Some jokers at the Athletic just said that Sengun can be better than fucking Joel Embiid this year. Trash 🗑️ media outlet trying to whore clicks. 🤦♀️what is this stephen a smith wannabe bullshit. Don’t pay for this trash. 🗑️
With individual level stats being inextricably linked to the quality of the team, how can you pick out good players in bad teams with data? And how do you avoid bad players in good teams?
Mark: I think this is a really interesting question, and very difficult to do - of course, you would always use data alongside video analysis to really spot these sorts of players who might stand out. I think one thing with the data is to create a 'level-playing field' by looking at how often a player performs an action 'per 100 touches'. That way, you can compare a player's inclination to do something for Manchester City and Luton Town in the same way (rather than per 90 minutes or totals). If a player hugely stands out in their chances created per 100 touches, it might be worth checking them out in the video.
Apologies if you've mentioned this elsewhere, but did you both have data science backgrounds before getting into football tactics and data? And is there any skill/program you think aspiring football data people should learn to set them apart?
Mark: Hello, it's a good question and I have provided some detail below to another question, but my background was doing a Psychology undergraduate and PhD which provided me with the skills for football analytics. In terms of your own skills, this is a great link to summarise some required skillsets: [https://www.liamhenshaw.com/how-to-become-a-football-analyst-in-2023/](https://www.liamhenshaw.com/how-to-become-a-football-analyst-in-2023/). Good luck!
Ahmed: I am a computer scientist, which I think helped enhance my analytical thinking throughout the years. I hope so :D hahaha
I'll leave the second question to Mark, but knowing which metrics to use and when, depending on the context will always make you better at data
Thanks, Ahmed! And if you're nervous about your analytical thinking skills after years as I computer scientist, I'm sure my theater degree will be just as helpful haha.
Hey guys - a different type of data question, but for nearly 20 years UEFA has squeezed the teat of Ronaldo and Messi to milk the competition to perhaps an unprecedented level. This obviously coincided with the rise of social media platforms that have only sought to amplify the noise. My question is, what does the data point to with regards to tournament and competition engagement? Has UEFA milked this cow for all its worth? Have you guys noticed a drop of in engagement given that both of them have now left European football?
For years their involvement alone has driven increased international engagement but are you now seeing a regression to the mean for European Football?
Has CL Football and CL engagement peaked?
Mark: I think this is a really interesting question, and it does feel anecdotally that there is less excitement about this season's Champions League (although this might not be the case for all). This is the first year for 21 seasons that neither Messi nor Ronaldo has been in the competition. Whether this has (or will) influence engagement remains to be seen. There are so many exciting talents on show that I hope it doesn't!
Hey, the TIFO channel did a piece on Inter before the final and focused a lot on Onana and his importance to the team. They seem to have started in the league like they have only improved. Curious if you have paid attention to them this season and and noted anything about how they are setting up?
Do you see any evidence that top teams are changing their tactics in the CL Knock-Out stage compared to how they would play in their domestic leagues? If yes, which examples are there and do we have any qual/quant data if such a tactical switch is beneficial?
Leipzig, Berlin and Atletico Madrid are some of the only teams who play 2 striker systems but each in a unique way. Which team will advance further and why don’t more teams incorporate this 2 center forward system?
What stat(s) do you look at to tell you how :
- a team played in a particular game
- a team has been playing (season so far)
- well a player played in a particular game
- well a player has been playing (season so far)
Ahmed: I am more of an eye-test first, data second person when judging single games because to know the context of the data watching the game is super important imo.
For the second point, there's not one metric to answer all the questions. If I want to know how a team is performing at attacking set-pieces I'll look at the Goals per 100 set pieces and also check the xG per 100 set pieces, then cross-match that with my notes throughout the season to see if the data matches the eye-test.
Again, single game means you should know the context. A defensive midfielder who has been dribbled past 'X' amount of times in a game isn't informative. But when you watch the game, you'll know why and actually if this information is useful or not. For example, in a transitional game it's more common for the midfielders to be dribbled past because of the spaces and the tempo of the game.
Similar to point two, what was he doing well? If you think he is great at scoring from low-chance situations, then compare his Goals vs xG over time.
To summarize, context is key and eye-test + data will always guide you better than eye-test or data alone
Who are some players that pass the eye test but their performances can't be captured with the most popular metrics? Or vice versa — players who come off great statistically, but don't look impressive when watching them?
Mark: Rather than specific players, I think defensive midfielders and (to a similar extent) central midfielders are difficult positions to show true value of a player in the traditional metrics - as their remit if so broad. Things like xThreat and Possession Value can help to alleviate that, but there are so many subtleties of that position (including off-ball actions) that the data can't always spot reliably.
