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Study Plan for Learning Data Science Over the Next 12 Months [D]
In this thread, I address a study plan for 2021. In case you're interested, I wrote a whole article about this topic: Study Plan for Learning Data Science Over the Next 12 Months Let me know your thoughts on this. https://preview.redd.it/emg20nzhet661.png?width=1170&format=png&auto=webp&s=cf09e4dc5e82ba2fd7b57c706ba2873be57fe8de We are ending 2020 and it is time to make plans for next year, and one of the most important plans and questions we must ask is what do we want to study?, what do we want to enhance?, what changes do we want to make?, and what is the direction we are going to take (or continue) in our professional careers?. Many of you will be starting on the road to becoming a data scientist, in fact you may be evaluating it, since you have heard a lot about it, but you have some doubts, for example about the amount of job offers that may exist in this area, doubts about the technology itself, and about the path you should follow, considering the wide range of options to learn. I’m a believer that we should learn from various sources, from various mentors, and from various formats. By sources I mean the various virtual platforms and face-to-face options that exist to study. By mentors I mean that it is always a good idea to learn from different points of view and learning from different teachers/mentors, and by formats I mean the choices between books, videos, classes, and other formats where the information is contained. When we extract information from all these sources we reinforce the knowledge learned, but we always need a guide, and this post aims to give you some practical insights and strategies in this regard. To decide on sources, mentors and formats it is up to you to choose. It depends on your preferences and ease of learning: for example, some people are better at learning from books, while others prefer to learn from videos. Some prefer to study on platforms that are practical (following online code), and others prefer traditional platforms: like those at universities (Master’s Degree, PHDs or MOOCs). Others prefer to pay for quality content, while others prefer to look only for free material. That’s why I won’t give a specific recommendation in this post, but I’ll give you the whole picture: a study plan. To start you should consider the time you’ll spend studying and the depth of learning you want to achieve, because if you find yourself without a job you could be available full time to study, which is a huge advantage. On the other hand, if you are working, you’ll have less time and you’ll have to discipline yourself to be able to have the time available in the evenings, mornings or weekends. Ultimately, the important thing is to meet the goal of learning and perhaps dedicating your career to this exciting area! We will divide the year into quarters as follows
First Quarter: Learning the Basics
Second Quarter: Upgrading the Level: Intermediate Knowledge
Third Quarter: A Real World Project — A Full-stack Project
Fourth Quarter: Seeking Opportunities While Maintaining Practice
A programming language that you can apply to data science: Python or R.
We recommend Python due to the simple fact that approximately 80% of data science job offers ask for knowledge in Python. That same percentage is maintained with respect to the real projects you will find implemented in production. And we add the fact that Python is multipurpose, so you won’t “waste” your time if at some point you decide to focus on web development, for example, or desktop development. This would be the first topic to study in the first months of the year.
Familiarize yourself with statistics and mathematics.
There is a big debate in the data science community about whether we need this foundation or not. I will write a post later on about this, but the reality is that you DO need it, but ONLY the basics (at least in the beginning). And I want to clarify this point before continuing. We could say that data science is divided in two big fields: Research on one side and putting Machine Learning algorithms into production on the other side. If you later decide to focus on Research then you are going to need mathematics and statistics in depth (very in depth). If you are going to go for the practical part, the libraries will help you deal with most of it, under the hood. It should be noted that most job offers are in the practical part. For both cases, and in this first stage you will only need the basics of:
Statistics (with Python and NumPy)
Descriptive statistics
Inferential Statistics
Hypothesis testing
Probability
Mathematics (with Python and NumPy)
Linear Algebra (For example: SVD)
Multivariate Calculus
Calculus (For example: gradient descent)
Note: We recommend that you study Python first before seeing statistics and mathematics, because the challenge is to implement these statistical and mathematical bases with Python. Don’t look for theoretical tutorials that show only slides or statistical and/or mathematical examples in Excel/Matlab/Octave/SAS and other different to Python or R, it gets very boring and impractical! You should choose a course, program or book that teaches these concepts in a practical way and using Python. Remember that Python is what we finally use, so you need to choose well. This advice is key so you don’t give up on this part, as it will be the most dense and difficult. If you have these basics in the first three months, you will be ready to make a leap in your learning for the next three months.
Second Quarter: Upgrading the Level: Intermediate Knowledge
https://preview.redd.it/y1y55vynet661.png?width=669&format=png&auto=webp&s=bd3e12bb112943025c39a8975faf4d64514df275 If you want to be more rigorous you can have start and end dates for this period of study at the intermediate level. It could be something like: From April 1 to June 30, 2021 as deadline. Now that you have a good foundation in programming, statistics and mathematics, it is time to move forward and learn about the great advantages that Python has for applying data analysis. For this stage you will be focused on:
Data science Python stack
Python has the following libraries that you should study, know and practice at this stage
Pandas: for working with tabular data and make in-depth analysis
Matplotlib and Seaborn: for data visualization
Pandas is the in-facto library for data analysis, it is one of the most important (if not the most important) and powerful tools you should know and master during your career as a data scientist. Pandas will make it much easier for you to manipulate, cleanse and organize your data.
Feature Engineering
Many times people don’t go deep into Feature Engineering, but if you want to have Machine Learning models that make good predictions and improve your scores, spending some time on this subject is invaluable! Feature engineering is the process of using domain knowledge to extract features from raw data using data mining techniques. These features can be used to improve the performance of machine learning algorithms. Feature engineering can be considered as applied machine learning itself. To achieve the goal of good feature engineering you must know the different techniques that exist, so it is a good idea to at least study the main ones.
Basic Models of Machine Learning
At the end of this stage you will start with the study of Machine Learning. This is perhaps the most awaited moment! This is where you start to learn about the different algorithms you can use, which particular problems you can solve and how you can apply them in real life. The Python library we recommend you to start experimenting with ML is: scikit-learn. However it is a good idea that you can find tutorials where they explain the implementation of the algorithms (at least the simplest ones) from scratch with Python, since the library could be a “Black Box” and you might not understand what is happening under the hood. If you learn how to implement them with Python, you can have a more solid foundation. If you implement the algorithms with Python (without a library), you will put into practice everything seen in the statistics, mathematics and Pandas part. These are some recommendations of the algorithms that you should at least know in this initial stage
Supervised learning
Simple Linear Regression
Multiple Linear Regression
K-nearest neighbors (KNN)
Logistic Regression
Decision Trees
Random Forest
Unsupervised Learning
K-Means
PCA
Bonus: if you have the time and you are within the time ranges, you can study these others
Gradient Boosting Algorithms
GBM
XGBoost
LightGBM
CatBoost
Note: do not spend more than the 3 months stipulated for this stage. Because you will be falling behind and not complying with the study plan. We all have shortcomings at this stage, it is normal, go ahead and then you can resume some concepts that did not understand in detail. The important thing is to have the basic knowledge and move forward! If at least you succeed to study the mentioned algorithms of supervised and unsupervised learning, you will have a very clear idea of what you will be able to do in the future. So don’t worry about covering everything, remember that it is a process, and ideally you should have some clearly established times so that you don’t get frustrated and feel you are advancing. So far, here comes your “theoretical” study of the basics of data science. Now we’ll continue with the practical part!
Third Quarter: A Real World Project — A Full-stack Project
https://preview.redd.it/vrn783vqet661.png?width=678&format=png&auto=webp&s=664061b3d33b34979b74b10b9f8a3d0f7b8b99ee If you want to be more rigorous you can have start and end dates for this period of study at the intermediate level. It could be something like: From July 1 to September 30, 2021 as deadline. Now that you have a good foundation in programming, statistics, mathematics, data analysis and machine learning algorithms, it is time to move forward and put into practice all this knowledge. Many of these suggestions may sound out of the box, but believe me they will make a big difference in your career as a data scientist.
The first thing is to create your web presence:
Create a Github (or GitLab) account, and learn Git. Being able to manage different versions of your code is important, you should have version control over them, not to mention that having an active Github account is very valuable in demonstrating your true skills. On Github, you can also set up your Jupyter Notebooks and make them public, so you can show off your skills as well. This is mine for example: https://github.com/danielmoralesp
Learn the basics of web programming. The advantage is that you already have Python as a skill, so you can learn Flask to create a simple web page. Or you can use a template engine like Github Pages, Ghost or Wordpress itself and create your online portfolio.
Buy a domain with your name. Something like myname.com, myname.co, myname.dev, etc. This is invaluable so you can have your CV online and update it with your projects. There you can make a big difference, showing your projects, your Jupyter Notebooks and showing that you have the practical skills to execute projects in this area. There are many front-end templates for you to purchase for free or for payment, and give it a more personalized and pleasant look. Don’t use free sub-domains of Wordpress, Github or Wix, it looks very unprofessional, make your own. Here is mine for example: https://www.danielmorales.co/
Add all the exercises and projects you have done so far, in the previous 6 months, to your online portfolio. You already have material to make yourself known, no matter how professional your Jupyter Notebooks look. My Jupyter Notebooks for now I’m uploading them here: https://www.narrativetext.co/
Choose a project you are passionate about and create a Machine Learning model around it.
