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u/Next-Abbreviations76

r/sportsanalytics r/footballtactics
▲ 33 r/sportsanalytics

At this point this sub could be renamed as r sportsbetting. And i think its boring.

Literally 90% of content is just "my model found a 5% edge at this game". Most of these have literally zero added value to the community, to the world. And its always just the same claude coded elo model that everyone has already made.

I get it, these are fun. But now they just feel like a huge pointless flood. I would prefer more innovation, even if it would result in less posts. Even if the quality of the posts would decrease. Seeing people try to make something new is what i wish for. And maybe just some general talk about it.

Am i overreacting? What do you think?

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u/Next-Abbreviations76 — 14 hours ago
▲ 9 r/footballtactics

What do we think of koeman's tactics?

During the whole first half, the two fullbacks have been used very strictly, almost in the same height of the 2 CBs. This resulted in a very strange and slow buildup, I would call it a 4123 or a 415 shape, frenkie being occupying a single pivot role. Defensively they were in a very robust 541 mid line, with almost zero aggressivity. De jong was the third centre back.

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The second half was much more intensive, but not as organized, which is understandable. But now im trying to focus on what happened in the first half.

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Do you think this setup is something that he actually wants to use throughout this tourmament? If so, I doubt it will work. This over-conservative way of using your fullbacks (not using them actually) seems so ineffective.

Or was he just trying to play it extra safe because it was the first game?

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u/Next-Abbreviations76 — 21 days ago
▲ 3 r/sportsanalytics

[Soccer] A function that **attempts** to tell what a team's clean sheet probability will be for any pre-projected xGA (expected goals conceded) value.

Data used: StatsBomb free API

Sample size: 3564 games

I collected and structured the data in jupyter notebook. Then my goal was to find the fitting function. My initial condition was the following: If a function like this exists, it must be in a^x form. Because we know the probability of 'surviving shots' is exponential, and f(0)=1.

So I took the log10 of each value. After that, the data points became linear, making it easy to fit a line on them. The slope was -0.557. Raising 10 to this power, we get the value of a=0.27723.

f(x)=0.27723^x

I'm perfectly aware it doesnt tell the whole story at all. For example, the saving ability of the keeper isn't taken into account. Or the usual xg/shot distribution of the opponent. (Do they take a lot of low xg shots, or are they a counter-attack team with few, but big chances?)

But i was curious if something like this could describe clean sheet odds. And for as simple as this, I think this can be a good starting point to work on some predictive models.

u/Next-Abbreviations76 — 2 months ago