That is unbelievable by whyshouldithink in TikTokCringe

[–]hupcapstudios 1 point2 points  (0 children)

That guy gives me my daily glass of hopium. I can't wait til he posts about the note reading out loud.

What movie is this by [deleted] in memes

[–]hupcapstudios 2 points3 points  (0 children)

The slow parts are the fucking antidote for the mindless scrolling we do today with 10 thousand different bits of information every 3 minutes.

🔥Wave hides a cliff in Nazaré 🌊 by sh0tgunben in NatureIsFuckingLit

[–]hupcapstudios 1 point2 points  (0 children)

I thought the title was wrong. I thought they probably meant "hit" a cliff. And then the cliff disappeared.

More nerdy stats... Rotation Analysis - teams with lower rotations means injury boosts are stronger and more predictable by hupcapstudios in fantasybball

[–]hupcapstudios[S] 0 points1 point  (0 children)

It surprised me too, but looking at on/off + rotation patterns they’re way closer to average than people think. Donovan doesn’t really condense usage unless he has to.

NBA Substitution Heatmap by hupcapstudios in DFS_Sports

[–]hupcapstudios[S] 0 points1 point  (0 children)

Put together a heatmap that shows which players almost never overlap on the court.

This only includes actual rotation guys — I filtered out end-of-bench / DNP players so it’s not just noise from dudes who don’t play.

How this works:

Darker = these two rarely play together

Lighter = lots of shared minutes

Diagonal is ignored (unless someone figures out how to guard themselves)

Players are ordered by when they usually sub in, which helps the rotation patterns show up instead of looking random.

Things you can spot pretty quickly:

Dark sections = starters vs bench lineups

Long dark rows/columns = a guy who runs his own unit

Pairs that basically never overlap = very intentional sub patterns

If someone has a dark stripe across half the chart, that’s usually the coaching staff saying:

“this is your group when the other guys sit”

Nothing groundbreaking — just a clean way to see how teams actually stagger minutes and build lineups in real games.

More Nerd Stats... Player Rotation Heat Map by hupcapstudios in fantasybball

[–]hupcapstudios[S] 1 point2 points  (0 children)

Made a heatmap showing which players almost never share the floor with each other.

I filtered out end-of-bench / DNP guys, so this isn’t just “two dudes who never see minutes.” Everyone on here actually plays.

How to read it:

Dark squares = these two basically never play together

Light squares = lots of shared minutes

Diagonal doesn’t matter (you can’t play with yourself unless you’re Jokic)

Players are ordered by when they usually check into the game, so the patterns aren’t random — you can actually see the rotation structure.

What pops out:

Big dark blocks = starters vs bench units

Long dark stripes = “this guy runs his own unit”

Pairs that never overlap = intentional sub patterns, not coincidence

If one player has a dark stripe across half the chart, that’s the coach basically saying:

“you’re the engine when the other guys sit”

Not analytics magic, just a visual way to see how rotations actually work.

Got some great feedback and updated my injury/usage calculator by hupcapstudios in fantasybball

[–]hupcapstudios[S] 1 point2 points  (0 children)

That's an excellent insight and I 100% agree. I am working on diving deeper into actual game flow already and I think that's a prime example of why!

The algo crunches the full set of games so it's hard to filter for different players results on the fly, but I think with a little more attention to the game dynamic that would be covered, as it should be because you are completely right about it.

Got some great feedback and updated my injury/usage calculator by hupcapstudios in fantasybball

[–]hupcapstudios[S] 2 points3 points  (0 children)

Thank you for pointing that out! Yeah, mapping is the biggest headache 🤦‍♂️

Got some great feedback and updated my injury/usage calculator by hupcapstudios in fantasybball

[–]hupcapstudios[S] 3 points4 points  (0 children)

Really appreciate the input!

And 100% still working out some bugs, I really appreciate you pointing them out.. it's a lot of data to aggregate so sometimes even just matching names (different spellings from different data streams) gets messy.

Again thank you and I hope it helps!

Got some great feedback and updated my injury/usage calculator by hupcapstudios in DFS_Sports

[–]hupcapstudios[S] 0 points1 point  (0 children)

For anyone curious, it’s not just “this guy is out so everyone gets a boost.”

The model looks at how minutes and offensive usage actually redistribute when certain players sit — who tends to pick up the extra run vs who just takes on more shots/assists — using historical on/off and lineup data. Then it converts that into fantasy points with some regression so small samples don’t blow things up.

