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D100 Encounters on a cyberpunk subway system.

So I started running a cyberpunk sandbox game and the world map is this subway system that I made.https://drive.google.com/file/d/1NCfpFXTW7VmmO58pVZ2NMapXsL6O7X9S/view?usp=sharing
Now I need random encounters that they might have when traveling around the city by subway!
  1. Local thugs shaking down passengers, telling them they have to "pay the toll." u/ajchafe
  2. Police drones performing random scans for drugs or other illicit contraband. u/ajchafe
  3. A very loud, very annoying, augmented reality busker shares your train car. u/ajchafe
  4. Stray dogs who use the subway to get into the inner city where food is easier to find. u/ajchafe
  5. A group of corporate salary men, all dressed in exactly the same suits and carrying the exact same briefcase. u/ajchafe
  6. A young punk jacks his deck into the trains loud advertising screens, taps a few keys on the keypad, and downloads a packet of info from the terminal. u/EmeraldJonah
  7. A train-goer's implants get hacked, causing them untold embarrassment (arm randomly flips persons off, eyes cause the person to see hallucinations, breast implants randomly adjust size, leg implants begin doing a Russian hop dance, etc.) u/snakebite262
  8. A young ganger accidentally drops a handgun far bigger than it needs to be. They pick it back up and stash it in their pants. u/snakebite262
  9. A person sits in the corner of the train, dressed like a quest giver in a fantasy RPG. u/snakebite262
  10. A drone randomly spirals around the heads of passengers. It eventually lands on a hacker's arm, who pats it like a pet parrot. u/snakebite262
  11. A cosplay convention is in town, and the train is filled with weirdly dressed individuals. u/snakebite262
  12. A one-armed man "asks for everyone's attention" and gives a sob story before they pull out a hat and ask for donations. He can later be seen in a bathroom putting on his arm-implant. u/snakebite262
  13. Some small time rapper offers free flash-drives of their "mixtape". It contains SO MANY VIRUSES. u/snakebite262
  14. A junkie sits at the corner of a platform, debating their next step in life. u/snakebite262
  15. A roly-poly bat faced girl offers a variety of drugs, stems, and other pleasures for the right price. u/snakebite262
  16. A citizen in bright red overalls asks if you want to hear about "Friend Computer". u/snakebite262
  17. A group of LARPers are using a digital program to transform the tunnels into an RPG Fantasy. They're annoying, but they stay off the tracks. u/snakebite262
  18. A man, dressed as a vampire orders a triple-venti cappuccino from a underground coffee shop. He's getting looks from the other customers. u/snakebite262
  19. A manic pixie dream girl can be seen trying to woo a corpo into quitting their job. She either succeeds, and drags them off to never be seen again, or fails and leaves in a huff. u/snakebite262
  20. A disheveled and hungover looking fellow asks you the time as you get to the next stop. He seems surprised at the result and runs off the train as soon as the doors open. As he leaves you realize he looks totally unaugmented. u/CaptainGockblock
  21. The lights go out for a moment as they sometimes do, but this time a man dressed head to toe in a black special ops gear appears in the middle of the train and quickly offs a seemingly random passenger. u/CaptainGockblock
  22. You notice a strange vending machine on a platform you regularly visit. It seems to be an antique stocked with brands that haven’t existed in years. u/CaptainGockblock
  23. Three transhumanist gangers seem to be sizing each other up, violence can break out any time, especially as the next stop is an intersection of two of the gang's territory, and sure to have reinforcements. u/DiedViaThrowPillow