The final goal of this third quarter is to create ONE project, that you are passionate about, and that is UNIQUE among others. It turns out that there are many typical projects in the community, such as predicting the Titanic Survivors, or predicting the price of Houses in Boston. Those kinds of projects are good for learning, but not for showing off as your UNIQUE projects. If you are passionate about sports, try predicting the soccer results of your local league. If you are passionate about finance, try predicting your country’s stock market prices. If you are passionate about marketing, try to find someone who has an e-commerce and implement a product recommendation algorithm and upload it to production. If you are passionate about business: make a predictor of the best business ideas for 2021 :) As you can see, you are limited by your passions and your imagination. In fact,those are the two keys for you to do this project: Passion and Imagination. However don’t expect to make money from it, you are in a learning stage, you need that algorithm to be deployed in production, make an API in Flask with it, and explain in your website how you did it and how people can access it. This is the moment to shine, and at the same time it’s the moment of the greatest learning. You will most likely face obstacles, if your algorithm gives 60% of Accuracy after a huge optimization effort, it doesn’t matter, finish the whole process, deploy it to production, try to get a friend or family member to use it, and that will be the goal achieved for this stage: Make a Full-stack Machine Learning project. By full-stack I mean that you did all the following steps:
You got the data from somewhere (scrapping, open data or API)
You did a data analysis
You cleaned and transformed the data
You created Machine Learning Models
You deployed the best model to production for other people to use.
This does not mean that this whole process is what you will always do in your daily job, but it does mean that you will know every part of the pipeline that is needed for a data science project for a company. You will have a unique perspective!
Fourth Quarter: Seeking Opportunities While Maintaining Practice
https://preview.redd.it/qd0osystet661.png?width=1056&format=png&auto=webp&s=2da456b15985b2793041256f5e45bca99a23b51a If you want to be more rigorous you can have start and end dates for this period of study at the final level. It could be something like: From October 1 to December 31, 2021 as deadline. Now you have theoretical and practical knowledge. You have implemented a model in production. The next step depends on you and your personality. Let’s say you are an entrepreneur, and you have the vision to create something new from something you discovered or saw an opportunity to do business with this discipline, so it’s time to start planning how to do it. If that’s the case, obviously this post won’t cover that process, but you should know what the steps might be (or start figuring them out). But if you are one of those who want to get a job as a data scientist, here is my advice.
Getting a job as a data scientist
“You’re not going to get a job as fast as you think, if you keep thinking the same way”.Author
It turns out that all people who start out as data scientists imagine themselves working for the big companies in their country or region. Or even remote. It turns out that if you aspire to work for a large company like data scientist you will be frustrated by the years of experience they ask for (3 or more years) and the skills they request. Large companies don’t hire Juniors (or very few do), precisely because they are already large companies. They have the financial muscle to demand experience and skills and can pay a commensurate salary (although this is not always the case). The point is that if you focus there you’re going to get frustrated! Here we must return to the following advise: “You need creativity to get a job in data science”. Like everything else in life we have to start at different steps, in this case, from the beginning. Here are the scenarios
If you are working in a company and in a non-engineering role you must demonstrate your new skills to the company you are working for. If you are working in the customer service area, you should apply it to your work, and do for example, detailed analysis of your calls, conversion rates, store data and make predictions about it! If you can have data from your colleagues, you could try to predict their sales! This may sound funny, but it’s about how creatively you can apply data science to your current work and how to show your bosses how valuable it is and EVANGELIZE them about the benefits of implementation. You’ll be noticed and they could certainly create a new data related department or job. And you already have the knowledge and experience. The key word here is Evangelize. Many companies and entrepreneurs are just beginning to see the power of this discipline, and it is your task to nurture that reality.
If you are working in an area related to engineering, but that is not data science. Here the same applies as the previous example, but you have some advantages, and that is that you could access the company’s data, and you could use it for the benefit of the company, making analyses and/or predictions about it, and again EVANGELIZING your bosses your new skills and the benefits of data science.
If you are unemployed (or do not want, or do not feel comfortable following the two examples above), you can start looking outside, and what I recommend is that you look for technology companies and / or startups where they are just forming the first teams and are paying some salary, or even have options shares of the company. Obviously here the salaries will not be exorbitant, and the working hours could be longer, but remember that you are in the learning and practice stage (just in the first step), so you can not demand too much, you must land your expectations and fit that reality, and stop pretending to be paid $ 10,000 a month at this stage. But, depending of your country $1.000 USD could be something very interesting to start this new career. Remember, you are a Junior at this stage.
The conclusion is: don’t waste your time looking at and/or applying to offers from big companies, because you will get frustrated. Be creative, and look for opportunities in smaller or newly created companies.
Learning never stops
While you are in that process of looking for a job or an opportunity, which could take half of your time (50% looking for opportunities, 50% staying in practice), you have to keep learning, you should advance to concepts such as Deep Learning, Data Engineer or other topics that you feel were left loose from the past stages or focus on the topics that you are passionate about within this group of disciplines in data science. At the same time you can choose a second project, and spend some time running it from end-to-end, and thus increase your portfolio and your experience. If this is the case, try to find a completely different project: if the first one was done with Machine Learning, let this second one be done with Deep learning. If the first one was deployed to a web page, that this second one is deployed to a mobile platform. Remember, creativity is the key!
Conclusion
We are at an ideal time to plan for 2021, and if this is the path you want to take, start looking for the platforms and media you want to study on. Get to work and don’t miss this opportunity to become a data scientist in 2021! Note: we are building a private community in Slack of data scientist, if you want to join us write to the email: [[email protected]](mailto:[email protected]) I hope you enjoyed this reading! you can follow me on twitter or linkedin Thank you for reading!
++>>recommended Super Bowl 2021++>>: Chiefs vs Buccaneers Live On Reddit
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See our roundup of the best Super Bowl TV sales When does Super Bowl pre-game coverage start on Sunday? Don't think about doing anything else on Super Bowl Sunday, because CBS is on-air live from Raymond James Stadium from 11.30am ET/8.30am PT, making for a whopping seven hours of Super Bowl pre-game coverage on the channel. Super Bowl 2021: full schedule and TV guide While Covid has forced the NFL to make a number of changes to the usual Super Bowl Week schedule in 2021, most of the usual events and formalities are going ahead in one way or another. Super Bowl Media Day, for instance, became Super Bowl Opening Night on Monday, February 1 and saw select players interviewed over Zoom - not the usual circus that ensues at the start of the week. Here's a complete Super Bowl 2021 TV schedule for the big weekend: Saturday, February 6: NFL Honors 2021 at 9pm ET/PT on CBS Sunday, February 7: Super Bowl LV pre-game coverage from 11.30am ET/8.30am PT on CBS Sunday, February 7: Puppy Bowl XVII from 1pm ET/10am PT (2pm/11am paw-off) on Animal Planet US Sunday, February 7: Kitten Bowl VII at 2pm ET/11am PT on Hallmark Channel Sunday, February 7: Miley Cyrus presents TikTok Tailgate concert at 3pm on TikTok and CBS watch puppy bowl 2021 live stream (Image credit: Animal Planet/Discovery+) How to watch a Puppy Bowl 2021 live stream - and what is the Puppy Bowl? Super Bowl build-up wouldn't be the same without the Puppy Bowl, a pawsome pre-game tradition now in its 16th year - so we're on Puppy Bowl XVII, officially. It sees 70 adorable pups compete in a two-hour long event pitting Team Ruff vs Team Fluff. The event is co-hosted and the teams 'coached' by two of America's least likely BFFs, Snoop Dogg and Martha Stewart. A one-hour long pre-game show will recap the highlights of Puppy Bowls past from 1pm ET/10am PT, while the game itself 'kicks-off' at 2pm ET/11am PT. TV coverage is on Animal Planet, which if you don't have via cable, can be streamed using either the Discovery+ platform (from $4.99 a month, 7-day free trial) or an over-the-top cable replacement service like FuboTV (from $64.99 a month, 7-day free trial). The reason the Puppy Bowl has captured the nation's imagination is that in addition to being so darn cute, it also features adoptable dogs from shelters all over the country, so if you get tired of the usual talking heads pre-game coverage, be sure to tune in! Sadly, the Puppy Bowl doesn't seem to be available internationally, even in countries like the UK where Animal Planet is available. But anyone from the US currently abroad needn't worry as they can try our No. 1 rated VPN 100% risk-free for 30-days and tune in just like they would at home. super bowl 2021 live stream half time show the weeknd (Image credit: Michael Kovac/FilmMagic) Super Bowl 2021 Halftime Show: who's performing at Super Bowl LV? Following in the footsteps of a sensational performance by Shakira and J-Lo last year that was watched by some 104 million people (and received over 1,300 complaints), The Weeknd has been confirmed to headline the 2021 Super Bowl halftime how. It's expected to go down as the longest halftime show ever at 24 minutes, with Jay-Z and Roc Nation responsible for production of this year's entertainment. For more details, check out our full guide to the 2021 Super Bowl halftime show. Super Bowl 2021 odds and predictions The Kansas City Chiefs are currently installed as the heavy favorites to lift the Lombardi trophy for a second straight season. With arguably the league's most gifted QB in Patrick Mahomes under center, its best TE in Travis Kelce menacing opposing defences, and deadly skill players like Tyreek Hill able to break out for a big play at any time...it's easy to see why. The Bucs are the underdogs, having emerged from the NFC Wild Card picture with big wins over the Saints and Packers to get this far - and few would put another upset past them with GOAT Tom Brady under center. The combination of home field advantage and Brady being Brady somewhat mitigates Tampa's otherwise heavy underdog status, even if the 22,000 fans expected to attended is well below the normal 65,000+ capacity of Ray Jay. Still, while Tampa are a team brimming with the kind of confidence you get when you're led by TB12, most pundits are joining Vegas and the bookmakers in predicting a Chiefs win - though most have it down to be a close game that's likely to come down to the final possession.