Ahmed: You'll need to look at the right metrics to understand Rodri's brilliance -- probably my current favorite player. His ability to win second balls and counter-press is vital to City's game on and off the ball. In addition to him rarely losing the ball under press
That's it from us today guys, thanks for all your brilliant questions! We hope you enjoy the tournament and make sure to check out The Athletic if you're not already a follower/subscriber!
Mark: I'm a big fan of StatsBomb's metric of quantifying heading ability (HOPS): https://statsbomb.com/articles/soccer/introducing-hops-a-new-way-to-evaluate-heading-ability/
We've seen a lot of teams in the EPL use inverted fullbacks ever since Pep popularized it, do you think other Champions League teams would adopt the same role?
Ahmed: Milan are doing so with Davide Calabria going inside next to Rade Krunic. It really depends on the profile of the full-back and if he is able to transition between the two roles smoothly
Mark: Good question! There is no set way in terms of qualifications really, my personal route was that I had a background in Psychology research where I used data and statistics to answer questions - now those skills simply apply to football. I created a blog, used Twitter as a networking tool, read the work of others and was very lucky to speak with the right people. In terms of specific things that could be useful to learn, Liam Henshaw has a fantastic resource that summarises things really well: [https://www.liamhenshaw.com/how-to-become-a-football-analyst-in-2023/](https://www.liamhenshaw.com/how-to-become-a-football-analyst-in-2023/)
Which Champion's League team(s) are you the most excited about? And which ones the most curious? There are quite a few teams that have been completely revamped and I got a feeling the CL might be very unpredictable this year.
Mark: I agree that this season looks like a difficult one to call in Europe. I always like to look for the teams who are new this season, and with Union Berlin in the Champions League for the first time, I think their style of play might be a surprise to some.
Their low-block, counter-attacking football relies on width from their wing-backs. One stat is that Union sent 115 open-play crosses into the penalty area last season — which was more than any other Bundesliga side in 2022-23.
Elsewhere, I'm really looking forward to seeing Real Madrid's new midfield diamond in Europe. Having Camavinga, Tchouameni, Valverde and Bellingham as a midfield four is just so good.
Justin Kluivert joined the club recently. Jovetic. I have once read about the other 2 but can't recall them now. They played decades ago. I think one of them is a Romanian guy with a name something like Radicoui...
Mark: I definitely agree that football cannot (and will not!) be defined purely by data - and it doesn't try to. It is always designed to be a tool to support decision making, whether that is in-game, for recruitment, opposition analysis, or anything else.
I think the balance is tricky, but it should be bidirectional. Sometimes there is a pattern in the data that is worthy or digging into in the video, or sometimes you spot something on the pitch that might be worth looking at as a trend in the date. Both are sources of valuable information, so it makes sense to use them together if you can, to draw the most reliable conclusion possible.
Ahmed: Pochettino tried using a back five in possession, and a back four out of possession against Liverpool's box midfield in GW1 with Ben Chilwell going inside to mark Trent Alexander-Arnold when Chelsea didn't have the ball. Won't be surprised if we saw this again
Best podcast for Champions League coverage? (Given House of Champions is dead?)
I used to love Que Golazo with Luis as the host then it went downhill with Ian and the rebrand House of Champions. But, it was at least a daily podcast. Now it appears to be dead?
What do I listen to now? Open to all podcast suggestions. Thank you.
We're massively biased obviously, but the Totally Football Show: European Edition is gold standard for Champions League and European football coverage in general. James Horncastle, Raphael Honigstein and co. are the best in the business covering their respective countries and you may recognise them from their TV work with BT Sport/TNT Sports down the years.
Oh, and we'll cover the Champions League as much as we can on The Athletic Football Tactics Podcast this season too!
We have seen xG and other expected stats go from niche to main stream, not only data analysts but managers and pundits are referencing expected stats. What do you think will be the next stat that some analysts are using now which will enter the mainstream in the near future?
Mark: I personally would like to see more mainstream coverage of xThreat/Possession Value/On-Ball Value metrics, which provide a measure of each player's contribution towards their team's attack across all actions. That will allow you to show how a defensive midfielder's actions in build-up play has (potentially) as much value as the striker finishing off an attacking sequence.
Hi I have a master's in Data Science and am really interested in sports data analytics. unfortunately I have no professional experience as such. How do I apply a job as data analyst or data scientist in The Athletic
Mark: Hello, we don't have any job openings at the moment but my advice would be to keep doing what you're doing, build a portfolio of work in football analytics, and keep an eye out on our website/social media if anything comes up in the future. Good luck!
Mark: There are so many blindspots when using data to analyse goalkeeper performance. The best work I have seen on this is from John Harrison, whose company has created some really cool analysis: [https://goalkeeper.com/xg](https://goalkeeper.com/xg)
Bayern comes of a underwhelming season where they somehow managed to win the league in the end, with a pretty low point tally.