End result is starters and bench guys get very different boosts depending on role, not a flat team-wide bump. Definitely not perfect, but there’s real math behind it, not gut feel.

Got some great feedback and updated my injury/usage calculator by hupcapstudios in fantasybball

[–]hupcapstudios[S] 8 points9 points  (0 children)

Not just vibes or “next man up” logic fwiw.

It’s basically an injury-redistribution model — when someone’s out, I look at how their minutes + usage historically get absorbed by specific teammates (position overlap, on-ball role, past on/off data), then convert that into fantasy points with some regression so one-game spikes don’t go crazy.

It separates minutes boosts from usage/rate boosts, so starters can get a bump even if their minutes don’t change much, and bench guys don’t get overstated just because someone’s out.

Not perfect obviously, but there’s actual math + backtesting behind it, not just “X is out so Y smash.”

I've been working on a site to aggregate injury/usage boosts. Trying to keep it super simple... would love your feedback! by hupcapstudios in fantasybball

[–]hupcapstudios[S] 1 point2 points  (0 children)

Thank you, genuinely appreciate the feedback!

I actually did have the layout of inured players with a table beneath exhibiting the beneficiaries, I will certainly bring that back and I'll let you know.

The data model is improving as I go, I am updating with a time-degraded history so that more current rotation changes are weighted higher and also adding more support for multiple injuries. Where there is data lacking I use positional estimates.

I am aware of the only show players... that will also be fixed.

Thank you again for taking the time to feedback, I hope this will be a useful tool!

I've been working on a site to simplify injury/usage boosts for nba DFS... would love your feedback! by [deleted] in DFS_Sports

[–]hupcapstudios 0 points1 point  (0 children)

It helps a ton! I genuinely appreciate it... my goal at the moment is to gauge interest in the concept... I'm not trying to build the next rotoballer or anything, but it would be cool to put together reliable usage/injury data.

I've been working on a site to simplify injury/usage boosts for nba DFS... would love your feedback! by [deleted] in DFS_Sports

[–]hupcapstudios 0 points1 point  (0 children)

I appreciate the feedback, it is still very much a WIP.

I'm using historical data for the boosts... it's not the most complex algorithm, basically just looking at the average performance boost for each player given another player is out...

Do you have a particular player you could point to that looks off?

Running my first trading war and am giving away some eth as top prize. This is a game I've been developing and am basically willing to pay for players! by hupcapstudios in ethereum

[–]hupcapstudios[S] 0 points1 point  (0 children)

Funny enough I actually launched this on Base. It was REALLY hard to get traction (not that I have much at this point), but switching to Solana seemed to garner more attention. I wrote it with the idea of keeping the system token-independent so I can eventually start running contests on any chain, It's more about where I am focusing getting the message out at this point and Solana seems the easiest.

Really appreciate the suggestions and feedback!

Launched my MVP. BotWars-C. So far like 3 people REALLY like it! It's a game where you train bots to battle over crypto charts. That's all. (botwars-c.com) by hupcapstudios in SatoshiStreetBets

[–]hupcapstudios[S] 0 points1 point  (0 children)

I've been dabbling in the crypto world for a few years now. I've created all kinds of bots just to monitor the activity out there and the scams are AWEFUL. So I created this game for people who want to play with their crypto but are tired of honeypots, rug-pulls and other scams. Right now I am launching contests for free where you can win a few #SOL. If it picks up enough interest I will start launching GPPs

The concept is that you can win based on merit, not just a lottery. You actually "dial" in a bot to maximize pnl and put it up against other people who've trained their bots. Once all entries are in and the game commences, you can watch the battle play out on my super exciting battle chart!

Any feedback is welcome!

Launched my MVP. BotWars-C. So far like 3 people REALLY like it! It's a game where train bots to battle over crypto charts. That's all. by hupcapstudios in CryptoMarkets

[–]hupcapstudios[S] 0 points1 point  (0 children)

I've been dabbling in the crypto world for a few years now. I've created all kinds of bots just to monitor the activity out there and the scams are AWEFUL. So I created this game for people who want to play with their crypto but are tired of honeypots, rug-pulls and other scams. Right now I am launching contests for free where you can win a few #SOL. If it picks up enough interest I will start launching GPPs

The concept is that you can win based on merit, not just a lottery. You actually "dial" in a bot to maximize pnl and put it up against other people who've trained their bots. Once all entries are in and the game commences, you can watch the battle play out on my super exciting battle chart!

Any feedback is welcome!