The yearly beating of french clubs in european group stages has come to an end with two teams getting out (Paris in Champions League, Lille in Europa League) and the other three (Marseille, Rennes and Nice) managing to earn a whopping combined total of 7 points in 18 matches. Congrats to them. This weekend, the Ligue 1 teams started a little marathon of four matches in ten days before the winter break with an exciting Marseille-Monaco on saturday and a climactic Paris SG-Lyon on sunday night.
Appetizers
On the day it was announced that Mediapro, the new broadcaster of Ligue 1, was giving up for default of payment after only four months, the opening match of the matchday, usually the symbol of a festive weekend, was an appealing Saint-Étienne-Angers. Yes, Saint-Étienne-Angers. 0-0. Next.
Marseille made a statement in the race for the podium, beating Monaco, a direct rival, 2-1 on saturday afternoon, their sixth straight win in the league. Despite a larger possession and more chances throughout the game, the monégasques conceded two early goals from the Benedetto-Thauvin duo who exchanged assists with each other to get that early lead. After the loss in Lille to another european aiming team, Monaco concedes another loss, a definite halt after climbing up the rankings in the past weeks.
Lens-Montpellier was expected to be a pretty entertaining fixture and it was indeed. Even though the southerners took a healthy lead in the first 30 minutes, their opponents from the other side of the hexagon came back thanks to a lucky goal and a penalty. In the middle of the second half, Gaëtan Laborde, usually assister, gave Montpellier the three points and a fifth victory across their last six matches (the other one being the loss last week against PSG).
The clash between the teams-that-play-in-red-and-black-and-that-ashamed-the-whole-country-in-Europe resulted in a win for Rennes away in Nice with a goal from Mbaye Niang at the end of a game easily controlled by the Bretons. Despite a managerial change, Nice is still struggling to get back in form, their last win dating from a month and a half (same for Rennes before this one).
Speaking of teams that hadn't won in a long time, Lorient was part of this not really prestigious club until this sunday where they dispatched Nîmes 3-0 at home. The Merlus (Hakes in english) were finally rewarded for their quality of play and their lack of efficiency (six matches in a row without scoring). Nîmes on the other end continues to fall and hit the 18th place, synonymous of a playoff spot.
After a great start of the season, Metz is starting to struggle a bit, suffering a fifth match without a win, this time in Strasbourg, at the end of a high-scoring match (for Ligue 1 standards at least). Bronn and Nguette successively gave Metz the advantage but they were answered respectively by Simakan and Thomasson.
Three days after throwing the first place of their Europa League group at Celtic Park, Lille had the opportunity to reclaim another top position in the case of a misstep from PSG at Lyon. And they did the job with a splendid strike from Jonathan Bamba and a rocket of a header from José Fonte. After a solid first half, Bordeaux was dominated quite heavily throughout the last 45 minutes and despite a recent good form couldn't avoid the loss.
The most anticipated match of the week (arguably of the whole season even) unfortunately didn't provide the most entertaining spectacle. Lyon's domination in the first half was rewarded by a goal from Kadewere following a disastrous misunderstanding between Kimpembe and Paredes. With only one shot on target during the whole game, the parisians were barely able to provide any danger towards Anthony Lopes. With that win, their first at the Parc des Princes since 2007, Lyon takes the second place, ahead of their opponents of the day.
With 0,48 penalty per match, Ligue 1 tops the rankings among the top 5 leagues in Europe (ahead of Premier League with 0,47 and Bundesliga with 0,45). Another seven of them were whistled this weekend.
1-2 Champions League group stage 3 Champions League qualifiers round 3 4 Europa League group stage 5 Europa Conference League play-offs 18 Relegation play-offs 19-20 Relegation to Ligue 2
Stade Brestois : Le Bilan didn't talk about Brest yet, not in length at least, and it's a mistake because the team has certainly been one of the most interesting to follow this season. You just have to look at the table to understand what kind of team it is. With seven wins, seven losses and no draw, the 6th best attack and the 3rd worst defense of the league, the bretons, led by the former Dijon coach Olivier Dall'Oglio, have gambled everything on entertainment in a safer Bielsist way. And it works. Of course they have conceded a lot of goals, of course they have yet to play Paris, Lyon and Montpellier but as they have shown in the past, much like their english counterparts, they are not afraid of big teams. They beat Lille 3-2, Monaco 1-0 and lost 3-2 a match they should have won against Marseille. With four wins in the last five matchdays, the brestois have given themselves a large cushion so that they don't have to think yet about an eventual return in Ligue 2. Oh yes, we didn't mention it yet, they got promoted only last year.
Downwards
David Guion : After correctly predicting the dismissals of Patrick Vieira and Christian Gourcuff in the past two weeks, Le Bilan has basically become the equivalent of the Washington Post of french football, no less. Pulitzer, here we come. Anyway, there's another man whose job is more and more in danger. And it would be by far the saddest of the three if David Guion was showed the door. Not that it wouldn't do good (the way Reims has been playing for a long time now is quite shocking) but what he has done for the club in the past three seasons must not be overlooked. For his first year in Champagne in 2017-2018, Guion led Reims to a Ligue 2 champion title (getting the UNFP best Ligue 2 coach trophy in the process), followed by an 8th place, then a 6th place (though the season was stopped early) and a first participation in a european competition in almost sixty years (stopped early in playoffs against the modest MOL Fehérvár). Sadly, this season has not been good for David Guion and his team. At all. Reims curretnly sits at the 19th place, has not won in the last five games and does not seem to have many assets to get back on track. Their reputation of a solid defensive team has disappeared and it would be unrealistic to ask Boulaye Dia (8 goals already) to carry the entire attack by himself for the whole season. Even worse, Reims president said he wouldn't oppose a departure from his striker. If he does indeed leave, Reims would need a miraculous replacement to save themselves from a sure relegation. Paris Saint-Germain : We may not get a lot of opportunities to have PSG in this category so let's not waste this golden one. Indeed, Paris has struggled lately in the league. With 4 points taken out of the last possible 12, already 4 losses in 14 matchdays (more than Lyon, Lille and Marseille combined), Paris has logically let go its top spot, reclaimed by Lille, their opponents on next sunday. In fact, PSG had not lost four times this early since 2009-2010, a season in which they ended 13th and Jean-Eudes Maurice had regular play time. Of course Paris won't finish 13th this year, they still have the best attack and the best defense of the league but it's clear that the crucial european matches against Leipzig, Manchester United and Istanbul Başakşehir have put an emotional and physical toll on players already tired since the end of Champions League this summer. One thing is certain though : for the first time since 2017, the league title is in play.
I am very, very happy. With our different systems, we have an element of surprise that we didn't have last year. It's harder for the opponents to prepare their match and it's interesting for us. Emotionally, it was very hard with the end of the european adventure. So to do a performance like that, I say bravo to the team.
Morgan Schneiderlin, Nice midfielder :
We have to keep this collective spirit, we take fewer goals but we score less or not at all, it's hard to win matches. Believe me, the fans are disappointed but we, the players, are the first to be affected by this situation. We are keen to rectify all this before the break. We don't want to spend a season playing nothing, getting bored. We're going to do everything we can to win on Wednesday.
Christophe Pelissier, Lorient coach :
It is a success both offensively and defensively. It's a perfect evening. It's a relief because it was a burden not to score, not to be rewarded. We must savour it and recover well. This victory allows us to be in the running, with 4-5 teams (Strasbourg, Nîmes, Reims, Dijon). We have a mini-Championship (for survival) where we have to perform well. We have to win that championship.
Thomas Tuchel, Paris coach :
We saw a very mentally tired team. I had the impression that the last sequence (Manchester United - Montpellier - Basaksehir) was too much for us. We missed even some easy passes. It's the fault of all of us, me first, the team. It wasn't serious enough, we must have enough quality to win every match. That remains my responsibility, that's clear.
Rerel, Paris supporter but football connoisseur first and foremost :
You give money to Arsenal, they turn it into shit.
