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I'd say both times we played Alabama. We've been outscored 87-7. And that 7 was a garbage time TD IIRC.

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2 points · 1 day ago

I can’t see your flair, but I’m guessing this is MSU.

-18 points · 1 day ago

Awesome, Nebraska has big needs in the secondary. UCF, sorry, not sorry.

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1 point · 1 day ago

Ah, there’s the Husker I love to hate.

With the recruiting classes we’ve had and the ones we have coming in, I’m optimistic we can finally sustain some success at Auburn. I also feel like Gus is slowly getting better as a head coach (besides the debacle at LSU last season that I won’t discuss). And War Damn.

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18 points · 1 day ago

If /u/WalkingCarpet it correct, you just doomed Auburn football for the next 5 years.

I've watched it 6 times and it gets better each time

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67 points · 3 days ago

Every time I watch it, I yell at the announcers when they were unsure about Ertz's TD catch in the 4th. It was so irrelevant whether the ball popped out of his hands.

18 points · 3 days ago

I feel like WAR is great at what it does but it's terrible at dealing with outliers. And Coors is an outlier. I think it overrates how much Coors helps players, you still have to make contact with the ball.

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You have to keep in mind that WAR has error bounds around it, IIRC WAR can be +/- 1. Statistics are based on limited data and often have some indication of error due to limited data. That’s why you can’t use WAR to say that a 1.5 WAR guy is better than a 1.4 WAR guy, but you can confidently say that both of them are better than a Minor League call-up.

He plays at Coors so his 19Hr is less valuable than it looks -- his wrc+ is 114 so he's only 14% better than average at the plate.

His defense is dead last in value produced of all outfielders in baseball. And his baserunning is a minus.

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-1 points · 3 days ago

IIRC WAR is context neutral, so it factors out effects from things like stadiums.

4 points · 3 days ago · edited 3 days ago

They don't really apply here. They apply when you're trying to show the difference between a range of values in things like heat maps and so on. In this example the colour choice is purely aesthetic.

Edit: Another reason people are against color gradient's like this are because for people with colour blindness they make it hard to differentiate between values. In this case the colour looks fine for the different types of colour blindness.

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Only partly true. OP is communicating direction with color here, which is why I said it’s extraneous information. It’s not a deal breaker for the visualization, but it’s a good teaching opportunity regardless.

Original Poster13 points · 4 days ago

It's incredible how fast browsers and JavaScript have gotten over the recent years. Combined with carefully optimized libraries such as the ones used for this map, they can crunch a lot of data easily, even on a phone.

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It’s especially incredible considering how slow the previous Python script was for generating these plots. There must be some caching in your libraries.

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41 points · 5 days ago

I love how his teammate tried to knock him down again at the end.

3 points · 5 days ago

If you'd like to make your own "city street orientation" data visualizations, you can run the notebook in your browser on Binder - no local installation required.

Binder link

Run this line first:

!conda install -c conda-forge osmnx --yes
16 points · 7 days ago

beat Alabama in the championship

Impossible. Bama never lasts past the first few seasons.

2 points · 7 days ago

Dunno if this project is directly relevant to the ML subreddit as it’s not a ML project, but this project is a core part of the awesome http://mybinder.org service. It’s too cool being able to point that web site and any web hosted notebook and start executing code in it right from the browser, no installation required.

Lots of fun if you're a Tennessee fan because they had talent on that roster so you can see what might have been with good coaching and development.

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Tennessee is actually too easy of a “rebuild” IMO.

Nebraska

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2 points · 10 days ago · edited 7 days ago

Nebraska is pretty decent if you use 2013 rosters.

Original Poster14 points · 11 days ago

The Netherlands has broken the country's all time driest start of the summer since we started looking at droughts with satellites. We have not seen these levels in June on such a widespread scale in 40 years of satellite soil moisture observations.

In this case we looked at root zone soil moisture levels. The level where most crops get their water and nutrients.

VanderSat does not look at rainfall, but looks at the direct source: soil moisture, which is influenced only partly by rainfall. Some spots in the Netherlands need hundreds of liters of water per square meter to get back to normal levels.

