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Professional Auto Trading EA Robots & Indicators For Forex, Stock, Binary Options, Bitcoin Trading submitted by elena_avr to altredo [link] [comments]

A rant

I think I'm at the point where playing the sims is more frustrating than enjoyable. I pre-ordered the sims 4 in 2014 and barely played it for 4 years because it sucked so hard upon release. I got back into it last year after buying the city living and get famous packs. I got a lot out of them but at the same time I got get to work and only use it for build mode. A few months ago I decided to try CC (I was always scared of crashing my game even though I have a chonker of a gaming computer, idk I guess I thought it was sketchy) and really found a zest for building again but things like stairs and roofs make it endlessly annoying. For the most part I can't download from the gallery, I only have 3 expansion packs and laundry day so most of the houses I download end up looking like shit and there's nothing I can really add to fix it. It's almost more work to fix up a download then to build a house from scratch. (Why do they give us the option to deselect packs when we search but it still gives me everything under the searched tag?)
CAS gives me dysphoria. I think we were all excited when they announced that clothes work for all genders now but the strict binary they inforce kills me. No facial hair for "female" bodies, no breasts for "male' bodies, there's no actual option for androgyny. I thought downloaded CC would help with this but I didn't realize most CC only works on one body type. I'm not blaming the CC creators for this.
I'm not going to even go into gameplay because there's nothing to do. I won't spend $500+ dollars for gameplay that's only playable once, if that. I also find it insulting that EA says they won't give us content because we don't deserve it. I will not smile while being forced to eat ashes, I will not play with elders until they give me a reason to play with them.
I think a lot of the creator content in sims 4 is incredible but I can barely get through a session anymore. Idk if it's cause SI has made me more negative and really highlighting all the things that have been frustrating me since forever or if I'm just finally getting fed up but I'm close to never playing again.
submitted by chubgothic to Sims4 [link] [comments]

A comparison of 7 visual story apps: Choices, Arcana, Lovestruck, Chapters, Romance Club, Journeys, and Storyscape!

This is an update to my previous post comparing visual story apps, but comparing three more apps! Romance Club, Journeys, and of course Storyscape.
These seven games are:
Since all of these apps have different names for the same things, I tried to standardize the terminology...
Choices: Stories You Play The Arcana: A Mystic Romance Lovestruck: Choose Your Romance Chapters: Interactive Stories Romance Club: Stories I Play Journeys: Interactive Series Storyscape
Release Date (App Store) 8/17/2016 10/22/2016 3/1/2017 10/27/2017 3/7/2018 8/22/2019 10/22/2019
App Store Age Rating 12+ 12+ 17+ 17+ 12+ 17+ 17+
Passes are Called Keys Keys Tickets Tickets Tea Tickets Tickets
Maximum Number of Passes 2 3 2 2 2 2 2
Pass Regeneration Rate 3 hours 4 hours 2.5 hours 2 hours 2 hours 2 hours 2.5 hours
Gems are Called Diamonds Coins Hearts Diamonds Diamonds Diamonds Diamonds
MC Visual Customization? Yes No No Yes Yes Yes Yes
MC Gender Majority female (several stories have male options) Male/Female/Non-binary Female-only Almost all female (1 male-only story) Female-only Female-only Almost all female
LI Gender Majority male (all but 1 story have at least 1 female LI) 3 Male, 2 female, 1 non-binary Male/Female (new releases are 50/50, 2 non-binary) Almost all male (2 female LI stories) Male/Female Male/Female Male/Female
Character Animations? No No No No No Yes Yes
Watch Ads to Earn Gems? Yes Yes (beta) No Yes Yes Yes Yes
Play Games to Earn Gems? No Yes No No No No No
Check-in Daily to Earn Gems? Yes Yes Yes* (daily puzzle piece) Yes Yes No No
Play Chapters to Earn Gems? Yes No Yes* (Romantic Quests) No Yes Yes Yes
Rate Chapters to Earn Gems? No No No No No Yes Yes
Number of Unique Series 35+ 1 (6 books) 14+ 100+ 7 12+ 4+
Series Types Both continuing series and stand-alones 1 continuing series Almost all continuing series (several stand-alones) Almost all stand-alones (two continuing series) Both continuing series and stand-alones Both continuing series and stand-alones Both continuing series and stand-alones
Average Chapters in Book ~15-18 22 (full) 12 (19 for earlier books) ~18-20 10 ~15 ~10-17
Average Choices per Book ~10-15 ~7-15 ~3-6 ~7-15 ~15-19 ~4-7 ~10-15
Can You Collect CGs? No* (they exist, but you can't collect them in one place) Yes Yes Yes (character cards) No No No* (they exist, but you can't collect them in one place)
Do Choices Affect the Story? Yes Yes (upright/reversed endings) No* (some older books have thrilling/passionate endings) No Yes Yes Yes
Are Series in Same Universe? Yes Yes Yes No No No No
Parent Company in: Korea (US Subsidiary) USA Japan (US Subsidiary) China (US Subsidiary) Moldova Argentina (?) USA

MC Customization

LI Choices

Earning Passes/Gems

Gameplay

Interface

History & Background

Demographics

Here's a chart by gendesexual orientation for which game gives you the most options / fits a particular demographic best in my opinion:
Gender x Male LIs x Female LIs x Non-binary LIs
Female All apps but esp. Chapters Lovestruck, Choices, Storyscape Lovestruck
Male Choices, Arcana Choices Arcana
Non-binary Arcana Arcana Arcana

Similarities

Here's how I would group the games according to similarity.
As a last word, it's kinda cool that for Choices, Storyscape, and Romance Club their developers have all been on and done stuff with their Reddit communities. Romance Club even has a link to the subreddit in the app! The other apps are slacking on this.
Agree, disagree? Tell me!
submitted by kori_no_ryu to Choices [link] [comments]

A comparison of four visual story apps: Choices, Arcana, Lovestruck and Chapters

I decided to write up a chart comparing four of the visual story games I've played and how they compare in some respects. Not going to try and judge the writing quality of the games, while Chapters is obviously the least-quality on this metric I'll leave it to everyone to decide quality among the other three. I'm not trying to rank any one as better than the other! I think it should be pretty evident from my comparison that all of them have strengths and weaknesses.
There are a couple more games coming out (Storyscape is probably the most anticipated one) but they're still changing things so I didn't include them. I also didn't include Episode because I honestly have no clue which stories are featured / written by their team and I know most people don't play the "official" stories anyway, so it's kinda pointless to compare.
These four games are:
Since all of these apps have different names for the same things, I tried to standardize the terminology...
Choices: Stories You Play The Arcana: A Mystic Romance Lovestruck: Choose Your Romance Chapters: Interactive Stories
Release Date (App Store) 8/17/2016 10/22/2016 3/1/2017 10/27/2017
App Store Age Rating 12+ 12+ 17+ 17+
Passes are Called Keys Keys Tickets Tickets
Maximum Number of Passes 2 3 2 2
Pass Regeneration Rate 3 hours 4 hours 2.5 hours 2 hours
Gems are Called Diamonds Coins Hearts Diamonds
MC Visual Customization? Yes No No Yes
MC Gender Majority female (several stories have male options) Male/Female/Non-binary Female-only Almost all female (1 male-only story)
LI Gender Majority male (all but 1 story have at least 1 female LI) 3 Male, 2 female, 1 non-binary Male/Female (new releases are 50/50, 2 non-binary) Almost all male (2 female LI stories)
Watch Ads to Earn Gems? Yes Yes (beta) No Yes
Play Games to Earn Gems? No Yes No No
Check-in Daily to Earn Gems? Yes Yes Yes* (daily puzzle piece) Yes
Play Chapters to Earn Gems? Yes No Yes* (Romantic Quests) No
Number of Unique Series 35+ 1 (6 books) 14 100+
Series Types Both continuing series and stand-alones 1 continuing series Almost all continuing series (several stand-alones) Almost all stand-alones (two continuing series)
Average Chapters in Book ~15-18 22 (full) 12 (19 for earlier books) ~18-20
Average Choices per Book ~10-15 ~7-15 ~3-6 ~7-15
Can You Collect CGs? No* (they exist, but you can't collect them in one place) Yes Yes No
Do Choices Affect the Story? Yes Yes (upright/reversed endings) No* (some older books have thrilling/passionate endings) No
Are Series in Same Universe? Yes Yes Yes No