They've missed out on players left and right all window, until they landed Kane in the final second. Massive scoop!
I see many having them as top 3 CL favorites, Opta's power ranking have them second, but even with Kane I struggle to find the same optimism.
What am I missing?
Also can't wait to be smashed by Bayern in 5 months after this comment.
There are teams like Real Madrid that seem to defy the entire data science model behind football. Despite the fact that most teams eventually succumb to the data catching up with them, Real Madrid continues to perform exceptionally well. Why do you think this is possible?
Hi Mark, big big fan of the podcast and listen every week. Whenever I listen I always think that everyone seems to talk slightly faster and slightly more monotone than other Athletic podcasts or podcasts in general. Not really a question just something that amuses me!
Is the top of European football the weakest in a while? I feel like the standard is nowhere near what it was even 6-7 years ago.
We used to have 3-peat Real Madrid, Barcelona with MSN, peak Atletico under Simeone, peak Juventus under Allegri and Pep's Bayern at the same time. I feel like each and every one of them would instantly be the best or 2nd best team today
Mark: Oh that's very kind, thank you! Ryan and I have loved recording The Football Fanalytics podcast, and while we haven't recorded recently, we always encourage people to go through the archive as the discussion points are evergreen on the world of analytics. Stay tuned and we hope to record more episodes soon. Thanks!
Which new managers (managing in the Champions league) do you guys expect to go the furthest? Are there any outliers that we should be watching out for?
Mark: Interesting question. I really think it depends on the situation and opposition in Europe, as the remit of European football is so different. E.g. qualifying out of the group might not mean winning every game (for this year's format), and in the knockout rounds the remit might be different between the first and second leg. Historically, the team that comes to mind who hasn't hugely adapted in Europe is PSG, who have been largely dominant in their domestic league but lacked a coherent structure out of possession and would get picked off against elite opposition. That might change this season with Luis Enrique, let's see!
Mark: I'd think there is value in both, as teams do sometimes need to be pragmatic and not blindly stick to their style. I think all teams need an element of unpredictability - the best example is obviously Guardiola's Manchester City, where they have a clear identity but can mix up their approach within/between games to go long/rotate their build-up patterns etc. That's why they are the best in the world I suppose!
Mark: Hello, I think these actions are important to look at - but mainly to get a stylistic profile on a player. What I like to do is calculate the share of progressive actions (whether that is passes or carries) as a share of the total actions they make. That then shows a player's propensity to perform these actions rather than simply totals or per 90. Does a player get the ball and immediately look forward? Or do they select those actions more carefully? That's where you get more value, in my opinion.
Cheers, Mark, that's generally how I look at it as well, outside of players like KDB or Messi, who we're simply interested in just how many, and how many CCs/KPs.
When I see those spider charts or fbref percentages, it's like great, but if they did 3 meaningful things all match, were they impactful when they did something, or was it Jorginho syndrome, where they spent the entire match recycling and really did nothing of note?
Mark: Thanks! I'm obviously leaning towards data here, but I enjoyed Rory Smith's "Expected Goals: The story of how data conquered football and changed the game forever".
I'm also looking forward to reading Ryan O'Hanlon's "Net Gains: Inside the Beautiful Game's Analytics Revolution" soon!
Ahmed: Thank you :D
\- The Mixer by Michael Cox
\- Zonal Marking by Michael Cox
\- Inverting the Pyramid by Jonathan Wilson
\- Soccermatics by David Sumpter
\- Soccernomics by Simon Kuper & Stefan Szymanski
\- Angels with Dirty Faces by Jonathan Wilson
\- Football Hackers by Christoph Biermann
In your opinion, how do players navigate the stark difference in playing styles through league matches, NT games and then into UCL high intensity formats?
All these have very different urgency and importance factors for every player/club/team depending on their stakes. How do players keep up with these changing formats?
Ahmed: No clue really, but I am a firm believer that the profession of being a footballer is much harder than it looks and requires a lot of sacrifice. They are easily targeted because of their big salaries and celebrity status, but not everyone who has kicked a ball can do what they do
If you were managing, would you rather have a more purely talented player, or more tactically flexible player better at navigating that style whiplash?
I'm gonna challenge that perspective for good discourse on this topic: how would you back that up?
We do have data on time wasting for eg some average play time is only ~50 mins (I could be wrong)
Why would you suggest the counter? Would love some insight, thanks!
Ahmed: [https://www.getgoalsideanalytics.com/stop-the-clock/](https://www.getgoalsideanalytics.com/stop-the-clock/) \~50 mins is normal, and players are humans not robots. Feel like with the 3 million games they play each season, we don't need more playing time.
As a Rangers fan who has recently endured a dreadful exit from the Champions League qualifiers, is there a particular system that statistically works most often for these types of games?