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4 points · 11 days ago

Beautiful data viz. This data viz would be greatly improved by showing historical data as well, otherwise we have no sense whether this really is the driest June in the Netherlands (based on the data you present).

3 points · 13 days ago

I found left outfielder (LF) to be a good first position to play, with the “reliable player” (or whatever it’s called) focus. Relatively low stress position on defense, and still plenty of time at the plate to contribute on offense.

Starting Pitcher was fun, but it got brutal throwing for 7-9 innings every game. Very time consuming. Catcher is the same way. Maybe start out as a Closing Pitcher if you want to try pitching.

In either case, as you play and progress you’ll get free stubs on your main account. Use those stubs to buy cheap gear for your player on the Marketplace - you can get a decent set of gear for 500 stubs and all those bonuses really add up. Don’t do instant purchases - put up purchase orders for 1 stub above the highest purchase order and be patient.

How many stubs do you get playing RTTS?

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2 points · 12 days ago

I’ve gotten maybe 3k stubs playing over a 2 week period. Not a ton but enough to get you started.

Original Poster-7 points · 13 days ago

The early DD sounds more fun than the card collection game it’s become.

Original Poster2 points · 13 days ago

they should keep it goin, there aren't enough ways i feel like to make stubs in the game

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That’s on purpose so you give them your real $ for stubs.

2 points · 13 days ago · edited 13 days ago

Reminds me of a game I played recently where I went 0 for 3 against a pitcher, each time power hitting the ball into his groin. It would bounce right off and he’d make an easy out. Talk about balls of steel.

SCOTT STERLING!!!

unfortunately Pitching is likely the worst RTTS has to offer as far as career paths.

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Was about to say this. My RTTS pitcher also got stuck in AA despite excellent performance. My LF was called up to the majors halfway into his first year. There’s some strange logic going on there.

3 points · 15 days ago

Not sure what’s so special about this. Plays like this happen to me all the time in MLB The Show.

/s

This article does nothing at all to answer the question of whether BA/OBP might be improved by hitting in a particular place in an order, but rather assumes that a player with a particular BA will perform exactly the same no matter where he bats. So then it basically just comes down to chances. What would be an interesting statistical analysis would be to see if the BA of players who have batted immediately before major threats tend to have an up- or down-tick in hittable pitches from pitchers. I would guess that the results would skew up. Similarly, hitting in front of a pitcher (or terrible hitter) would make them skew down. This might be a case for batting faster, poorer-hitting players before pitchers and less-disciplined players who can hit in the strike zone before power guys.

While your simulation is rather simplistic, it could produce some interesting scenarios... I’d be interested to see if, instead of clones, a team of equally-distributed players would sim out best if in best-to-worst order or staggered somehow.

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Original Poster1 point · 16 days ago

Thanks for the feedback. Can you please explain what you mean by "equally-distributed players"?

Like, one of each BA:

.125 .150 .175 .200 .225 .250 .275 .300 .325

Or maybe 3 each of .150 .225 .300

Things like that. It’s more likely that a team will have some sort of distribution, rather than just one and a star.

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Original Poster1 point · 16 days ago

Gotcha. That makes sense. That's exactly what I'm planning next: Now that we know what happens when we have a team of clone players, let's see what happens when we start simulating more realistic teams with different player types. I also plan to make it so each player has their own probability of hitting 1B, 2B, 3B, and HR on a successful hit, and eventually add in stolen bases (successful and unsuccessful) as well.

6 points · 16 days ago · edited 16 days ago

Very cool! I've always wanted to see what a lineup-simulator code looked like.

plt.title('Earlier batters have more At Bats on average')

That should be "Plate Appearances" and not "At Bats". (Walks, hit by pitches and sacrifices are plate appearances that do not count as at bats). This explains much of the study too. The end of the game can occur at any point in the lineup so each lineup position is worth an extra 18 (=162/9) plate appearances per season. You don't want to give bad players extra opportunities.

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Original Poster2 points · 16 days ago

Good catch! Thank you for the feedback.

rhiever

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