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you should butter to use SPSS

What differentiates this from the cartesian plane?

Hello! I want to extract all touches of a certain player from a video of a full match automatically, can we achieve that with your approach? Thank you

thanks much for this analysis: but my very concern and desire is that i want to design a program that will fetch a particular or current seasons games, match played (Mp), goals scored, goals conceded for both home (Hm) and away(Aw) teams, each of which should automatically run in a respective input unit for further analysis. the input units looks like this; #TeamA Hm = str(input('Home: ')) Mpa = int(input('enter Mp:')) HXa = int(input('Scored: ')) HXb = int(input('Conceded: ')) #TeamB Aw = str(input('Away: ')) Mpb = int(input('enter Mp:')) AYa = int(input('Scored: ')) AYb = int(input('Conceded: ')) #How can you go about helping me please?

I'm here because Chris Pajak sent me.

Great Video!

I want your gmail

I am looking for the PSG hackerton site any links?????

Raj Chohan reckons he can do your job even better than you do

Hi! nice video. I'm having problems to import the data in json file it seems that needs to be payed. by any where can I see the data structure to see if I can build it? or any other source?

Can't believe this was 4 years ago. This was such a productive and education friendly group. Incredible what you all gave to the community. Thank you.

Do you have course data anaylitcs soccer online? i need course! Thanks!

Awesome videos!!

I've tried replicating the code available in the GitHub, the exact way the code was written in the notebook file and in the Pdf available, but I encountered some problems along the way. I believe the 'Highlight Text' library has changed a little bit over the course of time since this video came out. So I struggled a little bit trying to solve it, and to anyone else who has had this problem: I encountered problems within this line: ssn_start = df[df.team == team].season_id.iloc[0] ssn_end = df[df.team == team].season_id.iloc[-1] ssn_start = str(ssn_start)+"/"+str(ssn_start+1) ssn_end = str(ssn_end)+"/"+str(ssn_end+1) s = "{}'s goal difference from {} to <{}> " >>> htext.fig_htext(s.format(team,ssn_start,ssn_end),0.15,0.99,highlight_colors=[primary], highlight_weights=["bold"],string_weight="bold",fontsize=22, fontfamily=title_font,color=text_color) The solution I found was writing it like this: ssn_start = df[df.team == team].season_id.iloc[0] ssn_end = df[df.team == team].season_id.iloc[-1] ssn_start = str(ssn_start)+"/"+str(ssn_start+1) ssn_end = str(ssn_end)+"/"+str(ssn_end+1) s = "{}'s goal difference from {} to <{}> " >>> highlight_text.fig_text(0.15, 0.99, s.format(team, ssn_start, ssn_end), highlight_textprops=[{"color": primary}], fontsize=22, fontfamily=title_font, color=text_color) Another problem I encountered along the way was the instalation of the Fonts, after instaling them I had to go to the Folder where is located the cache of Matplotlib and delete the font file, after doing that i relaunched the code and it worked fine! Thank you Peter for sharing this lovely Graph, Thank you David for posting the Soccermatics course online I've been developing a love for Data Science and I've been enjoying a lot helping through your classes.

Thanks for this video. It’s pretty good

Hello, I have a question about the Poisson model you've presented. You discuss variables such as attacking power and defensive power. I've developed a model in Excel (yes, I don't know how to program in Python or R), and I've divided it into "goals scored by the home team" and "goals scored by the away team". Then, I've further divided both groups into 2 subgroups: "goals scored by the home team and conceded by the away team" and "goals scored by the away team and conceded by the home team". Within each subgroup, I've included both the average goals scored by the home team at home (or when few games have been played, the expected goals), and the average goals scored by teams at home in the league (to capture the home team advantage), and I compare them with the average goals conceded by the away team, both overall of away teams in the league (to gauge the disadvantage or advantage of playing away for the opposing team). I then do the same with the goals scored by the away team and conceded by the home team. My question is, do you think this is a good model? The method for obtaining the expected goals for both teams arises from dividing the average goals scored by the home team by the average goals scored by home teams in the league, and multiplying the league's average goals by that result, and the result of dividing the average goals conceded away by the away team by the average goals conceded by away teams in the league. Logically, I apply the same formula for the away team. Do you think this model is correct? Is it more accurate in terms of the difference between playing at home or playing away? Should I capture the difference only with the difference in scoring at home and away and conceding at home and away? By the way, I love your videos, very well-utilized statistics and econometrics!