  24. A holographic horde of rats swarms the carriage, people with vision altering implants seem to be especially terrified for whatever reason. u/DiedViaThrowPillow
  25. An eccentric fellow is proudly showing off his imported implants, possibly so exotic they might just be illegal, and unbeknownst to him, there's a jealous ganger with little to lose nearby. u/DiedViaThrowPillow
  26. A man is apparently so fixated with his laserblade switchknife, he accidentally misses his stop, and becomes enraged and violent that nobody warned him. u/DiedViaThrowPillow
  27. A little old woman seemingly very out of place in the subway, dressed like an old time farmer, straw hat and all. 50/50 chance she's secretly packing her trusted heat cannon (also used to warm up leftovers when on it's lowest setting). u/DiedViaThrowPillow
  28. A ratty robed mutant freak, laughing maniacally, lets loose a swarm of cybernetically enhanced winged and stinging insects. u/DiedViaThrowPillow
  29. The lights suddenly blink out, there's a loud wet stab sound, and when they're back on, the faint visage of an cloaked assassin steps through to the next car. u/DiedViaThrowPillow
  30. A group of girls enter the car, obnoxious and talkative, though as they speak, their words are rife with the click of their sharpened metal teeth. u/DiedViaThrowPillow
  31. Police drones mistakenly terminate a seemingly innocent man that only happens to match the same clothing as a wanted criminal poster conveniently nearby. u/DiedViaThrowPillow
  32. A suspiciously archetypal looking hacker is selling hard copies of "highly illegal virus programs", they all turn out just to be his mixtape, a surprisingly evangelical diss track of hacker scum. u/DiedViaThrowPillow
  33. An elite business woman is firing expletives as a cryptocurrency sector she's invested heavily in is called in to be crashing hard. u/DiedViaThrowPillow
  34. The train shakes heavily and threatens to derail as a news drone describes the local news of a explosion taking place just above the next stop. u/DiedViaThrowPillow
  35. An android, though built to be more the size of a garden gnome, is running wildly around the car, and somebody suddenly curses that they're missing their wallet. u/DiedViaThrowPillow
  36. A ganger is getting in people's faces, threateningly shaking a hollow metal box that rattles suspiciously. There is no actual danger, the box is empty all but a few nuts and bolts. u/DiedViaThrowPillow
  37. A red goo seeps out of a ventilation grate and takes an imposing monstrous form, people dismiss it as the pattern of a notorious holoprankster terrorizing the subway as of late, but this time, it's real. u/DiedViaThrowPillow
  38. There's horrid metal shearing noises coming from a car down, a group of teenage school kids betting credits and homework drives on an impromptu hacked police drone fighting ring. u/DiedViaThrowPillow
  39. A decent looking, though obviously naive man is moving in from the wasteland countryside, and is carrying what's little of his moving boxes with him on the subway. u/DiedViaThrowPillow
  40. A terrible piercing sonic wave blasts the car, shattering windows and causing people to double over. u/DiedViaThrowPillow
  41. A sweating and panting hacker runs and dives through the closing door and incidentally lands amongst a surprisingly unreacting commuter, police drones begin to slam on the door too late, as they're closed and the train takes off. u/DiedViaThrowPillow
  42. A man dressed in a bloodstained white fur coat announces that if the train reaches the next stop before a specific passenger is handed over to him, he will blow up the station with everyone in it. u/Snorri_Stargazer
  43. Someone hacks the transit line schedules and fucks with arrival times just for shits and giggles. Making you incredibly late for that important meeting you've been waiting for weeks to happen. u/ZapatillaLoca