MC/LI Choices

Earning Passes/Gems

Gameplay

Stories & Genres

Genre Choices Lovestruck Chapters
Action The Heist: Romance, Most Wanted Gangsters in Love, Villainous Nights Bad Boy Blues
Fantasy The Crown & The Flame, The Elementalists Love & Legends, Reigning Passions Robin Hood
Historical A Courtesan of Rome, Desire & Decorum Speakeasy Tonight 50 Ways to Ruin a Rake
Horror It Lives Series N/A N/A
Mystery Veil of Secrets Castaway Dirty Little Secrets, Uninvited
Paranormal Bloodbound, Nightbound Havenfall is for Lovers Lux, Love at Stake
Science Fiction Across the Void Starship Promise Court of Nightfall, The Wandering Earth

History

Demographics

Here's a chart by gendesexual orientation for which game gives you the most options / fits a particular demographic best in my opinion:
Gender x Male LIs x Female LIs x Non-binary LIs
Female All apps but esp. Chapters Lovestruck, Choices Lovestruck
Male Choices, Arcana Choices Arcana
Non-binary Arcana Arcana Arcana
Let me know what you guys think, and if you can add another app to compare let me know too...
submitted by kori_no_ryu to Choices [link] [comments]

Mass Effect: Andromeda Story Rewrite

So, Mass Effect: Andromeda...

Disappointed would be a very good start to describe just how I felt about the whole game and its potential. Having replayed it to the point where I got the platinum trophy and nearly a level eighty Ryder, I feel like the game itself is good and fun. The new combat feels far more fluid and is a significant change to the corridor shooters of Mass Effect 2 and 3 and the addition of the jet pack was definitely fun for when I wanted my BroRyder to look like Tony Stark and my FemRyder to look like... Well, Toni Stark I guess. The new powers were fun and the way you could chain combos together really made you feel like you were commanding the team and the wins of the group were due to you and your tactical mind something I felt was missing for Shepard's combos.

The big point I think we were missing with Andromeda was the story though. The main group of characters were fine and they could all compliment one another and your Ryder but I feel like they could have been more. If we use Mass Effect 1 as an example, we have a group of six soldiers for squad mates and out of those six, four of them are aliens and brand new characters and people for us to discover as we played the game. So, with Andromeda, we got a similar squad size but out of the six, we only get one new race to fully explore. This is the first big thing I would change in the game and the way it is set up, the only thing I would change with the main game, and what is coming up in the story, (Ooh spoilers!) is that I would ditch Liam, purely because I like him the least, and add in a kett companion.

Crazy idea right? But no more crazy than adding a geth into Shepard's suicide squad in my opinion.

I actually think the starting point of Andromeda, strange faces and all, is really good. I love how the Arks look and the lived in, Star Trek type feel that it shows off. The sibling being taken out of the game right away is also a really fun point that instantly humanises your Ryder and gets you into their shoes. I mean, I can't imagine what it would be like having any of my brothers be stuck in a coma but I'm sure I would be a total mess and we need to see that be more of a deal for Ryder because I feel like in the main game everything just sort of falls into place as a set of lucky coincidences and as soon as the human Ark docks with the Nexus we don't see our new Citadel in the beat up shape it was in when it first arrived and the lights are on and all of the systems are working again.

I think seeing a beat up Nexus would be a good, interesting point especially if you levelling the Nexus up could actually affect the game and story. This is something I always enjoy doing in games myself and seeing it be a thing in my game would really make me happy. Imagine levelling the military aspect of the Andromeda Initiative and when you next dock the Tempest, there are more armed guards littered around the Nexus, or you put some points into the merchants and trading deals and inside the main lobby of the Nexus you can see more stalls popping up and offering you more things to spend your hard plundered credits on.

Back to the story, I think the first couple of missions with the Ark and then landing on Habitat 7 were really fun but this was where the first story misstep happened. I, personally, would keep SAM being able to help fix the remnant tech and help bring the viability of a damaged planet as a thing but I would also give it more of a consequence. The kickback won't be the cause of death for Alec Ryder but it will break his back and put him in the state where Alec Ryder has to transfer the rites of Human Pathfinder to his son/daughter and the player character. Cora, will stay the same as she is, annoyed at the fact that she was passed up but eventually will grow to accept that Alec was right to give the title to Scott/Sara and she worked a lot better as the second in command.

So, after dealing with Habitat 7 and arriving at the broken down Nexus, Alec Ryder and Scott/Sara Ryder are introduced to the main characters of the Nexus, Addison's tired face is probably not going to be a thing though. Sorry memers. Once that is through, we have something of an idea that the possible liveable worlds do exist out there and the possibility of the Initiative doing something now that they are in Andromeda and now they can live somewhere inside of Heleus. I would also use this point to ensure that the game only takes place inside of the Heleus Cluster and there will be no jumping from system to system.

I get why they decided to give us an entire new galaxy to explore but inside of this galaxy there are only three other new species to discover? That seems very unlikely to me personally. We could go one of two ways here in saying that there was some sort of galactic genocide that wiped out most of the life in Heleus but I think that sounds a lot like the Reapers and with what I'm planning, we already have another nod towards the original trilogy so let's go with the second option and just lock the first game of Andromeda into one single solar system and maybe give it a second sun to make it look more science fiction-ey.

So, while the planets Eos, Voeld, Havarl and all the other planets you needed to hit 100% viability on will basically have the same story, the main story missions like the Archon's ship and hitting the centre on Voeld will be significantly different. I think one of the issues I had with the game was just how quickly the game adapted to humanity and the rest of the milky way inhabitants got to be in control and be such a big part of Heleus and as invaders essentially, we should be treated with significant caution.

So, one of the big points I'd make with Andromeda, since we're only dealing with the Milky Way aliens and then the additions of the two Andromeda species in the kett and angara we should really focus on those last two and make a big deal with them. I would use the mission on Voeld with the kett holding centre being the main launching point for the big point for the story. At this point in the main game, Jaal, or whoever is the angaran squad member, will be forced to be a part of Ryder's team to assault the centre. This is going to be important later. The mission plays off as it does in the main game, complete with the team finding out that the kett are genetically modified angara and that is why the kett are stealing angarans and also why several Milky Way species have gone missing as well.

The team gets to the end of the centre and having kicked the crap out of the Cardinal in the exaltation facility, we get a lovely little exposition chat from him but we get one important detail.

Cardinal: Tell me Pathfinder, just what have the angaran told you about our war?
Ryder: They told me enough. They told me that you are bullies, picking on them because they weren't interested in fighting back.
Cardinal: Is that what they said? Let me tell you-

The Cardinal is then shot through the head by an off screen gun, the camera reveals that the shot was fired by the Moshae who has a knowing look on her face. She lowers the gun and greets Jaal and the Pathfinder, the team leave the exaltation facility, bombing the whole place or leaving it up so that the Milky Way can offer more good faith in ferrying out the mind wiped angaran and other species who were ready for the exaltation process.

