thebaldtactician.bsky.social
I like football…. And data. And thus, FPL.
Follow for a combination of the three.
Best OR: 23.000
588 posts
334 followers
533 following
Getting Started
Active Commenter
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😂😂 will try my very best.
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Een match waarbij Brugge het voornamelijk van de goede, snelle tegenstoot moet hebben.
Vanaken met slechts één schot uit ‘fast-break’ in de JPL en nul in de CL.
Wordt overgeslagen. Zal voornamelijk heel veel achter Ederson/De Roon/Posch vandaag aan moeten.
Zal wel weer met meeste km eindigen…
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Perhaps time for Brugge to have Tzolis and Talbi pressure the Atalanta wingbacks more?
Going to be an interesting second #UCL half.
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late in the box for these crosses, as they lack a third good defensive aerial asset. Have the feeling we’re going to be seeing Atalanta punish them more during this upcoming game and a half.
Posch moving up in midfield allows Ederson to get close to the box too and create a fourth tread….
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And even tough Ordoñez and Mechele have been doing bits in the air, Atalanta are just so strong in the air.
With Retegui (1st), De Ketelaere (6th) and Pasalic (7th) they’ve got 3 players up front in the top 7 for headed shots in the Italian league.
Brugge having so much trouble with runs arriving
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Fuck off I’m only here for FPL.
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Make another account that covers this and keep this just FPL/DATA related. I’ll follow that one!
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Yes! Post on here about UCL, Dutch and other European Leagues, non-fantasy related.
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I think: depends on how long moving house is gonna take! 😂
You’re team looks great, but it ain’t no DGW. If you’re gonna be busy moving houses and don’t have time planning a WC to BB over a 3 GW period, then: do it!
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Have you considered….
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Haha amazing ones again.
IYKYK
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Obviously if his wife just gives birth on a bloody Wednesday or smt he’ll be fine to play 😂
And then there’s of course the possibility he’ll play nevertheless.
Like this absolute madman.
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Hmm okay, you’re all good then and Watkins seems like a pretty nice option.
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Hmm… how many Liverpool+villa+palace+newcastle players do you already own?
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I love the extra sass in the picture description 😂
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Oh yeah and there’s of course the case of having millions of money tied up into him in the case you want to bring him back…
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Depends on a lot of variables.
How many FT’s you have, what your GW29-30 chip plans are, if there are bigger fires to put out, etc. etc.
It’s not for me, as I need all my FT to transfer out BGW29 players.
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Seems like you have answered your own question?
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Awful news. Not sure what to say.
All the best to you and Barley.
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Not sure I agree on that one but… sure
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Hmm wrong player but the right idea nevertheless 😂
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Do you have all the projected points for GW26 managers?
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What’d you think?
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Definitely, which is why i added the comparison between season PPM and first five games.
Having said that, it is usually true that managers get hired when they have easy games on the horizon.
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What about the fact you’ve got so much money tied up in him!
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information to as many people as possible. I would love to hear some feedback on this as well as ideas for what comes next!
Thank you all! Have a great (FPL-less) weekend!
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In short, if a team does not COMPLETELY suck or is actually very decent, the 'new manager bounce' is a very real thing that should be a part of our betting / #FPL analysis.
As always, if you've come this far, please like and reposts! These things take a lot of time, and I am trying to get this ...
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seasonal average for the teams that hire them.
This statistical evidence is mostly found in managers who get hired after their team has scored between 0.5-1.49 PPM, both during the season and in the last five. For teams that score less, it does not seem to matter too much.
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❗CONCLUSION❗
There is very strong statistical evidence to suggest that the 'new-manager bounce' is a very real thing in the premier league. On average, managers score almost 0.54 PPM more in their first five then in the five games before their arrival, and 0.34PPM more in their first five then
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we fail to reject the first category but have strong statistical evidence to reject the second and third category.
Now that all the statistical mumbo-jumbo is out of the way, let's get to the conclusion.
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0.0-0.49: 0.281
0.5-0.99: 1.900
1-1.49: 1.592
PART 2:
0.0-0.49: <0
0.5-0.99: 2.08
1-1.49: 3.06
For 0.05 significance level, we get z-score of 1.645. In this case, in part 1 we fail to reject the first and third category (but barely for the third) and reject the second category, and in part 2 ...
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... to reject the null hypothesis.
Then, for the individual categories, we perform z-tests with the variance of the population (managers that stayed) to the sample (new hires). I will not bore you with all the variances and such. But in PART 1, we got z-scores of:
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11.51, which is very strong evidence to reject our null hypothesis.
In part 2, we got:
A sample of 167 with an average of 0.94 before and 1.27 after. The differences over these 167 cases had a st. dev. of .6298, which gives us a t-statistic of approx. 6.77, which again is very strong evidence ...
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... and population are big enough.
First, let's look at the general results. In part 1, we got:
A sample of 192 with an average of 0.73 before and 1.27 after. The differences over these 192 cases had a st. dev. of 0.6499. In this case, we actually use a t-test, and get a t-statistic of approx.
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through to the big red arrows in the end with the word "CONCLUSION". You'll find it!
If you're still reading however, let's get into it. We will be performing a series of one-sided hypothesis tests with a z/t-test statistic and a significance level of 0.05. We assume normality because our sample ..
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Now, to determine if any of these findings actually have any statistical significance and we are sure that these differences are not due to 'luck' or 'chance', we have to do some (not so interesting, but very important) statistical analysis. If you are not interested in this, just skip straight ...
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... are just very, very bad. Like Leicester City this season, who have barely improved after v. Nistelrooy's arrival!
It is interesting to note however that in the category 0.5-1.5, newly hired managers actually seem to have had a great advantage over managers who stayed in their seats.
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Here actually, for a PPM season average of under 0.5, managers who stayed actually did a slightly better job in the next five matches then recently hired once. Again, this could be for a number of reasons hard to put into numbers, but it might have to do with the fact that these teams generally ...
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To make sure that we have a big enough sample for the seasonal PPM, we have only taken into account managers hired after GW10. Here, the numbers in the categories from 0.0-1.49 seem quite significant, but once again we have to compare them to our population:
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score 1.27PPM in their first five games, compared to an 'average' seasonal average of 0.94PPM before hand. Again, to get a closer look, we divide these into the same five categories.
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... bad run of form.
It might be different however when clubs have played bad all season.
PART 2
In this part, we will be comparing the average PPM of a manager in his first five games after his arrival to the average seasonal PPM of his team before his arrival. As stated before, managers ...
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your manager or hiring a new one.
Take a look at this season for example. Between GW9 and 13, Aston Villa scored 2 points (0.4PPM). However, they kept the same manager, and scored 9 points in the next five (1.8PPM). So perhaps, a 'new manager bounce' is inevitable after hiring because of a ...
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As we can see here, keeping your manager after a certain spell of five game weeks gives you similar results compared to switching, although hiring seems slightly more favorable. For teams scoring less than 0.5PPM over a five gameweek run, you are ‘on-average’ almost the exact same off keeping ...