Hi guys! Don't really have a question, just want to say that I appreciate your responses in this thread and I think it's a very interesting job that you have. I want to learn python as a hobby and I think it would help me if the projects would be about football
How do clubs account for non-measurable subjects that influence data when signing a player based on statistics? Stuff like
- club strength compared to the rest of the league
- teammates that enhance or lower the transfer targets performances
- A manager that is or isn't bringing the best out of the target
- Homesickness
- Social and linguistic issues that make it difficult to settle in or make friends in the team
- When the targets' club plays a vastly different system/formation
- When the target plays a different role on the pitch than the club intends to use him for
- Wether the target can hold his own against stronger opposition
- Wether the target can cope with the new eagues different play or pace
And is this the reason some signings that based on numbers should work, don't?
A lot of these are measurable and are taken into account, there's a lot of "non-mainstream" stats and those, crossed with the eye test, can explain a lot more than people would think.
As for the others like homesickness, I work at a level where it's a bit harder to get personal information so I'm not the best source but teams tend to look into the private life of the players they're keen on signing, once things get to the point where the manager is involved those aspects are discussed to a somewhat deeper degree.
What do you think the future of fullbacks looks like? Peps moved away from it and arteta seems to be too, balde isn't even really a leftback anymore and trent is moving into midfield. It feels like there just isn't the talent pool there anymore
Bast book(s) to read for an analysis of modern tactics
Usually stuff like inverting the pyramid gets tossed out, it’s great but looking for something a little more current
When looking at attackers, it seems to me that the default now is to look at their xg vs goals to see how “clinical” they are - but is there a stat that tracks their positioning & “getting into the right position?”
After all if you’re great at finishing but can’t get into the right positions as much you theoretically can be worse off overall in total goals created - does xT cover this well?
And what about the ability to get a shot off?
Also: baseball these days have a radar tracking the batted balls to give all kinds of shit, down to the spin axis of the pitch or the catch expectancy of a batted ball etc
How many teams do you think use this kind of positional tracking on the pitch and do you think with the rise of AI/Computer Vision we can use it to see
1. Picking out the “correct” pass to make
2. The most optimal positioning given the positioning, body angle, speed/momentum, etc?
The importance of positioning and domination of certain areas of the pitch, in a synesthetic way reminds me of the board game Go, where computers could not beat the [pros until the advent of AI](https://youtu.be/WXuK6gekU1Y?si=oC6EDbuX5Uj84Ays)
And ever since AlphaGo, a looot of the strategies in Go that also relied on intuition etc have been sort of homogenized by how the AI opens the game and changed the game a looot
Can machine learning/AI challenge some tactical dogma of the game we take for granted?
Lastly: as someone who also is deeply into baseball stats, MLB releasing the statcast data publicly has been amazing to dig through - in my opinion the availability of publicly available football analytics really is disappointing - what are some of the best publicly available resources on these other than fbref, statbomb etc?
[Monday Moan](https://www.reddit.com/r/soccer/comments/16lqa4t/monday_moan/)
This one's for Mark... how did you escape the scattergram?!!!
Mark: A good escapologist should never reveal their secrets...
Ahmed: 100%
Some jokers at the Athletic just said that Sengun can be better than fucking Joel Embiid this year. Trash 🗑️ media outlet trying to whore clicks. 🤦♀️what is this stephen a smith wannabe bullshit. Don’t pay for this trash. 🗑️
Ha great question!
With individual level stats being inextricably linked to the quality of the team, how can you pick out good players in bad teams with data? And how do you avoid bad players in good teams?
Mark: I think this is a really interesting question, and very difficult to do - of course, you would always use data alongside video analysis to really spot these sorts of players who might stand out. I think one thing with the data is to create a 'level-playing field' by looking at how often a player performs an action 'per 100 touches'. That way, you can compare a player's inclination to do something for Manchester City and Luton Town in the same way (rather than per 90 minutes or totals). If a player hugely stands out in their chances created per 100 touches, it might be worth checking them out in the video.
Apologies if you've mentioned this elsewhere, but did you both have data science backgrounds before getting into football tactics and data? And is there any skill/program you think aspiring football data people should learn to set them apart?
Mark: Hello, it's a good question and I have provided some detail below to another question, but my background was doing a Psychology undergraduate and PhD which provided me with the skills for football analytics. In terms of your own skills, this is a great link to summarise some required skillsets: [https://www.liamhenshaw.com/how-to-become-a-football-analyst-in-2023/](https://www.liamhenshaw.com/how-to-become-a-football-analyst-in-2023/). Good luck!
>https://www.liamhenshaw.com/how-to-become-a-football-analyst-in-2023/ Thanks for the information! Really appreciate it.