The story moves on to Havarl with the intention to clean it up and free it so that the angaran can move back there as well as using Aya as their species capital. Moving through the planet and doing plenty of side missions such as finding the lead on the turian ark and whatever, the final big mission on Havarl is an encounter with a huge team of Kett soldiers, I'm thinking a massive fortress type of thing. As you clean through the fortress, you find that the leader of the building has vanished and you are left with a computer and one blinking light. Activating the console, you find that the kett have left you an AI message that offers up some very interesting details involving the angara and kett. The information suggests that the angara and kett used to be very close and the whole reason why so many of them are so closely related. The kett are suggesting that the angara have a secret that they don't want to let out into the galaxy because they are ashamed of it.

Taking the information back, Ryder and the team discuss what the next plan is when Kallo lets Ryder know that they have a waiting video-call. Ryder dismisses the team, or rather, they dismiss themselves, and Ryder takes the call. Looking at the screen, Ryder is amazed to see the Archon himself looking at them. They have a conversation and the Archon lets Ryder know that he wants to discuss peace terms with the Moshae but he wants to make sure that things are legitimate. So, he is sending over one of his own people who can be picked up at a certain location. Picking up the kett squad member, the tension between the kett and the angaran squad member should come off as very obvious.

Moving on to Elaadaan or Kadara, there are a couple more missions before the big story mission comes up. The kett and angara have decided on a location for the possible peace talks and they want it on neutral ground. The Nexus. Ryder and the Tempest return and we can already see that the Nexus is starting to look more alive and as they disembark, they are greeted by Alec Ryder who is in a sort of Christopher Pike style wheelchair but he has a smile on his face at least. The two walk together and towards the elevator that will take them to the peace talks room near the bottom of the space station and as they move, Alec talks about how he failed the Ryder siblings and how he was so focused on saving their mother, he completely ignored his children. He basically apologises and says he is so proud of the Ryder Pathfinder. Ryder has the dialogue wheel choice that probably looks something like this.

[Humour] I guess this is a good time to ask if we can go trick or treating then?
[Good] Thanks dad, I appreciate it.
[Heart] I love you dad.
[Anger] Little late for twenty six years dad.

When the Ryders get to the peace talks, they can see that the angaran and kett are already spending their time scowling at each other and skulking up and down the long conference table and not threatening each other but they might as well be. When the Ryders arrive, the conference gets going and progress starts to be made right up until one of the kett mentions the two coming together again.

The peace talks start to break down, angry words start to be exchanged and while Alec tries to calm them down, one of the angaran breaks out a weapon that they smuggled into the talks and opens fire on the kett. Killing the entire kett peace talks team as well as wounding the Archon, the angara are ready to wipe them out completely when the Archon speaks. His head rolls to the side and he looks over to Ryder, his eyes wet and tears streaking down his cheeks as he coughs and splutters.

Archon: Ryder... We are guilty of the crimes they have accused us of. We only did it though because of what they did to us. All we wanted was to live, we wanted to please our masters and serve them. All we wanted was for them to be happy and to let us live. Our people worked to put them on the pedestal they believed they should be on and when they changed their minds, they tried to execute us. Our scientists found a way to make their dead work for us. The angara glassed our home world, they shot our children in their nests and they murdered our elderly and infirm. What the angara did to us was not an act of war, it was a massacre. So, we defiled their dead and it changed the war. It made us stronger and we were able to fight back. Those cowards realised that the war was changing and started to give worlds up to us. Just in time for you to arrive and fight their war for them. Ryder, please, I beg you... If I do die here at least make sure that my people live. Do not buy into their lies any more.

So, a little bit of a copy from Vegeta’s confession in the Frieza saga of Dragon Ball Z, and by a little bit, I of course mean a total copy. It’s not my stuff admittedly, but I think it could be an interesting take on the whole classic angle of ‘We hate these people because of reason x, y or z’.

So, with that revelation, Ryder is left on the Tempest with the crew assembled and the kett and angaran squadmates being kept apart by force if necessary but there is definite tension in the air and the two are staring daggers at each other. Here, Ryder really starts to stand out as a leader of their people and makes sure that both members of the team are aware that if they are going to be staying on the Tempest they have to behave themselves. As the discussion is sort of stalling, Kallo lets the Pathfinder know that there is a message coming through from the kett command. Ryder dismisses the crew and takes the call, it’s then that Ryder finds out that the kett are going to be moving together to take the

Binary choices:
The first outpost on Eos Military or Scientific?
Siding with the kett or angara?
Killing the other alien member of the team or letting them live?
Who do you take to the bone zone?
How does the galaxy look when the final fight is over? Are we setting up a democratic union or is Heleus in need of an iron hand?
Does the Nexus accept the survivors of the angara or kett with regards to an embassy or are they to stay in orbit of the station?

DLC

Because this is EA we're talking about so of course they’re going to monetise my thoughts.

£3.99/$4.99 Pack #1: Ryder Snr's training wheels programme
A short pack with this one, a new set of weapons, an armour kit and a fun new member of the squad in your sibling joining the team. This will be a series of horde mode where you get a ranking based on how you, and your team, does in the challenge. If you manage to reach level twenty or hit a specific points threshold then you will be granted the rank of N7, just like Alec Ryder and you get another feather in your cap as well. This could be played at any real point in the game but would only activate after both the angaran and kett join the team.

£7.99/$9.99 Pack #2: Two minutes to midnight
So the first story pack. This is going to expand the story on what's been happening with the remnant, where they went and what they were doing. The story comes out that the vaults are all linked for one specific reason and while they can transform a planet into a brand new, liveable biome, they can also destroy. SAM has been working on some specific algorithms with some of the brightest minds on the Nexus and they have worked out that there is a countdown and it is coming sooner than any of them would want. With a new moon area to discover, the team find out that the countdown is leading to the return of an alien race that wishes to reset anything that is incorrect in Heleus. Incorrect such as five planets being terraformed to a brand new setting. This would really lead to Andromeda 2 and the arrival of what could be the Andromeda equivalent of the Reapers and gives everything in Heleus something new to want to kill. There wouldn't be any new weapons with this pack, maybe add some remnant gear in to spruce it up though. This would be played, ideally, just before the final encounter though could also be played any other time too.

£7.99/$9.99 Pack #3: The final piece
The DLC we all thought we were going to get. I would lead with there being geth stowaways on board and that was what set off the fights on the ark. When we receive the news of the ark, we only know that the ship is in trouble. So, the crew dock with the ark, get the news that there are geth stowaways and maybe add some batarians or vorcha in so the team has something else to kill. One other point I would make about this DLC is that we actually get a canonised face for the quarians. Make up some scientific mumbo jumbo about the time spent travelling to Heleus has strengthened their immune system or something. This is the only other DLC that I would put some choices involved in.

Do you:
Use stun rounds and move forward non-lethally or use full force?
Let the troublemakers stay or do you exile them?

Okay... So this is definitely a lot longer than I thought it was going to be. I guess let me know what you think, whether you agree, whether you would change something or if you just wanted to chat about Mass Effect Andromeda too I would be more than happy to discuss it!
submitted by MeanBlackjack to masseffect [link] [comments]

[GUIDE] Name changing trick

Before I begin I wanna say sorry for the huge wall of text.
Also, instead of making a TL;DR, I've simply made a list of things you should read/skim over to get the gist of it:
  1. Introduction.
  2. Basic codes.
  3. Fade/opacity codes.
  4. "Special" codes.
  5. Codes that allow profanity.
  6. Combining codes.
  7. Final words.
  8. nsFAQ.