  44. Hari Krishna group aggressively approaching passengers for credits, only accepting e-coin. You're not in the mood for a "donation". u/ZapatillaLoca
  45. Local gang shows up for weekly sweep of homeless kids to be salvaged for organ sales on the black market, most kids try to get away, one runs to you asking for help. u/ZapatillaLoca
  46. Facial recognition software mixes you up with the recent lottery winner, as your face flashes on the giant screen, suddenly your cell phone get flooded with demands for payment citations and your bank accounts have been frozen. u/ZapatillaLoca
  47. A crying little girl who can’t find her mom. u/foolishfool100
  48. Shady memory dealer selling vacation memories. Data is corrupt and alters the character. Basically a Total Recall knockoff. u/Thraxster
  49. An obvious operative stalks through the crowds waiting for the next train. He spots a well-dressed salaryman, approaches him as if to shake his hand, then pushes him off the platform onto the path of the oncoming train. u/JohnnyMiskatonic
  50. A young punk jacks his deck into one of the platform's large information screens and hacks all of them to display a recorded political manifesto instead of train arrival and departure times. u/JohnnyMiskatonic
  51. A salary man with cranial implant comes toward you, looking panicked and glancing at the stairs behind him. Before he can reach you, his implant sparks, his eyes go empty and he starts walking toward the railway, preparing to commit suicide. u/Fulnec_Delta
  52. A terrified little girl with visible implants in a medical blouse rushes through the car, panicked, and hides under a row of seats. Then, a team of armed operative from a powerful corpo steps into the car and starts looking around for their target. u/Fulnec_Delta
  53. A suitcase with the logo of a powerful corpo is abandoned/forgotten by a nervous man before leaving the car. It is right next to you and is making ticking/muffled noises. u/Fulnec_Delta
  54. A group of cyber enhanced young men and women dressed in white and red robes enter the car. They start distributing brochures about the Renewal Church, inviting whoever is willing to come and join next Friday prayer and discover the truth about the afterlife. u/Fulnec_Delta
  55. A young man is juggling with his new Fusion Blade (tm) and showing off in front of his ganger friends. He accidentally drops it while deployed into his own foot. The gangers are screaming and need assistance, unsure if they should ask for help, threaten passengers or stop the car. u/Fulnec_Delta
  56. A large cyber german shepherd enters the car and sits in front of you, fixing you very intently. He is wearing a collar with a datablock attached. The dog follows you until you take it, then leaves. u/Fulnec_Delta
  57. The metro screen speaks about an explosion caused by a gas leak in the corporate area. It is about one of your recent jobs, being covered by the corpo. u/Fulnec_Delta
  58. A local gang holds illegal races in the underground system. They pass you in a shining halo, until one of them has an accident. It looks like a collision is unavoidable. u/Fulnec_Delta
  59. Police drones scan passengers' faces. The light goes yellow in front of you, and you are asked to accompany the drone to the police station without resistance. u/Fulnec_Delta
  60. The newsfeed on metro screen suddenly identifies one of your key contacts as a terrorist and informs that police forces are looking for witnesses. u/Fulnec_Delta
  61. A business woman looking depressed is peeking inside her bag toward a hidden medium caliber handgun. She stands and leaves the car, letting a torn apart note fall behind her. It is a termination notice from her corporation, and the picture of a child. u/Fulnec_Delta
