideas on what constitutes good goalkeeping?

An example of how increased stability/sophistication surrounding goalkeeper metrics & data has given us newfound insight into how they rate within their position.

Growing up as a goalkeeper myself in the American college system, training with MLS/USL clubs as well as my brief coaching of goalkeepers before moving into performance analysis, I was always taught and taught myself about ways (particularly in 1v1s) about how the player can “make the opposition miss” Whether it be making sure your angles are spot on to take up as much of the goal as possible, to pretty much the fugazi idea of having an imposing presence to make opponents lose composure. While much has been done in improving how we evaluate goalkeepers in terms of saving shots, not much has been done in regards to putting objective findings behind how they affect misses. Simply put – Can good goalkeepers influence how often the opposition hit the target? That’s my end goal, and I think I’ve found some interesting findings thus far!

Before we dive into it, the data set: I’m using goalkeeper data (and by extension shooting data) going back to the beginning of 2018 up until the start of this season from the “Big 5” leagues in European football. While most of the data has been unedited, I’ve manipulated some of the data myself to help better provide situational context to the players as needed – This will become clear as you read on.

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Analysis In Action: Part Three – Mailbag!

Analysis In Action: Mailbag! Answering Your Question On Analysis “In The Field”

First off, to lead part three, I’d like to issue a thank you to everyone for reading this series thus far. When I first decided on sharing my experiences and writing this series, I didn’t think it would be as popular as it has been. I think it’s a testament to how important analysis in football has become, and how the growth in the community space online is reflected; I’m just happy that I get a chance to call it a “career’ and help people out in some small way.

Another thank you to everyone for joining me and Carl Edwards of Rotherham last week with our Analyst’s Q&A: We hope to turn it into a running segment, and if you read on to the bottom, I’ll have some more news to share on that front…

So, this part of Analysis In Action will be a bit of a mailbag to break up the general flow of my thoughts thus far. In addition, this series was created to help people understand what the day-to-day role looks like and how to improve their own skills – You’re naturally going to have questions, so it’s good for me to address them. 

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World Cup Qualifying – Honduras (1) – (4) USA: Tactical Analysis

 “Football is a tale of two-halves”, the old cliché couldn’t have been truer than when the USMNT travelled to Honduras for their 3rd round match of World Cup Qualifying. Trailing 1-0 at halftime, the USMNT looked lost. Without ideas in possession, and a poor and uncoordinated pressing structure out of possession. With three subs made at half time, and a change in formation from a 5-2-3 to a 4-3-3, the USMNT managed to turn a dyer first half performance into an extremely important 4-1 victory picking up all three points on the road.

The new formation was not the only halftime change, as the USA also began to pressure higher up the picture and more aggressively.  A xG increase from .49 in the first half to 1.54 in the second half helps to tell the story for the Americans offensive improvement, while Honduras first half xG of .82 dropped all the way to .34 in the second half.

The USA also managed to decrease their PPDA (passes per defensive action) from 9.9 in the first half to 7.7 in the second half; a clear indication of their increased pressure.

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Analysis In Action: Part Two – Organizational Structures & Effective Feedback

Providing Effective And Organized Feedback Amongst The Chaos:

Football is chaos – And your job as an analyst is to package/collect that chaos into something that is discernible and palatable. Fun, right? While that can be tough at times, having clarity in your organization juxtaposed with the game itself (not-organized/fluid, mostly) is a huge factor in supporting one’s ability to do just that. This manifests itself in a number of ways: 

  • Use of technology/applications to database information.
  • Clear processes in your workflow so you can “automate” (without going on autopilot) the day-to-day admin.
  • Knowing how and when to feedback necessary information.

In part two of the series, I’ll give my thoughts and tips on how to do exactly that. This can be a bit of a dry subject: The operations of performance analysis are much less fun than the actual analysis process (i.e. watching games/training, looking at data, interacting with other people, etc.) but your ability to do those things effectively are dramatically affected by said “administration.” Hopefully by giving examples of it in practice this will provide concrete ideas of how to improve your own efforts!

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Coaching “Vision”: How to Turn Scanning Research into Training

The widely-held notion is, typically, that these players can see what others can’t, enabling them to then act on those esoteric opportunities. We call these people maestros or artists, in large part, due to their ability to create beauty out of what we might perceive as nothingness–but it’s often not the technical, execution-level ability, itself, that manifests in these stunning passes. It’s the amount of information they collect, and base their decisions off of, instead.

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Analysis In Action: Part One – Self Collected Data

If I were to write an article about explaining various metrics, “what is performance analysis?”, and other topics about what advanced analytics/analysis is, it wouldn’t get a lot of traction – People are still obviously interested in these: It’s not 100% part-and-parcel of the game yet, and there is still a lot of negative reaction when advanced statistics, specialization in coaching, and increased levels of objectivity are sought out. However, throughout my time working in football and since it became my full time job 4 years ago now, I have always tried to frame my work which can be summarized in one word: Actionable.

Ultimately, posting visualizations, videos, threads on tactical tweaks, etc. can get you picked out from the crowd and show people you have the technical skills to get a job. However the day to day of actually working in the game and making it usable is VERY different: Deadlines are more meaningful, ad hoc requests come out of the blue, and you need to work within a framework (ideally) of the coaching staff’s game model. The goal of this mini-series is to help people understand some basic tools I use (and those who are at level above me!) to translate technical skills to working at it. 

To do this, words are somewhat unhelpful: *Describing* how to work is just an extension of the articles I’m trying to get away from. Alongside this mini-series, I will be posting example data dashboards, presentations, and more! Hopefully it’ll give you a flavour of what I do. I cannot share all my trade secrets, of course, but it should serve as an inspiration and understanding for what analysis is like in the real world. Part one will look at “self collected” metrics.

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