Awesome video. You're so good at this. I love how you essentially touched on sanity checking too at the end.

Really great video thank you❤

loved this. brilliant watch!

This guy created voronoi map with python: ruclips.net/video/t0TJll06_hE/видео.html

13:16 😂😂 seriously at 10 years he thought of doing AI in football interested of being a football player 🥴🥴

Good luck with the search William! Klopp cant be replaced but we all know the new manager has to be someone who understands the club and philosophy. No Jose ok

Bro you better find the best manager now😂😢

you miss the french people you dont make the french traduction i dislike

hello Error in command 'gzfile(file, "wb")': cannot delete additional: Warning message: In the command 'gzfile(file, "wb")': unable to delete compressed file '.RDataTmp', probable cause 'Permission denied' Warning message: In the 'file.remove(outfile)' command: cannot delete file '.RDataTmp', reason 'No such file or directory' >this information is displayed when opening R

This is brilliant!

Hello Im a student and Im going to do a project in school and want to do a soccer tracking system. Can u help me, suggest which tracker i should use. Something where`s easy to code on it.

How to make tracking data?

How can i get the presentation plzzzz

About 3 years late to the game, but thanks Suds! This was amazing.

I have a question when you want to volunteer for a club how do you know they have the tools for you to do data analysis I mean if the pay a platform or company to gather the data

Thank you for this Sir.

ruclips.net/video/oOAnERLiN5U/видео.html, How do I do this on live match?

I keep receiving the error - ValueError: axis must be fewer than the number of dimensions (1)-- When I run -- tracking_home,tracking_away,events = mio.to_single_playing_direction(tracking_home,tracking_away,events) -- I'm not sure what this means or how to fix it.

Thanks amazing professor ❤

I was thinking, if using distance as log and angle as cos, wouldn't be better. Then you could make a linear regresion. Also, you would have: 0 < xG < 1 | 1 < log(d+1) < 2 | -1 < cosø < 1 This suposing that a field has 99 m, on average, and you cannot shoot over 180°

where to get the tracking data of champions league or any current matches . any one ??

This is amazing, i want to learn more about it, never coded in my life, would this work with the videos of my kids soccer U13 games? I've been looking for something to track data like this to help the coaches with the team to preform better. Thank you again.

Let me see the best channel ever!

how did he make this visualizations?

Should this also be broken down by the stronger foot of the player getting into the position?

I just wanted to share something here - if you look at the shot angle function. You'll see an initial descrease in scoring probability that david attributes to being an anomaly when in fact if you think intuitively about this and i have verified with data. The likelyhood is that despite the angle being low the Distance is also probably low too which possesses significant explanatory power and hence the higher goal probability is due to this rather than any direct effect of shot angle on goal scoring probability. Always check for Multicolinearity because i bet there is some interaction here. Are shots with lower angles typically from lower distances?

I have very, very basic experience with Python, but I adore football and am at that point in my career where I am seeking change. I'm 32 years old so hopefully not too old to learn and to be able to one day land a job in football data analytics! This video really was great and made me very excited to learn python.

I am unable to get the data from the link provided

It's awesome,i'm just wondering how can you track an event each 40 millisecondes, how does Metrica Sports does it ? do they manually track it ?

This guy talks like he has an advanced degree from MIT😉

Ashwin, I’m a consultant now but I had the same problem as you. When you start stuttering, pause. It’s better to have an awkward long silence than meaningless fillers. I worked on this till I was 25, takes time but you’ll do good.

Best wishes for the future in your new roll at Anfield.

1:26:00 core tools: tableau and having understanding of data analysis not just the preparing of data 🙌🏿

1:03:00 thanks for reassuring academics aren't the be all end all