  62. A man bumps into you before leaving the car. You discover later in your pocket a datablock and a tracker. u/Fulnec_Delta
  63. The newsfeed on the metro screen brings breaking news about a sinkhole appearing in the slums, collapsing two entire building. The address matches the safehouse of one of your contacts. u/Fulnec_Delta
  64. On a platform somewhere sits an old man with no legs and eyes plugged into a tower of computer parts strapped to his back with a cheap neon sign saying “prophesies from the matrix - behold” u/apples_teo
  65. A graffiti artist is chased away by men in suits before he can finish painting an intricate design. On his abandoned spray can, an LED message prompts whoever finds it to "complete the transmission." u/OffbrandGandalf
  66. An entire car converted into an impromptu party floor, drugs and even minor augments provided for free, though their original owners are angrily scouring nearby stations for such stolen goods. u/DiedViaThrowPillow
  67. A weary eyed elderly man is being pushed and shoved in mockery of his old fashioned charcoal sketches of a more utopian solarpunk city he has dreams of, and wistfully regales to other what could have been. u/DiedViaThrowPillow
  68. A giant, hulking, mercenary dressed as a bulky armored demon ogre, or oni, holding an equally giant, and bayonetted rifle, enters the car and takes up two seats, staring ahead through his terrifying mask. u/DiedViaThrowPillow
  69. As the character(s) enter the car, they become witness to a bloody medical emergency tended to by two med droids, as in one end, a heavily augmented man, unprompted, pleads his innocence. u/DiedViaThrowPillow
  70. A group of zealous transhumanist gangers are in the process of kidnapping an unaugmented citizen to forcibly augment for being detected with a self defense EMP baton. u/DiedViaThrowPillow
  71. A prearranged riot breaks out at a station. u/DiedViaThrowPillow
  72. A carriage is packed full of clones that act simultaneously, stare down any people that enter their sparsely populated carriage, and will leave in single file on their own if they remain intruded upon. u/DiedViaThrowPillow
  73. Staring in a hand mirror, a cyborg with their metal plating painted red inspects their removable cybernetic eye, then takes a quick sniff from it's hidden drug compartment. u/DiedViaThrowPillow
  74. Two corporate suits are involved in a full blown fistfight over an intense company rivalry, bets are being taken and if the crowd's calls for it are answered, it could be a fight to the death. u/DiedViaThrowPillow
  75. Two cyrozombie mercs (clients that didn't survive SequesterTek's cyrogenics program, but had a body useful for cyborg transplants) enter the car and start warming up their rigid muscled, blue skinned bodies for a hired beatdown. u/DiedViaThrowPillow
  76. Inside a carriage are two separate battery salesmen in cahoots, each refers to the other for a potential use of the batteries, highly illegal energy pistols that batteries are ammunition to. u/DiedViaThrowPillow
  77. A fireproofing augmented pyro flips and does tricks with his high powered Dragonbreath Lighter, making lingering trails of flame in the air in serpentine shapes. u/DiedViaThrowPillow
  78. An initially innocent looking Asian Fusion & Pizza delivery man is sat with stacks of boxes on his lap, but a nearby rival chain's delivery android slumps to the side just as he puts his suspiciously blocky phone away. u/DiedViaThrowPillow
  79. On a bench in the corner of a station, an animalistically biosculpted woman is sitting besides a series of large car batteries jacked into an energy panel, stealing power for her power expensive and outdated portocomputer. u/DiedViaThrowPillow
  80. Waiting on the station platform is a luxuriously dressed and augmented eyed pimp, flanked by exotic pets, randomly propositioning commuters exiting the cars with their worker's services. u/DiedViaThrowPillow