Introduction:

Hello Blazing players, today I will talk about something that quite a few of you might already be a little familiar with, the name change trick.

You might've played PvP and matched against someone with and underline in thier name, or thier name is written in italics.
Well today I've done some (in my own opinion) extensive testing with the name changer and it's codes.

  1. Go into the game settings and press on "Change Name".
  2. Type in a name you like with 5, 4, 3 or less characters, depending on the code you want to use (this is because of the 8 character limit in your name).
  3. After typing your prefered name, select a place in your name where you would like the effect to start from.

  1. Select any mission you can play in multipler, and press on "Gather friends".
  2. When you're in the pre-lobby, press on "Room settings" in the top left, and then press on the lowest text input field.
  3. Type your message.

In this example I'll use the names "Obito", "Neji" and "Lee" for the 5, 4 and 3 letter names respectively.
How this works is that you use what is called "BB code" codes to give effects to your name.
I will split these tables outlining the codes into sections;
  1. Basic codes (5 or less characters in name).
  2. Fade/opacity codes (4 or less chacaters in name).
  3. "Special" codes (3 or less characters in name).
  4. Weird codes (Varies in lenght, but the shortest one is 1 character, so 5 or less character name).
  5. Codes that allows profanity (Codes we already talked about, but how they can be used).
  6. Combining codes (Varies in length, but the shotest only allows you to have 2 or less characters in your name).
  7. Fun names you can use if you want to (the names obviously uses the codes I've mentioned here).
  8. Full list of fade/opacity codes - because english isn't my first language I don't believe in my own ability to get information across.
  9. Imgur albums with examples of all the mentioned codes.
  10. Final words.
  11. nsFAQ (edited in after posting).

1. Basic codes:

The first table is the basic codes, i.e the codes that are the most well known in the community, and consist of only 1 letter in the code.
You will need 5 or less characters in your name.

Name Code Usage Result
Bold [b] [b]Obito Obito
Italics [i] [i]Obito Obito
Underline [u] [u]Obito See Imgur album
Strikethrough [s] [s]Obito Obito

These are the codes/names you've most likely run into at some point playing the game since they are the most common and well known codes.
On a sidenote, I wanna mention that when you're on your homwscreen, then the code will be visible in your name (this goes for all codes), but don't worry, because in PvP and such it will still look differentand without the code looking horrible in your name.

Imgur album with examples: Album


2. Fade/opacity codes:

IMPORTANT EDIT at the bottom of the section!
The second table is the fade codes, i.e the codes that make your name "fade", or as normal people would say, it makes your name's opacity lower than original (transparent).
You need 4 or less characters in your name.

Now, these codes are a little special.
Have you ever been up against someone in PvP with an opaque name, and it turns out the have [69] in thier name?
Well, the 69 code is just a tiny part in the section that is opacity codes.
Let's get into the table first, and I'll then explain further afterwards.
The table doesn't have a "Result" column since Reddit doesn't have a feature for text opacity.

Name Code Usage
Regular 1-9 opacity [01-09] [05]Neji
Regular 10-99 opacity [10-99] [55]Neji
Fancy a-f opacity [ax-fx] [af]Neji

These are the name opacity codes.
The opacity codes work in such a way that the higher the number, the less opacity, meaning that a name with [90] will be less transparent compared to a name with [10].
A sidenote to the statement made above, is that the code [01-05] makes your name pretty much completely invisible, and [05]-[08] makes it almost unreadable.
Don't think you can use this to cheat, people will be able to see your full name and will be able to report after a match is done in PvP.
The two "regular" opacity codes are conected, it's just that you just put a [1] and it'll work, no, you have to put a zero (0) in front of single character numbers, which is the reason why I separeted them in the table above.

The "fancy" opacity codes is a little special in that it's basically an alphabet, but with everything beyond "f" removed, but also because they are the ones that adds the least total ammount of transaprency to your name.
Let me explain; we all know the alphabet, and we all know that "g" comes after "f", however not in this case., so basically just go up to "f" and then go to the next letter.
So a little quick list would be that you start with the code [aa], and then the next one is [ab], then [ac] and so on, until you get [af], after that you move on to [ba], then [bb] and so on. This means that the last code here will be [ff].
I will add a full list at the bottom of the post in case you still don't understand.

Imgur album with examples: Album

EDIT:
Due to the findings of user iramd24, I have done a little more testing, and can now confirm his statement:
"Since the opacity code goes from 01 to ff Im pretty sure It is hexadecimal instead of numeric and alphabetic so you could probably use the codes [b8] or [4e] for example I can't test It right now but following that logic it should work"
This means that they aren't split into numeric and alphabetic sections, but rather everything is linked.
I can confirm that he is indeed right (Full code table at the bottom has also been updated):

(Codes go from 0 to 9, and then it goes from A to F, meaning that one section is 00, 01, 02, 03, 04, 05, 06, 07, 08, 09, 0a, 0b, 0c, 0d, 0e and 0f, after that we start over, but add a 1 where the 0 was, so it would be 10, 11, 12... all the way up till 1a, 1b, 1c... which is repeated for each section, for the alphabetic codes you simply do the same; a0, a1, a2... all the up to f0, f1, f2...).
Hopefully this is understandable, but look under the section "Hexadecimal (base 16)" on this website for reference.



3. "Special" codes:

The third table is the "special" codes, i.e the codes that can give your name a "to the power of 2" aesthetic.
You will need 3 or less characters in your name.

Name Code Usage Result
Subscript [sub] L[sub]ee See Imgur album
Superscript [sup] L[sup]ee Lee

Now, there's not too much to say about these, they're just pretty cool to have, and they also looks the nicest when having a 3 letter profanity word in my opnition.

Imgur album with examples: Album


4. "Weird" codes:

The fourth table is the weird codes, i.e codes that's doesn't seem to do anything, but still works (or codes that just can't do anything due to the way the name changing and name displaying is set up).
At the time of writing this I've only found one, which is a one character code, however I'll update the table if I find or are made aware of any more.

Name Code Usage Result
??? (Seems to labeled as "code snippet") [c] [c]Obito ???

The first one I've found seems to labeled as a code snippet on this website, which then makes sense as to why it doesn't work.

Imgur album with examples: Album


5. Codes that allows profanity:

The fifth section is the profanity allowence codes, i.e codes that allows players to have banned words in thier name.
I'm gonna use something mild in this section.
This section feels sort of unnecessary in my own opinion, but hey, it's kinda funny to have your name as "Ass", right?

Well instead of having a table outlining how to do it exactly, I'll just tell you that you should just put the code in the middle of the banned word and then you can use it, along with a few examples.
Let's use "Ass" as an example once again.

Name Code Usage Result
The fancy ass [i] A[i]ss Ass
Subscript Ass [sub] A[sub]ss See Imgur album
Superscript Ass [sup] A[sup]ss Ass

I still don't know why "yeet" is a banned word :/

Imgur album with examples: Album


6. Combining codes:

The sixth section is the combining of codes, i.e codes that you can combine to make a name look nice with 2 effects.
Like with section 5 above, I'm not gonna outline everything since there is an endless amount of possibilities for you to combine codes and make a nice name.
In this section I'll use "xD" as an example, because I'm cringe like that.
And I'll just use "D" in the last example.