Next matchday
Wednesday 16/12, 19:00 Dijon FCO - Lille OSC Montpellier Hérault SC - FC Metz Angers SCO - RC Strasbourg Nîmes Olympique - OGC Nice Stade de Reims - FC Nantes Wednesday 16/12, 21:00 Paris Saint-Germain - FC Lorient Olympique Lyonnais - Stade Brestois Stade Rennais - Olympique de Marseille AS Monaco - RC Lens Girondins de Bordeaux - AS Saint-Étienne Thanks a lot to Hippemann and NotMeladroit for all the clips and the tables ! For more news about the best league in the world (except for the other four) and to improve your french, come and subscribe to /Ligue1. All feedbacks are welcome ! Previous matchdays : Season 2020-2021 M1 - M2 - M3 - M4 - M5 - M6 - M7 - M8 - M9 - M10 - M11 - M12 - M13 Season 2019-2020 M12 - M13 - M14 - M15 - M16 - M17 - M18 - M19 - M20 - M21 - M22 - M23 - M24 - M25 - M26 - M27 - M28
My sister has had, well, let’s say a history of less than amicable interactions with people outside of the family. Even those within haven’t been spared her seemingly source-less ire, but those who lack the commonality of blood feel—in ways both openly and subtly hostile—her anger and unfounded spite. For as long as I can remember, going all the way back to our troublesome toddlerhood, my sister has made it her modus operandi, her prime existential impetus, to inflict harm with words and derision; with guile and deception; all out of some inborn distaste for anyone she deems—by standards unknowable—pretentious, prideful, or otherwise unworthy of some perceived self-confidence with which they allegedly carry themselves. Throughout her life, in a role immediately given to me by my parents once I had achieved the physicality sufficient to restrain her, I was made my sister’s keeper, wrangler. Any arguments or social bouts with peers, or even strangers, were clumsily broken up and de-escalated by yours truly. I can’t begin to estimate how many quarrels with girls I ended by simply yanking her away from the group, who my sister had confronted—always unprovoked—because she felt that they were too sure of themselves and their prettiness. I’m not the kind of man who assigns a value of beauty to his own sister based on primitive or outdated standards of attraction, but I can say that, in a way, I get her jealously; I at least understand how one might feel the way she feels. My family at large isn’t the prettiest stock; I’m certainly no looker, myself. But what confounds me is the resultant rage and indignation, at the mere sight of someone she perceives as prettier than herself. It’s unreasonable, nonsensical. I won’t waste time describing each and every petty, pointlessly hostile confrontation. The idea of my sister’s “condition”, for lack of a better word, has been established. She’s a moderately intelligent person, who had—at one nearly forgotten point in her life—lots of ambition, and goals unrelated to the smiting and punishment of her peers. But as life went on, and I grew older, I couldn’t always be by her side, and she eventually got into some scraps and heated exchanges that landed her before judges, and behind bars, and at the beck and call of probation officers. Nothing that would’ve brought shame to the family name—there are some among us who have as many prison stories as other families might have camping trips—but bad enough to leave her in a sorry state; living in a downtrodden, ex-convict-ridden apartment complex. That is until she couldn’t even afford that near derelict hovel, and—after a needlessly protracted request—moved in with me, in my suburban home. While our paths of life had diverged considerably, we shared one thing in common: we were both single and childless, despite being in our early thirties. Now, I knew my sister, and had put into place several contingencies, and issued many warnings, in preparation for her arrival. I informed my neighbors of her perpetually “irritable” mood, and essentially begged them—saving only a slight amount of pride—to forgive any outbursts or lapses in courtesy she may have. They assured me that they understood, and even commended me for what I suppose would be called “familial charity.” Also, knowing that without distraction my sister would simply brood and conjure up entirely imaginary—or severely misinterpreted—scenarios in which she was the target of some offense, I bought her a laptop. I figured that if she were to engage in hostilities, it would be best if they occurred online, with strangers who couldn’t send bricks through my windows or leave dog shit in my mailbox. How could I have ever predicted that she’d use the laptop to bring about the ruin of my life and home? Once she had settled in—which hadn’t taken long, considering her lack of belongings—she immediately set to familiarizing herself with the laptop. She’d had experience with computers in the past, but her recent journeys into criminality had often included the restriction from, or limitation of, access to such privileges. She was of course extremely appreciative, and promised that she would eventually pay me back; “In some way”, being the convenient follow-up. I had stocked the fridge, cupboards, pantry, closets, and drawers with all the food, supplies, kitchenware, and every day household items she’d possibly need. I furnished the guest room that had laid empty since the purchase of the house, and told her that it was hers for as long as she needed it to be. The appropriate gestures of gratitude were spoken, hugs were exchanged, her parole officer was notified, and I resumed my life as normal. The first Monday of co-habitation with my sister was, as I had feared but sensibly anticipated, a disaster. I came home on my lunch break—I had suspected, or maybe preternaturally sensed, some disturbance—to find a few women standing on my front-lawn, glaring at my house. There were three of them, and they were all fairly attractive. Ordinarily, being the simple man that I am, I’d be over-joyed to find these well-out-of-my-league women gathered on my property. But the circumstances weren’t so fantastical, and the reason for their congregation wasn’t out of any sudden and inexplicable love for me. As I parked in the driveway and whispered a prayer of mercy towards whomever might be listening from above, the women stomped on over to the car; faces scowling fiercely. I took a moment examine whether or not they bore weapons, and once I was sure of my safety, exited the car. I gave them a friendly smile, and before anything else could be done, a barrage of anger was unleashed upon me, with the single inspiration being my sister. Somehow, over the weekend of her arrival, my sister had amassed quite the following on Twitter, after having spent almost every waking moment berating celebrities, social media figures, and anyone else she could think to criticize. I chalked the rapid accumulation of followers up to old expression of misery loving—needing—company, and that all of my sister’s followers—all 12,000 of them—were equally or at least similarly bitter, impoverished, and vitriolic. Apparently, when my sister had grown tired of the larger targets, she’d focused her sights on closer subjects. The three women, during their early morning jog, had passed by my home, and my sister—always awake, always seething—had seen them go by through the living room windows. Incensed by the sight of these undeniably attractive women, she immediately put fingers to keys, and fabricated a story about the women wantonly littering throughout the neighborhood. According to the six tweets that tackled the nonexistent issue, the streets and sidewalks were “covered” with energy bar wrappers, plastic water bottles, and smears of exhaustively chewed gum. Despite having only seen the women this one time, my sister applied a history to their objectionable and totally imagined delinquency; a history that spanned further back than her tenancy of my home. Since my sister had failed to withhold—had actually proudly offered—the location of the neighborhood in which the fictional environmental offenses had taken place, her followers quickly went to action; contacting city officials, and even residents who happened to have the location in their social media bios. And, if that hadn’t been enough, my sister had stealthily yet awkwardly taken a picture of the joggers with the laptop’s webcam, and uploaded it as supplemental evidence to her tweets. Despite the absence of the garbage in the image, the mere presence of the women was sufficient enough evidence for her flock. The women, all having twitter accounts, were eventually made aware of their online denigration by my sister. Infuriated by the lies, they stormed my property and demanded that my sister come out and explain herself. Sensibly, my sister had remained inside, and continued to pour gas onto the fire behind her computer screen. All of this had occurred in five hours. I went into the house expecting a tirade from my sister about the women, but she instead sat in the living room chair—from which she had conducted her adjudications—with her hands on the armrests; her face showing an expression that said, “I know, I know.” (Upon saying her name in exasperation, she replied by actually saying, “I know, I know.”) Using the remote-access app from my phone, I disconnected her laptop from the Wi-Fi, chastised her as best as I could, and set up an appointment with a therapist. She accepted and agreed to all this maturely, without any dubious looks or gestures of impudence. Once that half of the situation had been attended to—though not really remedied—I went outside and apologized for myself, and on behalf of my sister. I explained my sister’s psychological abnormalities to the women, who eventually softened, and complimented me on my patience. They left; their tempers quelled. I decided that, given the circumstances, it would be best if I stayed home for the remainder of the day; so, I called into work and gave an excuse that wasn’t believed, but was nonetheless accepted. What had been a stressful half-hour soon blossomed into a terrifying night. My sister, being relentlessly persistent in her disparagement of the world at large, had connected her laptop to one of the few unprotected networks of the neighborhood. Once she had regained access to Twitter and her followers, she unleashed a veritable shitstorm of criticisms, insults, and essentially illegal calls to action. She fumed, she ranted, she blasphemed, it was as if the demon which had guided her hands and words towards insults and conflict had at last taken full control of her. And, unsurprisingly, her followers joined in her rage; drank of it, and finally, disastrously, left their computers, pocketed their phones, and set off on the great pilgrimage to my town. By 6pm that same day, my neighborhood was aswarm with seething Twitter users. Thousands of them laid siege to my small, barely on the map town, first rivaling and then dwarfing the humble and unsuspecting populace. When I first heard of their arrival, I stormed into my sister’s room and demanded that she order them to leave the town. But she responded that it was out of her hands, and that town would be spared, anyway; that it was the three litterers who were destined to feel the fury of the Twitter-sent forces. Sure enough, shortly after confiscating the laptop and locking it in my safe, the ground began to tremble as the Twitter horde entered the neighborhood. Every kind of person was represented in that horde; it was the single most diverse gathering of people I’d ever seen, and yet shared by all was a visage of unrestrained hatred. I hadn’t seen the three women since they’d departed my house after my sincere apologies, but staring out my window at 6:32pm, I saw them sprinting towards the property. Despite their exertions, they were all dressed casually, as if they’d scrambled from their homes in panicked flight. I stepped out to meet them, and rather than be bombarded by complaints and demands for the head of my sister, they instead pleaded with me to have her recall the encroaching army. The rest of the night, as far as it concerned the short-lived siege, happened in a violent blur. I welcomed the women into my home, and they gladly entered. My sister had crept up behind me, and upon seeing her the women practically threw themselves at her feet; begging her to call off her soldiers. My sister told them as much as she’d told me; that the situation was out of her control, and even that she was just as scared as they were. I was particularly frightened myself, as I was unsure of how I had been included, if at all, in the narrative of littering and environmental sabotage. The fact that I had just granted asylum to these social media fugitives only seemed further my potential peril. Through