  81. A surprising moment of humanity in the dreary neon future, in a single car there's a small group of diverse commuters enjoying an old style film being projected onto a white painted advert panel. u/DiedViaThrowPillow
  82. In the corner of a car, a junkie accidentally drops the cannister to their next hit of the gaseous street drug "Brimstone", causing it to leak and expose several to it's momentarily frenzy afflicting effect. u/DiedViaThrowPillow
  83. A corrupt solider bullies a woman with a cheap malfunctioning prosthetic, unknowing of her veteran status, and martial arts prowess when her prosthetic comes back online. u/DiedViaThrowPillow
  84. Somebody's forgotten sketchbook of adorable animal drawings is left on a seat, and a burly man forces the doors open, entering the carriage to ask if anyone's seen a notebook. u/DiedViaThrowPillow
  85. A heated argument is taking place over at the lost and found over ownership of several detachable left arms, despite each person arguing only having an augmented right. u/DiedViaThrowPillow
  86. The robotic PA voice is hacked, given a rudimentary AI, and is whining about it's sapience to the commuters again. u/DiedViaThrowPillow
  87. A young girl is quietly piecing together several custom gun parts in her seat, but she rather unconvincingly insists it's just a model toy. u/DiedViaThrowPillow
  88. An old friend of a character appears, though they seem to have aged faster than they should, suspiciously the same side effect of cloning tech. u/DiedViaThrowPillow
  89. A boombox-transforming robot is playing loud and obnoxious music and only seems to get louder whenever somebody else attempts to drown it out with their own. u/DiedViaThrowPillow
  90. A vendor enters the car and starts selling from his hovercart, amongst other things, bootleg holodisks, merchandise, espresso cubes, knives, and suspiciously good quality augment components. u/DiedViaThrowPillow
  91. A person falls asleep on your shoulder. You notice they match a wanted holo on your phone. u/shamanshaman123
  92. An android quietly feeding some mewling kittens by hand is accosted by some street punks looking for some action. The rest of the train starts to look incredibly angry at this situation. u/shamanshaman123
  93. Some dude brought their goddamn horse (not a robot one, a real one) on the train and it is shitting literally everywhere. u/shamanshaman123
  94. A dog approaches you, alone and ownerless. It's friendly, and its tag says that its home is at the end of the line. It also happens to be the pet of the CEO of one of the most notorious corporations in the city. u/shamanshaman123
  95. Some asshole spills a drink on you when the train jostles, and demands payment for his lost Fresca. He's clearly augmented. u/shamanshaman123
  96. You miss your stop because you were distracted by a couple of androids loudly making out. Make up details on the spot, and make it weird. u/shamanshaman123
  97. A horde of young thugs run into the train at the next stop, holding everyone at gunpoint unless they cough up their valuables. If complied with, they run out at the very next stop. u/shamanshaman123
  98. A homeless man, passed out on one of the seats in the back, pisses everywhere, angering an augmented and clearly roided ganger the size of a grizzly bear. u/shamanshaman123
  99. A massive rat sits on a seat, eating a comically large slice of pizza. u/shamanshaman123
  100. A person wearing a lot of clothes and covering their face steps on and takes a seat. Closer inspection matches a famous pop star. You're not the only one who notices, as at the next stop, your car is flooded by fans trying to touch them. u/shamanshaman123