Name Code Uasge Result
Bold + Italics [b] + [i] [b][i]xD xD
[u]Underline[/u] + Italics [u] + [i] [u][i]xD See Imgur album
Transparent + strikethrough [s] + [69] [s][69]D D (image the text being transparent a bit too)

You can combine any 2 previously mentioned codes to make a nice looking name, altough the only real viable option is to use two of the single character codes, because then you can get a 2 character name.

Imgur album with examples: Album


7. Fun names you can use:

Now what is a guide about names without a section of free to use names? Well it's still a guide, but it's lacking that last section, like a frozen pizza is missing that jazz.
This is a list of names I made (only 2 at the time of writing this) that you can use freely if you want to.

Name Code used Usage Result
Hidden Rain village rouge ninja headband [s] [s] Try it yourself!
Triangle [u] [u]/\ Try it yourself!

Don't judge, I'm not the most well versed guy in what other people like and find "cool", so, yeah.


8. Full list of fade/opacity codes:

Please note that the table to supposed to be read from the left most column, all the way down, and then move one column to the right and repeat.
EDIT:
This table has been updated due to new information being found by user iramd24, to now include all the Hexadecimal values you can use (it was quicker to write that it looks, I promise).
This table takes the values from this website, look under the section "Hexadecimal (base 16)" for reference.
Section 0 codes Section 1 codes Section 2 codes Section 3 codes Section 4 codes Section 5 codes Section 6 codes Section 7 codes
[00] [10] [20] [30] [40] [50] [60] [70]
[01] [11] [21] [31] [41] [51] [61] [71]
[02] [12] [22] [32] [42] [52] [62] [72]
[03] [13] [23] [33] [43] [53] [63] [73]
[04] [14] [24] [34] [44] [54] [64] [74]
[05] [15] [25] [35] [45] [55] [65] [75]
[06] [16] [26] [36] [46] [56] [66] [76]
[07] [17] [27] [37] [47] [57] [67] [77]
[08] [18] [28] [38] [48] [58] [68] [78]
[09] [19] [29] [39] [49] [59] [69] [79]
[0a] [1a] [2a] [3a] [4a] [5a] [6a] [7a]
[0b] [1b] [2b] [3b] [4b] [5b] [6b] [7b]
[0c] [1c] [2c] [3c] [4c] [5c] [6c] [7c]
[0d] [1d] [2d] [3d] [4d] [5d] [6d] [7d]
[0e] [1e] [2e] [3e] [4e] [5e] [6e] [7e]
[0f] [1f] [2f] [3f] [4f] [5f] [6f] [7f]

Section 8 codes Section 9 codes Section a codes Section b codes Section c codes Section d codes Section e codes Section f codes
[80] [90] [a0] [b0] [c0] [d0] [e0] [f0]
[81] [91] [a1] [b1] [c1] [d1] [e1] [f1]
[82] [92] [a2] [b2] [c2] [d2] [e2] [f2]
[83] [93] [a3] [b3] [c3] [d3] [e3] [f3]
[84] [94] [a4] [b4] [c4] [d4] [e4] [f4]
[85] [95] [a5] [b5] [c5] [d5] [e5] [f5]
[86] [96] [a6] [b6] [c6] [d6] [e6] [f6]
[87] [97] [a7] [b7] [c7] [d7] [e7] [f7]
[88] [98] [a8] [b8] [c8] [d8] [e8] [f8]
[89] [99] [a9] [b9] [c9] [d9] [e9] [f9]
[8a] [9a] [aa] [ba] [ca] [da] [ea] [fa]
[8b] [9b] [ab] [bb] [cb] [db] [eb] [fb]
[8c] [9c] [ac] [bc] [cc] [dc] [ec] [fc]
[8d] [9d] [ad] [bd] [cd] [dd] [ed] [fd]
[8e] [9e] [ae] [be] [ce] [de] [ee] [fe]
[8f] [9f] [af] [bf] [cf] [df] [ef] [ff]
Well hopefully these tables helped someone, else I just wasted my time writing them for no reason.


9. Imgur albums with examples:

I have made a few Imgur albums dedicated to the different sections to give users an idea of how the different names look with the codes.
All the albums will have a neutral name without any codes on to show the difference.

Section 1 - Basic codes Section 2 - Fade/opacity codes Section 3 - "Special" codes Section 4 - "Weird" codes Section 5 - Codes that allows profanity Section 6 - Combining codes
Album Album Album Album Album Album

The table here was mainly to have the albums in one convenient place.
There is also a link to the albums in each section respectively.


10. Final words:

Thank you so much for reading! I dedicated a bunch of time to making this, especially since my brwser crashed halfway through writting it the first time around because my dumbass installed some sketchy software and it ate all my ram, which caused all my work to go to waste.

I will end the post here by saying; if you have anything to add, let me know and I'll add it to the post and give you the proper credits!
I'm always looking to expand, so if you know a code I don't know of, shoot it at me.
I'm really damn tired right now, so I'll hop off and answer comments and such tomorrow (if anyone decides to comment aha).
Also, please ignore any misspellings, English isn't my native language and I'm pretty self aware about my spelling, which causes me to misspell even more.

Also, rip mobile users, this post is pretty much a hell to read for you.
I'm sorry.

11. nsFAQ (not so Frequently Asked Questions):

In this section I will outline a few things that I have either figured out after posting, or things I simply forgot to add (both of which I don't know where exactly to put).

Q: Can I use this anywhere else besides my name?
A: Yes you can! Anywhere in the game where you have the ability to input text you can do it! Meaning you can really outline your message in multiplayer rooms by combining a few of the codes above (I can't remember if you have the ability to write text anywhere else, but I suppose that if you can, these codes will work).
I personally rock a message that looks like this: [b][i][u]ONLY 99LUCK. (In-game: "ONLY 99LUCK" with an underline).
In the multiplayer rooms you have a bit more freedom, since there is a 20 character limit instead of the tiny 8 when choosing a name.

Q: Will I be banned for using these?
A: No, this is Hexadecimal and BB codes which simply changes your name/text apperence, there's no reason for Bandai to ban players having a name with a code in it.
I even know someone that found one of the opacity codes by accident, and has been rocking with it for almost 3 years now.

This is all I have for now, but I will add more as I'm made aware of new things, or remember new stuff.


Edits:

EDIT: Just posted this. Apparently some of the results doesn't work proberly, so I've refered to the Imgur album instead to look at it.

EDIT2: Just realized the "fun names" results doesn't work. I've listed it as "try it yourself!".

EDIT3: Fixed a misspelling.