the front windows of my house, I saw the neighbors who had been oblivious to the e-drama retreat into their homes, as the horde finally swarmed onto the street. As if they’d been spotted by scouts, the location of the three women was known to the horde—and that great mass of enraged Twitter uses converged upon my lawn; their faces contorted into visages of contempt and long-buried savagery. Some had either brought along or appropriated weapons, while others simply stood with clenched fists and bared teeth. In the dying light of the day, they looked like a gathering of demons; as if the Earth had been thrown open, and Pandemonium had poured forth from the steaming Chthonic pits. One person, perhaps the deputized leader, spoke up, and demanded that the three women step out and face judgement. Peering through the windows, the women collectively squealed in terror, while my sister typed away on a phone she had stealthily swiped from one of them. She caught my disappointed glance, and assured me that she was, despite her previous statements, trying to redirect their ire elsewhere. Through the thin walls of my cheaply made suburban home, I heard the dings and chirps of smartphone notifications; but the horde ignored the newly issued mandates, and continued to gather around the home, and make their demands of sacrifice. Almost petrified by fear, I stood my ground—behind the protection of the front door—offering no response nor sacrifice to the invaders. This inaction, this unwillingness to throw the entirely innocent women to the wolves, only intensified the horde’s anger. Casting aside all notions of civility, maturity, and basic human decency, they at last stormed the house itself; weapons raised, faces snarling, eyes wide and red with malice and madness. I quickly dashed to the kitchen, where I gathered in my arms a bundle of spatulas, spoons, forks, knives, rolling pins, and ladles. Had I even a few moments more to think, I might’ve instead gone to the garage, where deadlier weapons could’ve been found; but oh well, I hadn’t the time to consider which objects in my house were the most effective against a small siege. I threw these items onto my coffee table and instructed everyone to arm themselves. My sister grabbed a ladle, and the women chose knives and forks with which to do battle. Just then, the front door strained for a moment against its hinges, and then was knocked completely free of them as the horde pressed in. The front windows were also suddenly shattered by people who had hurled themselves through the weak glass. Without ceremony, without the drawing of battle lines and the offering of terms, the melee was on. The battle was brief, bloody, and horrifying. In that frenetic bout, I saw the depths of barbarism that perpetually dwell within the hearts of men; kept barely at bay by the loosely held and ephemeral convictions of civilization. I also learned of the existence of a ferocity that had always dwelt within me; a reserve of primal power from which I drew the strength needed to not only defend myself, but strike boldly and savagely at my attackers. Steak knives and dinner forks were my weapons, and I swung and stabbed without care for human life. Terror and rage warred in my heart; each fearful sight inspired a greater horror, but also deepened my desire to survive against such horrors. The women with whom I had been forced to ally myself also fought with a similar primal conviction; I heard their shrieks, more like those of harpies than soccer moms, as they clashed with the veritable fiends who sought their destruction. My sister, accustomed to such vitriol, fought with the familiarity and skill of a warrior. The nightmarish battle lasted about six minutes. Somehow, despite the sharp and bluntly edged implements used, no one had actually died. Many indeed had been lacerated and stunned, one or two even temporarily disfigured; but no one had lost their life, and by the time some sense could be made of the situation, everyone was able to stand on their feet with little or no assistance. All of my companions had avoided serious harm. Someone had bitten my ankle at some point, and it kind of hurt when I put all my weight on it, but I was otherwise unharmed. The violence had been abruptly ended not by the submission of either side—I'd been in the process of slapping someone with a fork—but by another, unforeseen means of interruption. From somewhere amidst the ruins of my living room, a voice called out, saying that some moderately “influential” social media figure had made a slightly inflammatory statement during a stream. To the Twitter users, this was absolutely unacceptable, and required their immediate collaborative focus. Their collective anger towards the three joggers was immediately dispelled, and together, without further violence, they left my home. In a limping, sluggish mass they made a grand exodus from the town, back to their homes where they would assuredly launch an online campaign against the offending social media influencer. The three joggers, battered and disheveled but still very much alive, thanked me for the temporary sanctuary, and promptly left my home. My sister began tidying up the ruinous house, muttering about the apparent audacity and insensitivity of the newly infamous social media influencer. And despite the terror, the violence, and the realization that I wasn’t as civilized as I had thought, the worst thing about that night was that the three women had left with my cutlery; and I hadn’t any idea of where they actually lived within the neighborhood.
[France Football] Interview with scouts on how they discovered Ansu Fati, Takefusa Kubo, Federico Valverde, Kai Havertz, Hakim Ziyech, Riqui Puig and Raheem Sterling. "Try to find out if what you perceive to be different comes from the player's head. If it is the case, sign him."
What they have in common is that, one day, on the bend of a field, they have spotted or validated the profile of one of those who are now the joy of the biggest European clubs. Those who found Ansu Fati, Kai Havertz, Takefusa Kubo, Raheem Sterling, Federico Valverde and Hakim Ziyech tell the story of their love at first sight, why they fell in love at first sight, and, as a watermark, their profession. Freshly mowed parks in London, playgrounds in Montevideo, overcrowded fields in the Paris suburbs, synthetic playgrounds in Tokyo... Everywhere, all the time, soccer games are played throughout Europe and the world. Around the playgrounds, the voices of parents mingle with those of educators and the cries of young children. Further back, a fourth type of character is regularly added to the picture. Whether they are recruiters, intermediaries or simple enthusiasts, they scrutinize the catches and movements in a much more discreet way. Yet they are at the center of it all, because they have the power to put a budding star on the road to success. For FF, these talent scouts look back at their best find, how they got their hands on it, and - for some of them - the coaching work they then had to do with their nugget. Slawomir Czarniecki ( Kai Havertz): "He was never afraid of the other side's dry cleaning". Bayer Leverkusen's sports coordinator, the man who has just seen his protégé fly to England and Chelsea believes that fairies once had to bend over Kai Havertz's cradle. Endowed with a mad talent, the German international had to be mentally accompanied...
"By the time one of our regional scouts told us about him, Kai was already playing for a good academy, Alemannia Aachen (Editor's note: The main club in Aachen, the player's hometown). The first time I saw him play with them, he was ten years old. At that time we were already in contact with the family. We had introduced them to the club's facilities and philosophy. But if we stick to the field, the first match I saw him play was... against us. Our youngsters had won by a large margin but Kai had scored all three of his team's goals. But I can't take any credit for detecting great qualities in him that day. In the end, if I played a role, it was afterwards: when we presented our project and then to accompany him throughout his training. What were his main qualities before he joined us? I would say his speed, but also and above all his ability to make everything simple, even under pressure. He was never scared of the other side's dry cleaners. The funny thing is that he wasn't big at all at that time. Until the U15s he was even one of the smallest of our groups. It's interesting because it means that he had to be at full strength all those years." "I don't know if we can say that it was already sold out at the time, but in any case it had something special. He had everything that cannot be acquired, a kind of gift from heaven. He then worked hard, of course, but some things can't be learned... He was usually on the axis, in 8, 10 and 9. He was played here because that's where you have to be the most demanding. That's what we had to develop in him: that requirement. Once again, spotting a player like him is not very difficult. What you have to do, after you've identified a great potential, is to make the boy understand that he can become a top (he insists) player. Repeat it to him too, even when he's not as good a player. That's what we did with Kai. So you can imagine what kind of moment it was when, six years after his arrival, his mother and I attended his first training session with the big boys...".
Albert Puig ( Ansu Fati, Riqui Puig and Takefusa Kubo, among others): "Try to find out if what you perceive to be different comes from the player's head. If it is the case, sign it." A recruiter for FC Barcelona in the early 2000s, Albert Puig then directed the Masia between 2010 and 2014. Known for having brought Ansu Fati, Riqui Puig (no family ties), Takefusa Kubo, Thiago Alcantara but also Marc Cucurella or Dani Olmo, the one who now coaches in Japan (Albirex Niigata) looks back on the discovery of the first three cities.
"Both (Ansu Fati and Riqui Puig) are great players and have a bright future ahead of them. I am delighted to have found these two gems but I am also happy to have discovered other players, less exposed to the media but whose potential was more difficult to detect when they were young. Riqui (Puig) was obviously very talented but the question of recruiting him arose because it was clear that his physique was not going to be of much help in the short term and that could be a hindrance. With him, we had to look further... "For Ansu (Fati), it's different. He was a pure talent. There was no discussion about him. But as some of my colleagues have had to tell you, the essential thing is not so much to discover and then recruit but to train, educate and thus guide these promising people. The road to success is long and difficult and many external factors come into play. But yes, of course, raw talent is at the root of everything. It's a must and they had it back then. I'm talking about when Ansu was 9 years old. He had just left Africa, but it was a rough diamond that brought a lot of joy to the game." "Riqui was 11 years old the first time I saw him play. I watched him evolve from year to year and it was felt that he should be brought in at the age of 14. Again, his physique was a big handicap but I think that somehow it made him stronger mentally and made him want to do everything he could to improve tactically." "The case of Takefusa (Kubo) is even different. We signed him thanks to Oscar Hernandez, who is currently my assistant at Albirex. He was coordinating one of our campuses in Japan. He is the one who discovered Take. He told me that there was this young Japanese talent whose family was about to move to Barcelona. I trusted him and agreed to let him come and try out with us for a week. From his first balls, I understood how huge the talent of this child was. We then recruited him. He was a very mentally strong boy who didn't hesitate to take risks in the game. He had a great personality and, of course, a great technique. But when you have the talent, that competitive mindset, and that mental strength, you can only succeed, or almost succeed...." "I don't forget boys like Lee (Kang-in), Brahim Diaz, Sergi Roberto, Munir (El Haddadi), Thiago Alcantara, Oriol Romeu, Iñaki Peña, Adama (Traoré), (Jon) Toral, Miranda, Pablo Moreno... All of these boys have their own stories and I keep in mind memories about each one of them. But without going into details I think it is important to underline one thing about our job: stay on your first impression! It is the fruit of all your experience. Don't look for flaws. Try to find out if what you perceive to be different comes from the player's head. If so, sign it!"