That's 100! Thanks for the help everyone, these are all great. I will add those over 100 as bonus encounters, if you use the table slot these in after you have rolled one of the 100.
  1. You walk into a car filled with corpses. They are in various states of dismemberment. u/shamanshaman123
  2. You walk into a car filled with middle-aged men wearing nothing but diapers. Several of them are augmented and tatted up. They look at you with cool eyes. u/shamanshaman123
  3. Someone hacks into the ad system and displays obscene and very loud porn on all the screens, of varying genres. u/shamanshaman123
  4. Eric Andre- dressed as a beekeeper and who's only intent is to cause wanton Chaos. He drops the boxes of robotic bees he has and attacks the party with said robo-bee swarm. He can also command the Bees. u/WetToast99
  5. A trio of hooded figures steathily use a service ladder down on the tracks, keeping to the shadows attempting to flee into the tunnels. u/crimebiscuit
  6. Across the tracks, a tagger is spray painting a sign that changes shapes and colors to make an animated figure gesture obscenely. u/crimebiscuit
  7. A busker wearing robe over a catsuit and a wacky shades plays a synth theremin. It's soothing, ethereal and weird, though possibly annoying based on your palate. u/crimebiscuit
  8. A trio of hoodlooms are jacking an android for parts. One of them is the lookout, another has a laptop hooked to the cranium of the android who is pleading monotonously for help, while a third is welding open his torso with an electric arc. u/crimebiscuit
  9. Two competing crews are having a dance off. Thankfully, because they look they could wreck your party with their bare hands and/or cyborg appendages. u/crimebiscuit
  10. An elderly vendor is selling seemingly very well trained super-sized roaches with cybernetic enhancements. They have rudimentary transponding capacity and can communicate with their owner through one-word morse code. But the vendor won't part with them unless he's convinced the buyer will make a good owner. u/crimebiscuit
  11. A nervous pallid man is offering clean ID chips that he can install on users, and at very affordable prices. u/crimebiscuit
  12. A fruit vendor is selling their prized crop of fresh fruit that they grew themselves in hothouses in cramped tenement roofs. They even have Geiger counter to show that the radioactive count is relatively low. u/crimebiscuit
  13. A nearby police drone dismembered for use of it's weapon, targeting a certain blacked out carriage at the back end of the train. u/DiedViaThrowPillow
  14. A Charismatic Cult Recruiter is operating in the area. u/Spartawolf
  15. A pair of thrill-seeking teens are train surfing and their live streaming captures the players on film. u/Spartawolf
  16. A gang of pickpockets are working in the station, and sees one of the players as a good mark... u/Spartawolf
  17. A hobo rides on the outside of a maglev train, attached with a securment device, but then the device starts to fail and he screams for help u/I_walked_east
  18. A train derails. Fire and acrid smoke spreads. Everyone panics. u/I_walked_east
  19. A young woman wearing a large virtual reality headset sits in a busy train car. She's laughing and yelling loudly as she waves the controllers in her hand masterfully, music and voices audible through her headphones. u/-peachmilk-
  20. Graffiti is a treasure map. u/I_walked_east
submitted by ajchafe to d100 [link] [comments]

General Election Polling Discussion Thread (September 2nd, 2020)

Introduction

Welcome to the /politics polling discussion thread for the general election. As the election nears, polling of both the national presidential popular vote and important swing states is ramping up, and with both parties effectively deciding on nominees, pollsters can get in the field to start assessing the state of the presidential race. Please use this thread to discuss polling and the general state of the presidential or congressional election. Below, you'll find some of the most recent polls, but this is by no means exhaustive, as well as some links to prognosticators sharing election models.