EDIT4: Added a bad TL;DR outlining what you should read/skim over to get the gist over everything.
Added a "rip/sorry mobile users" message in Section 10 - Final words.
Edited name of Section 8 to better reflect findings by user below.
Added the findings of iramd24 under "Section 2 - Fade/Opacity codes" and "Section 8 - (Thanks man!).
Added a "nsFAQ" (not so Frequently Asked Questions) outlining a few datails I overlooked when writing and don't know where else to put.
submitted by Lyn_The_2nd to NarutoBlazing [link] [comments]

A comparison of four visual story apps: Choices, Arcana, Lovestruck and Chapters

I decided to write up a chart comparing four of the visual story games I've played and how they compare in some respects. Not going to try and judge the writing quality of the games, while Chapters is obviously the least-quality on this metric I'll leave it to everyone to decide quality among the other three. I'm not trying to rank any one as better than the other! I think it should be pretty evident from my comparison that all of them have strengths and weaknesses.
There are a couple more games coming out (Storyscape is probably the most anticipated one) but they're still changing things so I didn't include them. I also didn't include Episode because I honestly have no clue which stories are featured / written by their team and I know most people don't play the "official" stories anyway, so it's kinda pointless to compare.
These four games are:
Since all of these apps have different names for the same things, I tried to standardize the terminology...
Choices: Stories You Play The Arcana: A Mystic Romance Lovestruck: Choose Your Romance Chapters: Interactive Stories
Release Date (App Store) 8/17/2016 10/22/2016 3/1/2017 10/27/2017
App Store Age Rating 12+ 12+ 17+ 17+
Passes are Called Keys Keys Tickets Tickets
Maximum Number of Passes 2 3 2 2
Pass Regeneration Rate 3 hours 4 hours 2.5 hours 2 hours
Gems are Called Diamonds Coins Hearts Diamonds
MC Visual Customization? Yes No No Yes
MC Gender Majority female (several stories have male options) Male/Female/Non-binary Female-only Almost all female (1 male-only story)
LI Gender Majority male (all but 1 story have at least 1 female LI) 3 Male, 2 female, 1 non-binary Male/Female (new releases are 50/50, 2 non-binary) Almost all male (2 female LI stories)
Watch Ads to Earn Gems? Yes Yes (beta) No Yes
Play Games to Earn Gems? No Yes No No
Check-in Daily to Earn Gems? Yes Yes Yes* (daily puzzle piece) Yes
Play Chapters to Earn Gems? Yes No Yes* (Romantic Quests) No
Number of Unique Series 35+ 1 (6 books) 14 100+
Series Types Both continuing series and stand-alones 1 continuing series Almost all continuing series (several stand-alones) Almost all stand-alones (two continuing series)
Average Chapters in Book ~15-18 22 (full) 12 (19 for earlier books) ~18-20
Average Choices per Book ~10-15 ~7-15 ~3-6 ~7-15
Can You Collect CGs? No* (they exist, but you can't collect them in one place) Yes Yes No
Do Choices Affect the Story? Yes Yes (upright/reversed endings) No* (some older books have thrilling/passionate endings) No
Are Series in Same Universe? Yes Yes Yes No

MC/LI Choices

Earning Passes/Gems

Gameplay

Stories & Genres

Genre Choices Lovestruck Chapters
Action The Heist: Romance, Most Wanted Gangsters in Love, Villainous Nights Bad Boy Blues
Fantasy The Crown & The Flame, The Elementalists Love & Legends, Reigning Passions Robin Hood
Historical A Courtesan of Rome, Desire & Decorum Speakeasy Tonight 50 Ways to Ruin a Rake
Horror It Lives Series N/A N/A
Mystery Veil of Secrets Castaway Dirty Little Secrets, Uninvited
Paranormal Bloodbound, Nightbound Havenfall is for Lovers Lux, Love at Stake
Science Fiction Across the Void Starship Promise Court of Nightfall, The Wandering Earth

History

Demographics

Here's a chart by gendesexual orientation for which game gives you the most options / fits a particular demographic best in my opinion:
Gender x Male LIs x Female LIs x Non-binary LIs
Female All apps but esp. Chapters Lovestruck, Choices Lovestruck
Male Choices, Arcana Choices Arcana
Non-binary Arcana Arcana Arcana
Let me know what you guys think, and if you can add another app to compare let me know too...
submitted by kori_no_ryu to Lovestruck [link] [comments]

[OC] Building an NFL Draft Model using Machine Learning

Happy Sunday nfl. Like most of the users here, I get draft-obsessed every February when the Combine comes around. Well, this year I decided to do something about it by building a draft model. If you're not interested in the details, you can stop right here and click the links below.
 
Model outputs from validation can be viewed here: https://docs.google.com/spreadsheets/d/1-ooQ4UTafyFOTWDtbYGmPgdHfspY8bci45tUS6I5-LU/edit?usp=sharing
Album of select draft prospect profiles: https://imgur.com/a/SCdkLj1
I've created some simple player visual dashboards which present position-specific percentile rankings in performance and athleticism. Each of these refer to either neutralized statistics, or engineered features, so "Tackles" is more accurately "Neutralized Tackles per Game" and "Speed" is actually "Speed Score". If anyone has requests to see other players, let me know and I'll try to cover all of them.

Research Goal

To build an NFL draft model capable of producing meaningful player predictions. I had originally planned to do so using a fuzzy Random Forest trained on NFL Combine and Pro Day physical measurements, individual and team college statistics, and engineered features. The model produced superior results when treating physical measurements as crisp rather than fuzzy, which was surprising but nonetheless forced me to change my approach.
Random Forest model is appropriate for this dataset because of the relatively small number of observations (roughly 250-300 players per draft class) and the highly non-linear relationship between the input and output variables. Random Forests are fairly robust against overfitting, which is a concern when modelling noisy data.
Player performance is impacted by round and team selection in the draft - first-round selections receive more opportunities than seventh-round selections, different schemes fit some players better. Because of this the model performance can be greatly improved by including some regression to draft selection or, in the case of test data, public rankings.

Model Output

I've decided to take the novel approach of using player ratings from EA Sports' Madden video game franchise as a proxy for player production, skill, and value. This is beneficial for a number of reasons. The first is that these ratings provide continuous output on a consistent scale across both years and positions; a player rated 99 overall is considered to be elite at their position, regardless of the unique responsibilities or challenges in quantifying performance specific to that position. The second reason is that Madden ratings predate modern quantitative evaluative metrics like those provided by Football Outsiders or Pro Football Focus.
Madden ratings explained - https://fivethirtyeight.com/features/madden/#
Overall ratings are calculated using position-specific formulas that weight individual attributes like speed, strength, and tackling. Ratings are updated each year through a Bayesian-like process of weighing new information to update old. To aggregate ratings for each player, I use a 5-part mean which includes ratings in Years 1-4 and Peak rating.
NFL rookie contract length is 4 seasons (along with a fifth year club option for first-round picks), while the average career length in the NFL is less than 4 years. As such, when building a draft model is makes sense to only consider production accrued during the first 4 years of a player's career.
Year 1 represents the Madden rating given to each player following their rookie season. For this reason, the final year for which complete data is available is the 2014 draft class (with Madden 19 providing Year 4 ratings). This decision was made to better capture NFL success, as rookie player ratings are highly dependent on draft order. For example, in Madden 2008 rookie #1 overall pick JaMarcus Russell was awarded an overall rating of 82, just 1 point lower than #3 overall pick Joe Thomas. The next year, Russell's rating was 83, while Thomas was a 97 overall. By Madden 2010, Russell was given a rating of 72 overall, while Thomas maintained his 97 overall rating. Year 3 and Year 4 ratings have been given double weight for the same reason, with the added effect of lowering the ratings of players who were not able to stay in the league for at least 4 years.
While this metric on the whole does a good job of ranking player talent and production, it is blind to players who peaked later in their careers or those who had short careers. Notable examples of each include Eric Weddle (84.6 rating, eventual 2x All Pro, 6x Pro Bowl) and Jon Beason (95.4 rating, 1x All-Pro, 3x Pro Bowl). Weddle did not reach his peak until after re-signing with the Chargers as an unrestricted free agent prior to the 2011 season, and could have presumably reached his peak while playing for another team. Beason suffered an Achilles injury during the 2011 season and eventually lost his job with the Panthers, starting in only 26 games in the years following his rating window. Beason would have been eligible to sign as a free agent following the 2011 season had the Panthers not offered a contract extension.
In the NFL, the drafting team maintains the exclusive right to employ each player for 4 years following their selection, thus it is incumbent upon the team to select and develop players who provide the most value during that period. For that reason I stand by the decision to evaluate draft selections only on a player's first 4 years in the league.