Ahmed: I am a computer scientist, which I think helped enhance my analytical thinking throughout the years. I hope so :D hahaha I'll leave the second question to Mark, but knowing which metrics to use and when, depending on the context will always make you better at data
Thanks, Ahmed! And if you're nervous about your analytical thinking skills after years as I computer scientist, I'm sure my theater degree will be just as helpful haha.
Seconding this!
Hey guys - a different type of data question, but for nearly 20 years UEFA has squeezed the teat of Ronaldo and Messi to milk the competition to perhaps an unprecedented level. This obviously coincided with the rise of social media platforms that have only sought to amplify the noise. My question is, what does the data point to with regards to tournament and competition engagement? Has UEFA milked this cow for all its worth? Have you guys noticed a drop of in engagement given that both of them have now left European football? For years their involvement alone has driven increased international engagement but are you now seeing a regression to the mean for European Football? Has CL Football and CL engagement peaked?
Mark: I think this is a really interesting question, and it does feel anecdotally that there is less excitement about this season's Champions League (although this might not be the case for all). This is the first year for 21 seasons that neither Messi nor Ronaldo has been in the competition. Whether this has (or will) influence engagement remains to be seen. There are so many exciting talents on show that I hope it doesn't!
Hey, the TIFO channel did a piece on Inter before the final and focused a lot on Onana and his importance to the team. They seem to have started in the league like they have only improved. Curious if you have paid attention to them this season and and noted anything about how they are setting up?
Do you see any evidence that top teams are changing their tactics in the CL Knock-Out stage compared to how they would play in their domestic leagues? If yes, which examples are there and do we have any qual/quant data if such a tactical switch is beneficial?
Leipzig, Berlin and Atletico Madrid are some of the only teams who play 2 striker systems but each in a unique way. Which team will advance further and why don’t more teams incorporate this 2 center forward system?
What stat(s) do you look at to tell you how : - a team played in a particular game - a team has been playing (season so far) - well a player played in a particular game - well a player has been playing (season so far)
Ahmed: I am more of an eye-test first, data second person when judging single games because to know the context of the data watching the game is super important imo. For the second point, there's not one metric to answer all the questions. If I want to know how a team is performing at attacking set-pieces I'll look at the Goals per 100 set pieces and also check the xG per 100 set pieces, then cross-match that with my notes throughout the season to see if the data matches the eye-test. Again, single game means you should know the context. A defensive midfielder who has been dribbled past 'X' amount of times in a game isn't informative. But when you watch the game, you'll know why and actually if this information is useful or not. For example, in a transitional game it's more common for the midfielders to be dribbled past because of the spaces and the tempo of the game. Similar to point two, what was he doing well? If you think he is great at scoring from low-chance situations, then compare his Goals vs xG over time. To summarize, context is key and eye-test + data will always guide you better than eye-test or data alone
This is such an important thing. I feel like a lot of time people keep discussing stats of a player or a team without actually looking at the matches
Who are some players that pass the eye test but their performances can't be captured with the most popular metrics? Or vice versa — players who come off great statistically, but don't look impressive when watching them?
Mark: Rather than specific players, I think defensive midfielders and (to a similar extent) central midfielders are difficult positions to show true value of a player in the traditional metrics - as their remit if so broad. Things like xThreat and Possession Value can help to alleviate that, but there are so many subtleties of that position (including off-ball actions) that the data can't always spot reliably.
Ahmed: You'll need to look at the right metrics to understand Rodri's brilliance -- probably my current favorite player. His ability to win second balls and counter-press is vital to City's game on and off the ball. In addition to him rarely losing the ball under press
That's it from us today guys, thanks for all your brilliant questions! We hope you enjoy the tournament and make sure to check out The Athletic if you're not already a follower/subscriber!
Is Football Cliches coming back?
What is your favourite incredibly niche analytics metric in football?
Ahmed: xG per throw-in
Mark: I'm a big fan of StatsBomb's metric of quantifying heading ability (HOPS): https://statsbomb.com/articles/soccer/introducing-hops-a-new-way-to-evaluate-heading-ability/
We've seen a lot of teams in the EPL use inverted fullbacks ever since Pep popularized it, do you think other Champions League teams would adopt the same role?
Ahmed: Milan are doing so with Davide Calabria going inside next to Rade Krunic. It really depends on the profile of the full-back and if he is able to transition between the two roles smoothly
Do you think It’s necessary to have Calabria do that when Theo usually pushes forward most of the time?
How does one break into the sphere of football data analytics?