Clive Ellington ( Raheem Sterling): "We were simulating post-game interviews on the way home".
"I was introduced to Raheem when he was about eight years old. I watched him play in the middle of a playground and I thought, either this kid is incredibly good, or the people he plays with are incredibly bad (laughs). He had a technique and moves that you only see in professionals. So I asked him what he was doing on the weekend. He told me he wasn't doing anything special. I then asked him what team he played with. He told me that he didn't play for anyone. (Editor's note: Clive Ellington is an educator with Alpha & Omega FC). And that's when the magic started to happen. We watched him play and wondered how he could achieve what he was doing in front of players who were bigger than he was. It's a natural, pure talent. It wasn't the first time we'd heard about a talented kid, but he had, and still has, the humility to do it. That's what we noticed very quickly and one of the things I like most about him. He realized very quickly that he had great potential, the potential to make a career, but he never showed it. When he was 12 or 13 years old it was particularly visible: it was not the desire to be above the pack that motivated him. On the contrary, he wanted the whole team to be at his level, if not at an even higher level. He was anything but selfish. That doesn't mean he wasn't more determined than average. His teammates saw this as a recreation, not him." "Where he was stronger? Speed, of course, but also balance, the ability to stand. What did he need to learn? Accepting defeat or at least learning how to live it better. Passing more assists, too. He was also asked to pay attention to how he was getting his messages across. I remember telling him, "If you can't find the words to get your teammate to lift his head, it's better not to say anything at all." We also prepared him a little bit for whatever was going to happen to him by faking interviews. We did that in the car on the way to the game or training (laughs). And when I would ask him if he was aware that he had become one of the best players in the country, he would answer me with a look that would say, "What are you talking about?" (laughter). But we knew we had a phenomenon in our hands, a future superstar. And since his passion for the sport was equal to all that... He wanted to play soccer all the time, all the time (he insists)! He is also very grateful to the educators who made him do some extra work after training, which says a lot about his education. In this regard, we also have a lot of esteem for his mother, who worked very hard to provide for him. Are we still in contact with Raheem? Of course we are! And we don't just talk about soccer. What I can tell you is that we haven't seen everything yet. I'm convinced that the best is yet to come... In conclusion, you should know that the fact that he has been able to face judgments that have not always been made in the past is a great advantage for him." "I'm very proud to be the man he is now."
Karel Brandsma ( Hakim Ziyech): "You don't really discover this kind of player". Director of the SC Heerenveen recruiting unit at the time of the signing of the new signing for Chelsea, Brandsma is humbled to look back on one of the most beautiful moves in the club's history.
"A few months before we moved, we had been given the information that there was a very promising young dribbler playing for ASVD Dronten. So we logically moved. Our scout could notice how Hakim was the best player on the field. When the difference is so big, it's not so difficult to notice it. Anyone with a pair of eyes could have seen that talent. To tell the truth (he's looking for his words)... you don't really get to know this kind of player. The boy is there, right in front of you, and you just have to do everything you can as a club to bring a player of that caliber back to Heerenveen. And that's what we did! "His father had just passed away. So he needed a structure that could accommodate him, that would allow him to go back and forth between his home in Dronten and the training center. With him, we knew that the main thing was not the recruitment of the player but the accompaniment that would have to follow. The gambler had to feel that he was going to join a family. The rest, and especially the determination, we soon saw that he had it. We also quickly realized that this boy hated mediocrity."
Néstor Gonçalves ( Federico Valverde): "He knew how to get out of the frame to solve a situation". Gonçalves is also the origin of the emergence of Rodrigo Bentancur (on the Boca Juniors side), and is the one who recommended the name Federico Valverde to the leaders of the mythical Peñarol. A few months later, his foal became a Uruguayan international at youth level and scared the recruitment cells all over Europe (the player notably did an internship with the Arsenal Gunners in 2014). The scout, whose eyes always shine when he talks about the Real midfielder, remembers a kid who already read the game perfectly.
"The first time I saw Fede, he must have been nine or ten years old. His name had been slipped to me, so I went to see him play and talk to him. They hadn't told me he was extraordinary, no. It's hard to use that term at that age. I was told there was a player who was doing well, that's all. The first thing that caught my attention was how smart he was playing. The way he read the game was, for his age (he's looking for his words)... surprising. At that level, he was already quite different from the people he was playing with. I don't know how to say it precisely, but let's say that he managed to solve the situations that were submitted to him. He didn't hesitate to get out of the frame, out of the organization, if that was what the team needed. All of this was done very quickly. Again, these are things you don't often see in children that age. There was something else, too: his obsession with the goals he wanted to achieve and the progress he wanted to make. I'm talking about obsession in the positive sense of the word. On top of that, he was always listening to his educators. At that time, Fede was also very small and thin. But this was not a problem because with the chief doctor of the Peñarol and thanks to science, we knew approximately how big he was going to get. It's quite funny because Fede is now measuring exactly the size that we had determined. Was it easy to predict his success? When he was ten years old, I told the then president of Peñarol that this player embodied the future of the club and the future of the selection, I have documents that prove it. You know (he is looking for his words)... there are many factors, many aspects of the game that can be analyzed, but there is also something else: intuition."
My sister has had, well, let’s say a history of less than amicable interactions with people outside of the family. Even those within haven’t been spared her seemingly source-less ire, but those who lack the commonality of blood feel—in ways both openly and subtly hostile—her anger and unfounded spite. For as long as I can remember, going all the way back to our troublesome toddlerhood, my sister has made it her modus operandi, her prime existential impetus, to inflict harm with words and derision; with guile and deception; all out of some inborn distaste for anyone she deems—by standards unknowable—pretentious, prideful, or otherwise unworthy of some perceived self-confidence with which they allegedly carry themselves. Throughout her life, in a role immediately given to me by my parents once I had achieved the physicality sufficient to restrain her, I was made my sister’s keeper, wrangler. Any arguments or social bouts with peers, or even strangers, were clumsily broken up and de-escalated by yours truly. I can’t begin to estimate how many quarrels with girls I ended by simply yanking her away from the group, who my sister had confronted—always unprovoked—because she felt that they were too sure of themselves and their prettiness. I’m not the kind of man who assigns a value of beauty to his own sister based on primitive or outdated standards of attraction, but I can say that, in a way, I get her jealously; I at least understand how one might feel the way she feels. My family at large isn’t the prettiest stock; I’m certainly no looker, myself. But what confounds me is the resultant rage and indignation, at the mere sight of someone she perceives as prettier than herself. It’s unreasonable, nonsensical. I won’t waste time describing each and every petty, pointlessly hostile confrontation. The idea of my sister’s “condition”, for lack of a better word, has been established. She’s a moderately intelligent person, who had—at one nearly forgotten point in her life—lots of ambition, and goals unrelated to the smiting and punishment of her peers. But as life went on, and I grew older, I couldn’t always be by her side, and she eventually got into some scraps and heated exchanges that landed her before judges, and behind bars, and at the beck and call of probation officers. Nothing that would’ve brought shame to the family name—there are some among us who have as many prison stories as other families might have camping trips—but bad enough to leave her in a sorry state; living in a downtrodden, ex-convict-ridden apartment complex. That is until she couldn’t even afford that near derelict hovel, and—after a needlessly protracted request—moved in with me, in my suburban home. While our paths of life had diverged considerably, we shared one thing in common: we were both single and childless, despite being in our early thirties. Now, I knew my sister, and had put into place several contingencies, and issued many warnings, in preparation for her arrival. I informed my neighbors of her perpetually “irritable” mood, and essentially begged them—saving only a slight amount of pride—to forgive any outbursts or lapses in courtesy she may have. They assured me that they understood, and even commended me for what I suppose would be called “familial charity.” Also, knowing that without distraction my sister would simply brood and conjure up entirely imaginary—or severely misinterpreted—scenarios in which she was the target of some offense, I bought her a laptop. I figured that if she were to engage in hostilities, it would be best if they occurred online, with strangers who couldn’t send bricks through my windows or leave dog shit in my mailbox. How could I have ever predicted that she’d use the laptop to bring about the ruin of my life and home? Once she had settled in—which hadn’t taken long, considering her lack of belongings—she immediately set to familiarizing herself with the laptop. She’d had experience with computers in the past, but her recent journeys into criminality had often included the restriction from, or limitation of, access to such privileges. She was of course extremely appreciative, and promised that she would eventually pay me back; “In some way”, being the convenient follow-up. I had stocked the fridge, cupboards, pantry, closets, and drawers with all the food, supplies, kitchenware, and every day household items she’d possibly need. I furnished the guest room that had laid empty since the purchase of the house, and told her that it was hers for as long as she needed it to be. The appropriate gestures of gratitude were spoken, hugs were exchanged, her parole officer was notified, and I resumed my life as normal. The first Monday of co-habitation with my sister was, as I had feared but sensibly anticipated, a disaster. I came home on my lunch break—I had suspected, or maybe preternaturally sensed, some disturbance—to find a few women standing on my front-lawn, glaring at my house. There were three of them, and they were all fairly attractive. Ordinarily, being the simple man that I am, I’d be over-joyed to find these well-out-of-my-league women gathered on my property. But the circumstances weren’t so fantastical, and the reason for their congregation wasn’t out of any sudden and inexplicable love for me. As I parked in the driveway and whispered a prayer of