Dataset

I wrote several web scraping programs to pull data from NFL Draft Scout (an excellent resource for Combine data, and the only source I'm aware of that includes Pro Day data), Pro-Football-Reference, and CFB Reference (both Sports-Reference-operated sites, easily the best sources for football statistics in the NFL or FBS).
The dataset covers the 2006-2014 draft classes and includes players who were ranked in NFL Draft Scout's top 300 in their draft year. I have removed all quarterbacks, kickers, punters, long snappers, and fullbacks due to the relatively small sample sizes or extreme specialization that each position requires. It might be valuable to evaluate these positions later – particularly quarterbacks – but for now the model focuses exclusively on 13 "skill" positions, bucketed into 7 position groups.
The dataset restrictions exclude some notable players ranked outside of the top 300, both drafted and undrafted, who went on to varying degrees of success in the NFL. At the top extreme are 4-time All Pro Antonio Brown and Super Bowl LIII MVP Julian Edelman. But while many players on this list never played a down in the NFL, it is important to be aware of which players are excluded and it may be worthwhile to expand the dataset in the future.
I have removed players from the dataset whose NFL careers were cut prematurely short either voluntarily or involuntarily (due to injury, not ability). These players' ratings (or lack thereof) are not representative of their production and thus only serve to complicate the dataset and confuse any modeling attempts. Examples include Aaron Hernandez, Gaines Adams, and Chris Borland. The list is as long as it is depressing.
There is also a subset of players who drastically changed position upon entering the league. This is contrary to less extreme position changes (tackle to guard, cornerback to safety), which occur frequently. These players have been removed because their college statistics create noisy data. Examples: Denard Robinson, Devin Hester, J.R. Sweezy.

College Statistics

College statistics have been collected and cleaned at the FBS level from Sports Reference. Using college statistics is important because they provide information on a player's in-game performance. However, college football styles vary greatly among teams and have changed over time. Therefore we must control for differences in pace and style of play when considering college numbers. Rather than attempt to fit a model on raw season total statistics, I've decided to use neutralized per game statistics under the following parameters:
 
 
To illustrate this point let's look at Calvin Johnson and Michael Crabtree, who were both highly productive college wide receivers selected early in the first round.
 
 
The two statlines appear very similar without context. It's easy to make this distinction empirically, but little effort has been made to translate college statistics into more informative data. Johnson and Crabtree put up similar overall numbers, but Crabtree did it in an air raid style offense that relied heavily on passing while Johnson played on a more balanced offense.
 
 
When we neutralize both players' statistics, we can better compare each player's level of production.
 
 
Compare those numbers to each player's NFL career statistics:
 
 
This is a cherry-picked example but it does well to show that while raw statistics are not to be trusted, college data when put into the proper context can be made more predictive. On a larger scale, we can compare RMSE of the model when including raw college statistics compared to pace- and schedule-neutralized statistics. Controlling for strength of schedule does not improve the predictiveness of the model, but controlling for pace and style of play does have a significant effect.
 
Neutralization RMSE
Raw per Game 8.065
Pace-Neutralized per Game 8.029
Pace- and Schedule-Neutralized per Game 8.058
 
Here's the full stat list, with a few notable performers:
 
Offensive Statistics
 
Defensive Statistics
 

NFL Combine and Pro Day Measurements

The final major inputs of the draft model are the physical measurements taken at the NFL Combine and university Pro Days. Pro Day measurements are harder to come by due to their decentralized and often scarcely reported nature. Fortunately, NFL Draft Scout has maintained a database of reported Pro Day measurements spanning the years in our dataset.
There is an enormous benefit in using Pro Day measurements in a model like this. It allows for a larger training set by including data on players who were not invited to the NFL Combine, but also provides much more complete data because not all players who attend the combine perform the full slate of workouts. This lessens the need for imputation and reduces uncertainty.
However, there is bias observed in Pro Day measurements. Pro Days are typically scheduled in the weeks following the NFL Combine, giving players more time to train for the specific physical events. Furthermore, they often take place at the players' home campuses in environments in which the players feel more comfortable. Lastly, many events (most notably the 40-yard dash) are hand-timed at Pro Days, leading to better reported times than the electronic times at the Combine. Each of these factors contributes to improvement in every event among the population of players who participated both at the NFL Combine and at their university Pro Day.
 
Players who participated in both NFL Combine and Pro Day
Measurement Combine Pro Day n Sigma Adjustment
40 Yard Dash 4.80 4.70 831 0.076 + 0.07
20 Yard Split 2.79 2.71 733 0.065 + 0.06
10 Yard Split 1.68 1.62 739 0.057 + 0.04
Bench Press 20.0 reps 21.7 reps 254 2.556 - 1.2
Vertical Jump 31.7" 33.6" 593 2.342 - 1.3"
Broad Jump 112.9" 115.2" 481 4.356 - 1.6"
20 Yard Shuttle 4.46 4.42 424 0.155 + 0.03
3 Cone Drill 7.34 7.22 342 0.223 + 0.08
 
In order to correct for this bias, I've (somewhat arbitrarily) chosen to shift recorded Pro Day measurements by 70% of the mean delta. Even when we correct for some of the systematic bias observed in Pro Day measurements, we must also recognize that most physical measurements aren't static. Some players aren't performing at maximum physical capacity on the day of the Combine, occasionally players injure themselves during their workout, and the measurements aren't always recorded with perfect accuracy or consistency.
A dataset with this much uncertainty lends itself well to fuzzy set theory. In simple terms, this will allow us to consider not only a player's recorded 40 yard time of 4.40, but will also consider some probability that their "true" speed is 4.39 or 4.43. So when the model attempts to predict NFL success given a player's 40 yard dash time, it's not based on a singular number but rather a distribution of times centered around that number.
Fuzzy Set Theory explanation - https://www.doc.ic.ac.uk/~nd/surprise_96/journal/vol4/sbaa/report.fuzzysets.html
My approach is to generate a random forest model on the discrete data, then fit n iterations on randomly shuffled data to generate a distribution of outcomes for each player. This "shuffling" will occur randomly for each measurement using a normal distribution centered around the discrete number, with sigma equal to half of the standard deviations recorded above.
In a single random forest, data is crisply split by decision trees based on discrete information. But with enough randomly shuffled iterations, the trees are no longer binary decisions but rather probabilistic ones centered on each measurement's distribution. This is particularly relevant for players who may have measurements near decision tree boundaries. Two players with sprint times separated by mere hundredths of a second are not appreciably different in speed, but a random forest might classify them as such. The purpose of shuffling is not to fundamentally change each player's physical characteristics, rather to acknowledge measurement uncertainty. My belief is that this will improve the model outputs over a large enough number of trials.
We have a wealth of NFL Combine and Pro Day data but not every player has participated in every drill, so we'll need to fill in missing values. Because many of these physical measurements are correlated and most football positions require some degree physical specialization (size, speed, etc.), I've chosen a k nearest neighbor imputation method. The belief is that if Players A and B are similar in terms of position, size, speed, and quickness, then the two players will also have similar strength or jumping ability. The exceptions are draft age and wingspan, which can be reasonably predicted using population means.

Engineered Features

Perhaps the most essential component of a machine learning model is feature engineering.
Modern feeling toward physical measurements taken at the Combine is highly dubious, and I agree that each measurement taken in isolation cannot alone adequately define athleticism, much less predict success. However, there exist more complex metrics which can better perform both tasks across a large enough sample.
 