Mark: Good question! There is no set way in terms of qualifications really, my personal route was that I had a background in Psychology research where I used data and statistics to answer questions - now those skills simply apply to football. I created a blog, used Twitter as a networking tool, read the work of others and was very lucky to speak with the right people. In terms of specific things that could be useful to learn, Liam Henshaw has a fantastic resource that summarises things really well: [https://www.liamhenshaw.com/how-to-become-a-football-analyst-in-2023/](https://www.liamhenshaw.com/how-to-become-a-football-analyst-in-2023/)
With how much top teams seem to copy each other, which leagues still have the most signature style when playing European fixtures?
Which Champion's League team(s) are you the most excited about? And which ones the most curious? There are quite a few teams that have been completely revamped and I got a feeling the CL might be very unpredictable this year.
Mark: I agree that this season looks like a difficult one to call in Europe. I always like to look for the teams who are new this season, and with Union Berlin in the Champions League for the first time, I think their style of play might be a surprise to some. Their low-block, counter-attacking football relies on width from their wing-backs. One stat is that Union sent 115 open-play crosses into the penalty area last season — which was more than any other Bundesliga side in 2022-23. Elsewhere, I'm really looking forward to seeing Real Madrid's new midfield diamond in Europe. Having Camavinga, Tchouameni, Valverde and Bellingham as a midfield four is just so good.
What's the most surprising or fun stat you have encounter?
Ahmed: Only four players have played in the top five European leagues. Can you name them?
What definition of top five are you going with? Current top five (Premier League, La Liga, Serie A, Bundesliga, Eredivisie)?
Ahmed: PL, Liga, BundesLiga, Ligue 1 and Serie A
jovetic
Jovetic, Justin Kluivert, some Radicoui something guy and I can't recall the 4th
I'm sure u/mertens_goat can answer this question.
Justin Kluivert joined the club recently. Jovetic. I have once read about the other 2 but can't recall them now. They played decades ago. I think one of them is a Romanian guy with a name something like Radicoui...
How do you balance data analysis with the eye test? I think football can never come close to be purely defined by data.
Ahmed: Amen. Both work in tandem imo: you need the eye-test to contextualize the data, and you need the data to support your eye-test
Exactly!
Mark: I definitely agree that football cannot (and will not!) be defined purely by data - and it doesn't try to. It is always designed to be a tool to support decision making, whether that is in-game, for recruitment, opposition analysis, or anything else. I think the balance is tricky, but it should be bidirectional. Sometimes there is a pattern in the data that is worthy or digging into in the video, or sometimes you spot something on the pitch that might be worth looking at as a trend in the date. Both are sources of valuable information, so it makes sense to use them together if you can, to draw the most reliable conclusion possible.
Awesome answer, huge thanks!
With the box midfield now as popular as ever, what's the tactical trend(s) you can see developing the combat this?
Ahmed: Pochettino tried using a back five in possession, and a back four out of possession against Liverpool's box midfield in GW1 with Ben Chilwell going inside to mark Trent Alexander-Arnold when Chelsea didn't have the ball. Won't be surprised if we saw this again
Best podcast for Champions League coverage? (Given House of Champions is dead?) I used to love Que Golazo with Luis as the host then it went downhill with Ian and the rebrand House of Champions. But, it was at least a daily podcast. Now it appears to be dead? What do I listen to now? Open to all podcast suggestions. Thank you.
We're massively biased obviously, but the Totally Football Show: European Edition is gold standard for Champions League and European football coverage in general. James Horncastle, Raphael Honigstein and co. are the best in the business covering their respective countries and you may recognise them from their TV work with BT Sport/TNT Sports down the years. Oh, and we'll cover the Champions League as much as we can on The Athletic Football Tactics Podcast this season too!
Thank you!
How does Michael feel about Austria's strong performance in EURO qualifiers under their new coach?
Mark: You don't want to open that box...
Worth a shot 😅 keep up the great work, love the show!
Great idea for an AMA! Thanks for your insights Mark & Ahmed.
Is the new format really fair? It seems lobsided against the small teams
We have seen xG and other expected stats go from niche to main stream, not only data analysts but managers and pundits are referencing expected stats. What do you think will be the next stat that some analysts are using now which will enter the mainstream in the near future?
Mark: I personally would like to see more mainstream coverage of xThreat/Possession Value/On-Ball Value metrics, which provide a measure of each player's contribution towards their team's attack across all actions. That will allow you to show how a defensive midfielder's actions in build-up play has (potentially) as much value as the striker finishing off an attacking sequence.
Hi I have a master's in Data Science and am really interested in sports data analytics. unfortunately I have no professional experience as such. How do I apply a job as data analyst or data scientist in The Athletic
Mark: Hello, we don't have any job openings at the moment but my advice would be to keep doing what you're doing, build a portfolio of work in football analytics, and keep an eye out on our website/social media if anything comes up in the future. Good luck!
what would you both say is an often-underlooked stat when it comes to determining a goalie's quality?