mercy towards whomever might be listening from above, the women stomped on over to the car; faces scowling fiercely. I took a moment examine whether or not they bore weapons, and once I was sure of my safety, exited the car. I gave them a friendly smile, and before anything else could be done, a barrage of anger was unleashed upon me, with the single inspiration being my sister. Somehow, over the weekend of her arrival, my sister had amassed quite the following on Twitter, after having spent almost every waking moment berating celebrities, social media figures, and anyone else she could think to criticize. I chalked the rapid accumulation of followers up to old expression of misery loving—needing—company, and that all of my sister’s followers—all 12,000 of them—were equally or at least similarly bitter, impoverished, and vitriolic. Apparently, when my sister had grown tired of the larger targets, she’d focused her sights on closer subjects. The three women, during their early morning jog, had passed by my home, and my sister—always awake, always seething—had seen them go by through the living room windows. Incensed by the sight of these undeniably attractive women, she immediately put fingers to keys, and fabricated a story about the women wantonly littering throughout the neighborhood. According to the six tweets that tackled the nonexistent issue, the streets and sidewalks were “covered” with energy bar wrappers, plastic water bottles, and smears of exhaustively chewed gum. Despite having only seen the women this one time, my sister applied a history to their objectionable and totally imagined delinquency; a history that spanned further back than her tenancy of my home. Since my sister had failed to withhold—had actually proudly offered—the location of the neighborhood in which the fictional environmental offenses had taken place, her followers quickly went to action; contacting city officials, and even residents who happened to have the location in their social media bios. And, if that hadn’t been enough, my sister had stealthily yet awkwardly taken a picture of the joggers with the laptop’s webcam, and uploaded it as supplemental evidence to her tweets. Despite the absence of the garbage in the image, the mere presence of the women was sufficient enough evidence for her flock. The women, all having twitter accounts, were eventually made aware of their online denigration by my sister. Infuriated by the lies, they stormed my property and demanded that my sister come out and explain herself. Sensibly, my sister had remained inside, and continued to pour gas onto the fire behind her computer screen. All of this had occurred in five hours. I went into the house expecting a tirade from my sister about the women, but she instead sat in the living room chair—from which she had conducted her adjudications—with her hands on the armrests; her face showing an expression that said, “I know, I know.” (Upon saying her name in exasperation, she replied by actually saying, “I know, I know.”) Using the remote-access app from my phone, I disconnected her laptop from the Wi-Fi, chastised her as best as I could, and set up an appointment with a therapist. She accepted and agreed to all this maturely, without any dubious looks or gestures of impudence. Once that half of the situation had been attended to—though not really remedied—I went outside and apologized for myself, and on behalf of my sister. I explained my sister’s psychological abnormalities to the women, who eventually softened, and complimented me on my patience. They left; their tempers quelled. I decided that, given the circumstances, it would be best if I stayed home for the remainder of the day; so, I called into work and gave an excuse that wasn’t believed, but was nonetheless accepted. What had been a stressful half-hour soon blossomed into a terrifying night. My sister, being relentlessly persistent in her disparagement of the world at large, had connected her laptop to one of the few unprotected networks of the neighborhood. Once she had regained access to Twitter and her followers, she unleashed a veritable shitstorm of criticisms, insults, and essentially illegal calls to action. She fumed, she ranted, she blasphemed, it was as if the demon which had guided her hands and words towards insults and conflict had at last taken full control of her. And, unsurprisingly, her followers joined in her rage; drank of it, and finally, disastrously, left their computers, pocketed their phones, and set off on the great pilgrimage to my town. By 6pm that same day, my neighborhood was aswarm with seething Twitter users. Thousands of them laid siege to my small, barely on the map town, first rivaling and then dwarfing the humble and unsuspecting populace. When I first heard of their arrival, I stormed into my sister’s room and demanded that she order them to leave the town. But she responded that it was out of her hands, and that town would be spared, anyway; that it was the three litterers who were destined to feel the fury of the Twitter-sent forces. Sure enough, shortly after confiscating the laptop and locking it in my safe, the ground began to tremble as the Twitter horde entered the neighborhood. Every kind of person was represented in that horde; it was the single most diverse gathering of people I’d ever seen, and yet shared by all was a visage of unrestrained hatred. I hadn’t seen the three women since they’d departed my house after my sincere apologies, but staring out my window at 6:32pm, I saw them sprinting towards the property. Despite their exertions, they were all dressed casually, as if they’d scrambled from their homes in panicked flight. I stepped out to meet them, and rather than be bombarded by complaints and demands for the head of my sister, they instead pleaded with me to have her recall the encroaching army. The rest of the night, as far as it concerned the short-lived siege, happened in a violent blur. I welcomed the women into my home, and they gladly entered. My sister had crept up behind me, and upon seeing her the women practically threw themselves at her feet; begging her to call off her soldiers. My sister told them as much as she’d told me; that the situation was out of her control, and even that she was just as scared as they were. I was particularly frightened myself, as I was unsure of how I had been included, if at all, in the narrative of littering and environmental sabotage. The fact that I had just granted asylum to these social media fugitives only seemed further my potential peril. Through the front windows of my house, I saw the neighbors who had been oblivious to the e-drama retreat into their homes, as the horde finally swarmed onto the street. As if they’d been spotted by scouts, the location of the three women was known to the horde—and that great mass of enraged Twitter uses converged upon my lawn; their faces contorted into visages of contempt and long-buried savagery. Some had either brought along or appropriated weapons, while others simply stood with clenched fists and bared teeth. In the dying light of the day, they looked like a gathering of demons; as if the Earth had been thrown open, and Pandemonium had poured forth from the steaming Chthonic pits. One person, perhaps the deputized leader, spoke up, and demanded that the three women step out and face judgement. Peering through the windows, the women collectively squealed in terror, while my sister typed away on a phone she had stealthily swiped from one of them. She caught my disappointed glance, and assured me that she was, despite her previous statements, trying to redirect their ire elsewhere. Through the thin walls of my cheaply made suburban home, I heard the dings and chirps of smartphone notifications; but the horde ignored the newly issued mandates, and continued to gather around the home, and make their demands of sacrifice. Almost petrified by fear, I stood my ground—behind the protection of the front door—offering no response nor sacrifice to the invaders. This inaction, this unwillingness to throw the entirely innocent women to the wolves, only intensified the horde’s anger. Casting aside all notions of civility, maturity, and basic human decency, they at last stormed the house itself; weapons raised, faces snarling, eyes wide and red with malice and madness. I quickly dashed to the kitchen, where I gathered in my arms a bundle of spatulas, spoons, forks, knives, rolling pins, and ladles. Had I even a few moments more to think, I might’ve instead gone to the garage, where deadlier weapons could’ve been found; but oh well, I hadn’t the time to consider which objects in my house were the most effective against a small siege. I threw these items onto my coffee table and instructed everyone to arm themselves. My sister grabbed a ladle, and the women chose knives and forks with which to do battle. Just then, the front door strained for a moment against its hinges, and then was knocked completely free of them as the horde pressed in. The front windows were also suddenly shattered by people who had hurled themselves through the weak glass. Without ceremony, without the drawing of battle lines and the offering of terms, the melee was on. The battle was brief, bloody, and horrifying. In that frenetic bout, I saw the depths of barbarism that perpetually dwell within the hearts of men; kept barely at bay by the loosely held and ephemeral convictions of civilization. I also learned of the existence of a ferocity that had always dwelt within me; a reserve of primal power from which I drew the strength needed to not only defend myself, but strike boldly and savagely at my attackers. Steak knives and dinner forks were my weapons, and I swung and stabbed without care for human life. Terror and rage warred in my heart; each fearful sight inspired a greater horror, but also deepened my desire to survive against such horrors. The women with whom I had been forced to ally myself also fought with a similar primal conviction; I heard their shrieks, more like those of harpies than soccer moms, as they clashed with the veritable fiends who sought their destruction. My sister, accustomed to such vitriol, fought with the familiarity and skill of a warrior. The nightmarish battle lasted about six minutes. Somehow, despite the sharp and bluntly edged implements used, no one had actually died. Many indeed had been lacerated and stunned, one or two even temporarily disfigured; but no one had lost their life, and by the time some sense could be made of the situation, everyone was able to stand on their feet with little or no assistance. All of my companions had avoided serious harm. Someone had bitten my ankle at some point, and it kind of hurt when I put all my weight on it, but I was otherwise unharmed. The violence had been abruptly ended not by the submission of either side—I'd been in the process of slapping someone with a fork—but by another, unforeseen means of interruption. From somewhere amidst the ruins of my living room, a voice called out, saying that some moderately “influential” social media figure had made a slightly inflammatory statement during a stream. To the Twitter users, this was absolutely unacceptable, and required their immediate collaborative focus. Their collective anger towards the three joggers was immediately dispelled, and together, without further violence, they left my home. In a limping, sluggish mass they made a grand exodus from the town, back to their homes where they would assuredly launch an online campaign against the offending social media influencer. The three joggers, battered and disheveled but still very much alive, thanked me for the temporary sanctuary, and promptly left my home. My sister began tidying up the ruinous house, muttering about the apparent audacity and insensitivity of the newly infamous social media influencer. And despite the terror, the violence, and the realization that I wasn’t as civilized as I had thought, the worst thing about that night was that the three women had left with my cutlery; and I hadn’t any idea of where they actually lived within the neighborhood.