Body Mass Index (BMI)
 
Speed Score
 
Height-Adjusted Speed Score
 
Vertical Jump Power
 
Broad Jump Power
 
Quickness Score
 
Weight-Adjusted Bench
 
Catch Radius
 
The models also include several features designed to summarize the collection of college statistics being used.
 
Offensive Usage
 
Defensive Disruption
 
S&P Market Share

Cross-Validation and Tuning

I've tuned the model using stratified k-fold cross validation, leaving out each draft class as OOB observations. As a result, every player has been included in both the training and validation sets. Each position group has been fit with its own unique hyperparameters to optimize predictions.
 
Hyperparameters by Position Group
Position Number of Trees Max Depth Max Features Min Leaf Samples
WR 100 5 10 3
FS 250 5 10 1
CB 50 10 20 2
SS 40 10 10 2
ILB 30 15 5 2
RB 40 10 10 1
TE 20 10 3 2
EDGE LB 50 5 10 2
EDGE DL 250 15 10 2
C 50 5 5 3
DT 100 3 10 1
OT 20 5 3 2
OG 20 10 5 2
 
Additionally, the model performed best when aggregating predictions from 3 randomized sets, as shown in the plot below. However, this fuzzy approach failed to outperform discrete features during cross-validation. I expected the opposite, but it seems treating each measurement as precise leads to the best fit.
 
RMSE Using Various Methods
Method RMSE
Discrete 8.027
1 Random set 8.122
2 Random sets 8.069
3 Random sets 8.063
5 Random sets 8.098
10 Random sets 8.115

Results and Further Research

By and large the model does surprisingly well considering the lack of more traditional evaluative inputs. NFL teams have the resources of scouting departments providing more detailed player evaluation, experienced coaching staffs evaluating personnel fits, and front offices to balance financial considerations and positional value. Each of these factor into draft decisions and improve ranking methods beyond the scope of this model.
 
Model results by position
Position RMSE n Most Important Features
WR 7.523 314 Underclassman, Usage, Age, Srimmage Yards, Total TD, Receiving Yards
FS 7.621 128 S&P Share, Age, SOS, 20-Yard Shuttle, Height, 40-Yard Dash
CB 7.604 292 Age, Quickness Score, Height-Adjusted Speed Score, S&P Share, Height, 20-Yard Dash
SS 7.437 107 Run Stuffs, BMI, Defensive Disruption, Quickness Score, Tackles, TFL
ILB 7.649 291 S&P Share, Age, Tackles, Height-Adjusted Speed Score, Vert Power
RB 8.121 194 Rush TD, Rush Yards, Age, Total TD, Scrimmage Yards, Height-Adjusted Speed Score
TE 8.097 139 Scrimmage Yards, Receiving TD, Receiving Yards, Offensive Usage, Hand Size
EDGE LB 8.846 90 S&P Share, Disruption, Catch Radius, Tackles, Weight, Age
EDGE DL 7.445 190 Age, TFL, Weight, Height-Adjusted Speed Score, Quickness Score, Underclassman
C 8.948 82 3-Cone, Weight, Broad Jump, Quickness Score, Hand Size, Age
DT 7.823 211 S&P Share, TFL, Tackles, Disruption, Run Stuffs, 3 Cone
OT 8.882 222 Age, Vert Power, Arm Length, Speed Score, Weight
OG 8.819 140 Adjusted Bench, 20-Yard Dash, Catch Radius, Quickness Score, Age, Weight
 
When properly optimized, the model can achieve RMSE below 8 during cross-validation. Unsurprisingly, it struggles most with offensive linemen, who lack individual statistics. In particular it struggles with centers, whose responsibilities in the NFL are as much mental as physical. Interestingly, NFL teams have had great success evaluating centers, as 4 of the 5 first rounders were named to All-Pro teams in their careers, and all made the Pro Bowl at some point.
As mentioned in the introduction, the model could be improved substantially by including draft selection or consensus rankings. Furthermore, team-specific random effects could likely explain some of the residuals. I may eventually explore these research questions, but my short-term priorities are on visualization and presentation of data.
 
If you've made it this far, check out my github for the source code: https://github.com/walt-king/NFL-draft-research
This was created using Python for web scraping, data collection, modelling, and visuals. I used R to create the player dashboards. Comments, thoughts, and feedback all greatly appreciated.
submitted by dataScienceThrow1 to nfl [link] [comments]

The Mind Vault - Unlocked. Beyond Binary

You look in the mirror with disgust.
You think to yourself; Why do I look so...wrong?
You mentally compartmentalize the hideous growth between your legs and visualize a happy blonde girl.
You close your eyes so tightly it makes your eyes water.
You’ve tried on make-up, and your Mum’s shoes numerous times.
The comments from your dad when he caught you left you feeling... wrong... alone …lost.
You think to yourself; I’m not this person in this reflection.
I am neither a boy nor a girl - I am me.
Children are not born knowing what it means to be a boy or a girl; they learn it from their parents, older children and others around them. This learning process begins early. As soon as the doctor announces – based on observing the newborn’s external sex organs – “it’s a boy” or “it’s a girl,” the world around a child begins to teach these lessons. Whether it’s the sorting of blue clothes and pink clothes, “boys’ toys” and “girls’ toys” or telling young girls they’re “pretty” and boys they’re “strong.” It continues into puberty and adulthood as social expectations of masculine and feminine expression and behaviour often become more rigid. But gender does not simply exist in those binary terms; gender is more of a spectrum, with all individuals expressing and identifying with varying degrees of both masculinity and femininity. Transgender people identify along this spectrum, but also identify as a gender that is different than the one, they were assigned at birth.
At some point, all children will engage in behaviour associated with different genders – girls will play with trucks, boys will play with dolls, girls will hate wearing dresses and boys will insist on wearing them – and gender nonconforming behaviour does not necessarily mean that a child is a transgender. That said, sometimes it does – with some children identifying as another gender than the one they were assigned by the time they are toddlers.
The general rule for determining whether a child is a transgender (rather than gender nonconforming or gender variant) is if the child is consistent, insistent, and persistent about their transgender identity. In other words, if your 4-year-old son wants to wear a dress or says he wants to be a girl once or twice, he probably is not transgender; but if your child who was assigned male at birth repeatedly insists over several months that she is a girl, then she is probably transgender. Naturally, there are endless variations in the ways that children express themselves, so the best option, if you think your child might be transgender, is to consult a gender therapist.
Transgender people come from all walks of life. They are dads and mums, brothers and sisters, sons and daughters. They are your colleagues and your neighbours. They are 7-year-old children and 70-year-old grandparents. They are a diverse community, representing all racial and ethnic backgrounds, as well as faith backgrounds.
Although the word “transgender” and our modern definition of it only came into use in the late 20th century, people who would fit under this definition have existed in every culture throughout recorded history.
Despite the increased visibility of transgender celebrities like actress Laverne Cox or more recently singer Sam Smith, many people still don’t personally know anyone who is transgender – but the number who do is growing rapidly.
In the HRC Foundation’s 2012 survey of LGBTQ youth, about 10 percent of respondents identified themselves either as “transgender” or as “other gender,” and wrote in identities like “genderqueer,” “gender-fluid” or “androgynous.” This suggests that a larger portion of this generation’s youth are identifying somewhere on the broad transgender spectrum.
In many ways, transgender people are just like cisgender (non-transgender) people; but because of the social stigma surrounding our transgender identity, our community faces a unique set of challenges.
Currently, Primary scho