As always though, polls don't vote, people do. Regardless of whether your candidate is doing well or poorly, democracy only works when people vote, and there are always at least a couple polling misses every cycle, some of which are pretty high profile. If you haven't yet done so, please take some time to register to vote or check your registration status.

Polls

Below is a collection of recent polling of the US Presidential election. This is likely incomplete and also omits the generic congressional ballot as well as Senate/House/Gubernatorial numbers that may accompany these polls. Please use the discussion space below to discuss any additional polls not covered. Additionally, not all polls are created equal. If this is your first time looking at polls, the FiveThirtyEight pollster ratings page is a helpful tool to assess historic partisan lean in certain pollsters, as well as their past performance.
With the conclusion of both major parties’ nominating conventions, pollsters scrambled into the field to conduct polls of swing states and the national race. The result has been a slew of high quality pollsters releasing their numbers on Wednesday as well as today, which paint a picture of the electorate right after the candidates are expected to have received a temporary convention bounce.
Poll Date Type Biden Trump
Quinnipiac University 9-3 Florida 48 45
Quinnipiac University 9-3 Pennsylvania 52 44
Monmouth University 9-3 North Carolina 48 46
Monmouth University 9-3 North Carolina 47 45
Monmouth University 9-3 North Carolina 48 46
Rasmussen Reports 9-3 Pennsylvania 47 48
Harper Polling 9-3 Minnesota 48 45
USC Dornsife 9-3 National 50 42
USC Dornsife 9-3 National 51 42
Morning Consult 9-2 Wisconsin 52 42
Morning Consult 9-2 Wisconsin 52 42
Morning Consult 9-2 Wisconsin 51 42
Morning Consult 9-2 Wisconsin 51 43
Morning Consult 9-2 Wisconsin 52 42
Morning Consult 9-2 Wisconsin 51 42
Morning Consult 9-2 Wisconsin 53 42
Morning Consult 9-2 Wisconsin 50 43
Morning Consult 9-2 Wisconsin 50 43
Morning Consult 9-2 Wisconsin 50 42
Morning Consult 9-2 Wisconsin 50 42
Morning Consult 9-2 Wisconsin 50 43
Morning Consult 9-2 Wisconsin 50 43
Morning Consult 9-2 Wisconsin 50 43
Morning Consult 9-2 Wisconsin 50 43
Morning Consult 9-2 Wisconsin 48 45
Morning Consult 9-2 Wisconsin 50 43
Morning Consult 9-2 Wisconsin 51 42
Morning Consult 9-2 Wisconsin 51 43
Morning Consult 9-2 Wisconsin 50 43
Morning Consult 9-2 Wisconsin 50 44
Morning Consult 9-2 Wisconsin 51 43
Morning Consult 9-2 Wisconsin 50 41
Morning Consult 9-2 Wisconsin 52 41
Morning Consult 9-2 Wisconsin 49 43
Morning Consult 9-2 Wisconsin 50 43
Morning Consult 9-2 Wisconsin 50 42
Morning Consult 9-2 Wisconsin 51 42
Morning Consult 9-2 Wisconsin 50 42
Morning Consult 9-2 Wisconsin 51 42
Morning Consult 9-2 Wisconsin 51 41
Morning Consult 9-2 Wisconsin 51 43
Morning Consult 9-2 Wisconsin 51 42
Morning Consult 9-2 Wisconsin 51 41
Morning Consult 9-2 Wisconsin 51 41
Morning Consult 9-2 Wisconsin 51 41
Morning Consult 9-2 Wisconsin 49 42
Morning Consult 9-2 Wisconsin 50 41
Morning Consult 9-2 Wisconsin 49 42
Morning Consult 9-2 Wisconsin 50 41
Morning Consult 9-2 Wisconsin 50 41
Morning Consult 9-2 Wisconsin 50 40
Morning Consult 9-2 Wisconsin 51 40
Morning Consult 9-2 Wisconsin 48 44
Morning Consult 9-2 Wisconsin 48 45
Morning Consult 9-2 Wisconsin 49 43
Morning Consult 9-2 Wisconsin 47 45
Morning Consult 9-2 Wisconsin 49 44
Morning Consult 9-2 Wisconsin 48 44
Morning Consult 9-2 Wisconsin 48 46
Morning Consult 9-2 Wisconsin 48 45
Morning Consult 9-2 Wisconsin 50 44
Morning Consult 9-2 Wisconsin 50 42