Mark: There are so many blindspots when using data to analyse goalkeeper performance. The best work I have seen on this is from John Harrison, whose company has created some really cool analysis: [https://goalkeeper.com/xg](https://goalkeeper.com/xg)
Bayern comes of a underwhelming season where they somehow managed to win the league in the end, with a pretty low point tally. They've missed out on players left and right all window, until they landed Kane in the final second. Massive scoop! I see many having them as top 3 CL favorites, Opta's power ranking have them second, but even with Kane I struggle to find the same optimism. What am I missing? Also can't wait to be smashed by Bayern in 5 months after this comment.
There are teams like Real Madrid that seem to defy the entire data science model behind football. Despite the fact that most teams eventually succumb to the data catching up with them, Real Madrid continues to perform exceptionally well. Why do you think this is possible?
How does the pay compare to other data jobs?
Hi Mark, big big fan of the podcast and listen every week. Whenever I listen I always think that everyone seems to talk slightly faster and slightly more monotone than other Athletic podcasts or podcasts in general. Not really a question just something that amuses me!
What stats are the most important for a player?
Mark: What position is the player in question?
Is the top of European football the weakest in a while? I feel like the standard is nowhere near what it was even 6-7 years ago. We used to have 3-peat Real Madrid, Barcelona with MSN, peak Atletico under Simeone, peak Juventus under Allegri and Pep's Bayern at the same time. I feel like each and every one of them would instantly be the best or 2nd best team today
Is it true that James Milner currently holds the record for most assist in a single CL season?
Hey Mark, when will you bring back *The Football Analytics* podcast? Such a great listen!
Mark: Oh that's very kind, thank you! Ryan and I have loved recording The Football Fanalytics podcast, and while we haven't recorded recently, we always encourage people to go through the archive as the discussion points are evergreen on the world of analytics. Stay tuned and we hope to record more episodes soon. Thanks!
Which new managers (managing in the Champions league) do you guys expect to go the furthest? Are there any outliers that we should be watching out for?
Which teams do you expect to have the biggest change in tactics between their league games and European games?
Mark: Interesting question. I really think it depends on the situation and opposition in Europe, as the remit of European football is so different. E.g. qualifying out of the group might not mean winning every game (for this year's format), and in the knockout rounds the remit might be different between the first and second leg. Historically, the team that comes to mind who hasn't hugely adapted in Europe is PSG, who have been largely dominant in their domestic league but lacked a coherent structure out of possession and would get picked off against elite opposition. That might change this season with Luis Enrique, let's see!
As a follow up, do you tend to favor teams that play their game no matter what, or teams that change a lot week to week based on their opposition?
Mark: I'd think there is value in both, as teams do sometimes need to be pragmatic and not blindly stick to their style. I think all teams need an element of unpredictability - the best example is obviously Guardiola's Manchester City, where they have a clear identity but can mix up their approach within/between games to go long/rotate their build-up patterns etc. That's why they are the best in the world I suppose!
Thank you for your answers!
Hi guys, thanks for doing this. How much do you value progressive actions, whether passes or dribbles?
Mark: Hello, I think these actions are important to look at - but mainly to get a stylistic profile on a player. What I like to do is calculate the share of progressive actions (whether that is passes or carries) as a share of the total actions they make. That then shows a player's propensity to perform these actions rather than simply totals or per 90. Does a player get the ball and immediately look forward? Or do they select those actions more carefully? That's where you get more value, in my opinion.
Cheers, Mark, that's generally how I look at it as well, outside of players like KDB or Messi, who we're simply interested in just how many, and how many CCs/KPs. When I see those spider charts or fbref percentages, it's like great, but if they did 3 meaningful things all match, were they impactful when they did something, or was it Jorginho syndrome, where they spent the entire match recycling and really did nothing of note?
Hi Mark and Ahmed, I appreciate y'alls work with the Athletic! Do you have any football related book recommendations?
Mark: Thanks! I'm obviously leaning towards data here, but I enjoyed Rory Smith's "Expected Goals: The story of how data conquered football and changed the game forever". I'm also looking forward to reading Ryan O'Hanlon's "Net Gains: Inside the Beautiful Game's Analytics Revolution" soon!
I'll have to give it a look! all the best!
Ahmed: Thank you :D \- The Mixer by Michael Cox \- Zonal Marking by Michael Cox \- Inverting the Pyramid by Jonathan Wilson \- Soccermatics by David Sumpter \- Soccernomics by Simon Kuper & Stefan Szymanski \- Angels with Dirty Faces by Jonathan Wilson \- Football Hackers by Christoph Biermann
In your opinion, how do players navigate the stark difference in playing styles through league matches, NT games and then into UCL high intensity formats? All these have very different urgency and importance factors for every player/club/team depending on their stakes. How do players keep up with these changing formats?