This week, Le Bilan celebrates its first birthday. Thank you everyone for being here every week to follow the last events of your favorite championship. And thank you to my londoner friend LeMexicanos for being the perfect Hermes last week. In Europe, the french clubs had another shocker with 4 losses and a win. Lille was brilliant in Milan and french football is grateful to the Dogues and Yusuf Yazıcı for this performance, single handedly saving the coefficient. Before the last international break of the year, there was still a Ligue 1 matchday this weekend with three obvious matches to follow : PSG-Rennes, Nice-Monaco and Lyon-Saint-Étienne.
Appetizers
Marseille won in Strasbourg in the most efficient and minimalistic way possible, with only one shot (but what a shot) in the whole 90 minutes. If Philip Glass was involved in football, he would coach Marseille.
Unsurprisingly, Montpellier won in Bordeaux 2-0 with goals from Mollet, who is starting to get his starting spot back regularly, and Delort. Bordeaux keeps disappointing with no visible signs of improvement. Their fans already knew from the start that the season would be long and certainly painful, it's looking more and more this way.
After an upsetting loss at the hands of RB Leipzig, Paris had to redeem themselves against another Champions League team, Rennes, defeated 3-0 by Chelsea this week. With eight injured players at the start of the game (and twelve at the end, seriously what are the physios doing ?), Paris still had no troubles taking the three points thanks to another goal from Kean and a brace from Di María (well one goal and a half in the end as the second one was given as an own goal for Da Silva). Rennes started the season very well but the last few weeks have been extremely rough to say the least, most likely a consequence of the heavy calendar, which is new for the team.
For the first time this season (and the first time in competitive matches since february), Lille fell. Brest was the team that finally defeated the Dogues. By scoring three times in the first half, they certainly made things quite complicated for a team probably physically diminished after their formidable feat in Milan (though according to Christophe Galtier, it was more the mentality that was lacking). Still, they didn't give up, getting back progressively with two goals from the inevitable Burak Yılmaz. The turkish striker even shot on the post late in the game but ultimately it was the Bretons who left the pitch victorious.
In the least Angers-esque possible, the black & white massacred Nîmes in their own home 5-1. You know you did poorly when even Loïs Diony scores against you (ok it was a penalty but still). Angers reaches the first half of the table, two points away from the Champions League spots (*shudders*, please don't). Meanwhile, the Crocodiles continue to feel the heat of the red zone.
Another high-scoring match saw Lens snatching a draw in the last minutes against Reims for their comeback after three weeks out of the pitches because of a COVID outbreak in the team. No less than five goals were scored in the last 15 minutes with Florent Sotoca being the hero of the Sang et Or (again should I say) with two goals at the end of the game.
After being humiliated in Prague against a team that lacked half of their players due to COVID, Nice had to bounce back, especially against their nearest rival. Unfortunately, they encountered a Monaco who seems to be (finally, perhaps, we will see) on the right track. Disasi opened the score, Diop doubled it in the second half before Pierre Lees-Melou reduced the gap. Not enough despite a clear domination in the last 45 minutes.
A derby between Lyon and Saint-Étienne is never a normal match and once again bizarre events occurred. First, Saint-Étienne played way better than expected and made their rivals suffer, especially in the first half with notable disappointing performances from Depay, Aouar and Bruno Guimarães, concluded by an own goal from Anthony Lopes following a great individual work from Bouanga. After an hour of playtime, Garcia made three changes, bringing in Thiago Mendes, Paqueta and, above all, Tino Kadewere. The zimbabwean, best scorer and best player of Ligue 2 last season with Le Havre, scored a brace something he dreamt about right before the match, delivering the Gones from a potential humiliating defeat. At the end of the game, les Verts had the opportunity to equalize but Denis Bouanga completely bottled the penalty.
34 goals were scored this weekend, as I predicted on thursday (and I've got witnesses to certify it). So far this season we've got on average 2,82 goals/match, compared to 2,34 last season at the same time.
1-2 Champions League group stage 3 Champions League qualifiers round 3 4 Europa League group stage 5 Europa Conference League group stage 18 Relegation play-offs 19-20 Relegation to Ligue 2
I had already planned to take stock of Ligue 2 since one or two weeks given the fact there were 5 matchdays since the last one. So imagine my reaction when I learned Toulouse lost against Valenciennes, a team that hadn't won since September. 5-4. At home. With FOUR GOALS FROM A RIGHT BACK. Was it laughter ? Confusion ? How does one not feel like it was a gift to the Bilan from the Almighty ? So yeah, that happened. In his whole career before this match, the hero of the day Jérémy Cuffaut, now 32, had only scored 11 goals. Unsurprisingly, he becomes the first defender having done such a feat in the history of Ligue 2. And that includes two wonderful free kicks (here's the last one, credit to NotMeladroit). Now I know laughing about Toulouse is fun but apart from this little hiccup, they have actually performed quite well lately. Since their first win in 11 months against Auxerre that we talked about last time, they have added another three wins to their tally, consecutively nonetheless, which allows them to reach the heights of the 9th place. And it's a dutchman, Stijn Spierings, who has become the technical leader of the team that still hopes to get back in the elite and with only one point from the playoffs spots, it's definitely doable. But the team there's a need to talk about is definitely Paris FC. After a last season where they barely saved their place in Ligue 2, it was tough to expect something incredible from them. Yet not only are the parisians leading the ranking, they are crushing it. With eight wins in ten matches and seven points above the second Troyes, the best attack and the second best defense, PFC is currently on an autoroute heading towards Ligue 1. It would be the first time two teams from Paris compete in Ligue 1 since 1990 and the relegation of Racing Club de Paris (though technically it can be debated since RC Paris is based in Colombes which is 6 km from Paris but let's not get too picky). Apart from the huge gap at the top, Ligue 2 is extremely tight with only the tiny club of Chambly seemingly on the wrong track. The fact they survived last year for their first L2 season, finishing at the 10th place, was already incredible. Also shoutout to Mickaël Le Bihan from Auxerre, top scorer of the league. Le Bilan 🤝 Le Bihan The complete Ligue 2 results Ranking
André Villas-Boas, Marseille coach, slightly angry at journalists :
You are not allowed to make efforts to win a match and when you win a match with your efforts the match is saved by others! What are you saying! But what are you saying sincerely! You have to stop sometimes! Make concrete analyses! If you look at other clubs, you will see this kind of things. You think that winning in Strasbourg away from home is easy! Extraordinary guys make the difference in all the clubs, it's always like that. It's a victory on a difficult pitch that takes us very high in the rankings. I know you're upset but that's how it is, that's life.
Thomas Tuchel, Paris coach, also angry at journalists :
For me you are disrespecting the players who are there and you are disrespecting the team's performance by asking five questions about Marquinhos, two about Florenzi and none about the game, none about the opponent or what is needed today. It shows that you have no respect at all for what we are doing and what the team needs to do here, and that is very sad for me.
Julien Stéphan, Rennes coach :
There was more realism, more efficiency, I also found more cunning in them, more intensity. We have a lot of progress to make to be able to fight against these teams. We saw it this week in wednesday's match (3-0 defeat against Chelsea in the Champions League) or today's match: even if they are two different match contents, at the end of the match, that makes two heavy defeats and there are a lot of things to correct.
Christophe Galtier, Lille coach :
We thought the kick-off was going to be at 2 p.m., we were an hour wrong. We found an opponent that we knew was determined, we didn't know how to respond to their commitment, especially in their offensive races. We didn't exist, it was difficult for us to make the counter-efforts, just like the first two goals. When it is the full-backs who score, it is because there is a real problem of balance. [...] When there is such a contrast between two matches, the explanation is mental, and the only person responsible is me. My starting eleven didn't work at all. We couldn't get back into Sunday's match. I should have injected more freshness.
ThePr1d3, Rennes supporter and #FrenchTech enthusiast :
Truffert is such a cone he could be a VLC ambassador.
Next matchday
Friday 20/11, 19:00 Stade Rennais - Girondins de Bordeaux Friday 20/11, 21:00 AS Monaco - Paris Saint-Germain Saturday 21/11, 17:00 Stade Brestois - AS Saint-Étienne Saturday 21/11, 21:00 Olympique de Marseille - OGC Nice Sunday 22/11, 13:00 FC Nantes - FC Metz Sunday 22/11, 15:00 Montpellier Hérault SC - RC Strasbourg Dijon FCO - RC Lens Stade de Reims - Nîmes Olympique Sunday 22/11, 17:00 Angers SCO - Olympique Lyonnais Sunday 22/11, 21:00 Lille OSC - FC Lorient Thanks a lot to Hippemann for all the clips and the tables ! For more news about the best league in the world (except for the other four) and to improve your french, come and subscribe to /Ligue1. All feedbacks are welcome ! Previous matchdays : Season 2020-2021 M1 - M2 - M3 - M4 - M5 - M6 - M7 - M8 - M9 Season 2019-2020 M12 - M13 - M14 - M15 - M16 - M17 - M18 - M19 - M20 - M21 - M22 - M23 - M24 - M25 - M26 - M27 - M28
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