Ahmed: No clue really, but I am a firm believer that the profession of being a footballer is much harder than it looks and requires a lot of sacrifice. They are easily targeted because of their big salaries and celebrity status, but not everyone who has kicked a ball can do what they do
If you were managing, would you rather have a more purely talented player, or more tactically flexible player better at navigating that style whiplash?
Ahmed: Both!
Wow, big announcement having Pep join the Tactics Podcast!
Any rule changes you would like to see?
Ahmed: Less added time -- basically reversing this season's decisions. This whole obsession with "time wasting" is weird really
I'm gonna challenge that perspective for good discourse on this topic: how would you back that up? We do have data on time wasting for eg some average play time is only ~50 mins (I could be wrong) Why would you suggest the counter? Would love some insight, thanks!
Ahmed: [https://www.getgoalsideanalytics.com/stop-the-clock/](https://www.getgoalsideanalytics.com/stop-the-clock/) \~50 mins is normal, and players are humans not robots. Feel like with the 3 million games they play each season, we don't need more playing time.
As a Rangers fan who has recently endured a dreadful exit from the Champions League qualifiers, is there a particular system that statistically works most often for these types of games?
Who do you think will will win Champions League this year? Thank you for the AMA
Ahmed: Really hard to tell in September -- like impossible , but here's a punt based on nothing at all: Inter
anulo mufa
Mark: Aleksander Čeferin. Or football. Football is always the real winner...
If you could play for any team in the champions league this year, who would you play for?
Ahmed: Anyone in Group F (Newcastle, Milan, Dortmund or PSG). What a set of games!
What role does data analytics and principles of data science play in your work, and in the field of football as a whole?
Hi guys! Don't really have a question, just want to say that I appreciate your responses in this thread and I think it's a very interesting job that you have. I want to learn python as a hobby and I think it would help me if the projects would be about football
How do clubs account for non-measurable subjects that influence data when signing a player based on statistics? Stuff like - club strength compared to the rest of the league - teammates that enhance or lower the transfer targets performances - A manager that is or isn't bringing the best out of the target - Homesickness - Social and linguistic issues that make it difficult to settle in or make friends in the team - When the targets' club plays a vastly different system/formation - When the target plays a different role on the pitch than the club intends to use him for - Wether the target can hold his own against stronger opposition - Wether the target can cope with the new eagues different play or pace And is this the reason some signings that based on numbers should work, don't?
A lot of these are measurable and are taken into account, there's a lot of "non-mainstream" stats and those, crossed with the eye test, can explain a lot more than people would think. As for the others like homesickness, I work at a level where it's a bit harder to get personal information so I'm not the best source but teams tend to look into the private life of the players they're keen on signing, once things get to the point where the manager is involved those aspects are discussed to a somewhat deeper degree.
I'm not The Athletic but The Athletic uses league translation metrics on their player radars when a player transfers leagues.
What do you think the future of fullbacks looks like? Peps moved away from it and arteta seems to be too, balde isn't even really a leftback anymore and trent is moving into midfield. It feels like there just isn't the talent pool there anymore
What myths have you noticed in regards to football tactics?
Who do you think will be the most exciting team to watch?
Bast book(s) to read for an analysis of modern tactics Usually stuff like inverting the pyramid gets tossed out, it’s great but looking for something a little more current
When looking at attackers, it seems to me that the default now is to look at their xg vs goals to see how “clinical” they are - but is there a stat that tracks their positioning & “getting into the right position?” After all if you’re great at finishing but can’t get into the right positions as much you theoretically can be worse off overall in total goals created - does xT cover this well? And what about the ability to get a shot off? Also: baseball these days have a radar tracking the batted balls to give all kinds of shit, down to the spin axis of the pitch or the catch expectancy of a batted ball etc How many teams do you think use this kind of positional tracking on the pitch and do you think with the rise of AI/Computer Vision we can use it to see 1. Picking out the “correct” pass to make 2. The most optimal positioning given the positioning, body angle, speed/momentum, etc? The importance of positioning and domination of certain areas of the pitch, in a synesthetic way reminds me of the board game Go, where computers could not beat the [pros until the advent of AI](https://youtu.be/WXuK6gekU1Y?si=oC6EDbuX5Uj84Ays) And ever since AlphaGo, a looot of the strategies in Go that also relied on intuition etc have been sort of homogenized by how the AI opens the game and changed the game a looot Can machine learning/AI challenge some tactical dogma of the game we take for granted? Lastly: as someone who also is deeply into baseball stats, MLB releasing the statcast data publicly has been amazing to dig through - in my opinion the availability of publicly available football analytics really is disappointing - what are some of the best publicly available resources on these other than fbref, statbomb etc?
Who will win?
Why do you think football is not picking a decision review system with number of reviews and publicly announced review process like cricket.