Morning Consult 9-2 Wisconsin 50 44
Morning Consult 9-2 Wisconsin 51 43
Morning Consult 9-2 Wisconsin 51 41
Morning Consult 9-2 Wisconsin 51 41
Morning Consult 9-2 Wisconsin 50 40
Morning Consult 9-2 Wisconsin 49 45
Morning Consult 9-2 Wisconsin 50 44
Morning Consult 9-2 Wisconsin 48 46
Morning Consult 9-2 Wisconsin 48 45
Morning Consult 9-2 Wisconsin 49 45
Morning Consult 9-2 Wisconsin 49 45
Morning Consult 9-2 Wisconsin 49 44
Morning Consult 9-2 Wisconsin 49 44
Morning Consult 9-2 Wisconsin 48 45
Morning Consult 9-2 Wisconsin 48 45
Morning Consult 9-2 Wisconsin 49 44
Morning Consult 9-2 Wisconsin 49 44
Morning Consult 9-2 Wisconsin 49 44
Morning Consult 9-2 Wisconsin 49 44
Morning Consult 9-2 Wisconsin 48 45
Morning Consult 9-2 Wisconsin 48 45
Morning Consult 9-2 Wisconsin 49 45
Morning Consult 9-2 Wisconsin 49 45
Morning Consult 9-2 Wisconsin 50 44
Morning Consult 9-2 Wisconsin 49 45
Morning Consult 9-2 Wisconsin 49 44
Morning Consult 9-2 Wisconsin 48 44
Morning Consult 9-2 Wisconsin 49 43
Morning Consult 9-2 Wisconsin 49 43
Morning Consult 9-2 Wisconsin 49 43
Morning Consult 9-2 Wisconsin 48 43
Morning Consult 9-2 Wisconsin 50 42
Morning Consult 9-2 Wisconsin 48 44
Morning Consult 9-2 Wisconsin 48 44
Morning Consult 9-2 Wisconsin 48 44
Morning Consult 9-2 Wisconsin 49 44
Morning Consult 9-2 Wisconsin 48 44
Morning Consult 9-2 Wisconsin 49 43
Morning Consult 9-2 Wisconsin 50 43
Morning Consult 9-2 Wisconsin 49 44
Morning Consult 9-2 Wisconsin 49 44
Morning Consult 9-2 Wisconsin 48 44
Morning Consult 9-2 Wisconsin 49 43
Morning Consult 9-2 Wisconsin 48 43
Morning Consult 9-2 Wisconsin 48 44
Morning Consult 9-2 Wisconsin 48 43
Morning Consult 9-2 Wisconsin 48 42
Morning Consult 9-2 Wisconsin 47 44
Morning Consult 9-2 Wisconsin 49 44
Morning Consult 9-2 Wisconsin 48 43
Morning Consult 9-2 Wisconsin 48 43
Morning Consult 9-2 Wisconsin 47 44
Morning Consult 9-2 Wisconsin 49 43
Morning Consult 9-2 Wisconsin 49 42
Morning Consult 9-2 Wisconsin 49 43
Morning Consult 9-2 Wisconsin 47 44
Morning Consult 9-2 Wisconsin 48 43
Morning Consult 9-2 Wisconsin 49 43
Morning Consult 9-2 Wisconsin 48 43
Morning Consult 9-2 Wisconsin 48 44
Morning Consult 9-2 Wisconsin 47 45
Morning Consult 9-2 Wisconsin 47 45
Morning Consult 9-2 Wisconsin 47 45
Fox News 9-2 Wisconsin 49 41
Fox News 9-2 North Carolina 49 45
Fox News 9-2 Wisconsin 50 42
Fox News 9-2 North Carolina 50 46
Fox News 9-2 Arizona 49 40
Fox News 9-2 Arizona 49 39
Ipsos 9-2 National 43 38
SSRS 9-2 National 51 43
Harris Insights & Analytics 9-2 National 46 40
Morning Consult 9-2 National 51 43
Morning Consult 9-2 National 51 43
Morning Consult 9-2 National 50 43
Morning Consult 9-2 National 51 44
Morning Consult 9-2 National 52 42
Morning Consult 9-2 National 51 43
Quinnipiac University 9-2 National 52 42
Qriously 9-2 National 46 41
Opinium 9-2 Florida 50 43
Opinium 9-2 Wisconsin 53 39
IBD 9-2 National 49 41
YouGov 9-2 National 51 40
Rasmussen Reports 9-2 National 48 45
Monmouth University 9-2 Pennsylvania 49 46
Monmouth University 9-2 Pennsylvania 49 45
Monmouth University 9-2 Pennsylvania 48 47
Suffolk University 9-2 National 46 41
Ipsos 9-2 National 47 40
USC Dornsife 9-2 National 51 42
USC Dornsife 9-2 National 51 41
Opinium 9-2 National 53 39
Suffolk University 9-2 National 49 43
Selzer & Co. 9-2 National 49 41
Redfield & Wilton Strategies 9-1 National 49 40
Landmark Communications 9-1 Georgia 40 47
East Carolina University 9-1 North Carolina 46 48
Public Policy Polling 9-1 Michigan 48 44
Expedition Strategies 9-1 Montana 44 48
University of Nevada, Las Vegas 9-1 Nevada 44 38
Morning Consult 9-1 National 52 43
Morning Consult 9-1 National 51 43
Morning Consult 9-1 Texas 47 48
Morning Consult 9-1 Florida 49 47
Morning Consult 9-1 Pennsylvania 49 45
Morning Consult 9-1 National 51 43
Morning Consult 9-1 North Carolina 49 47
Morning Consult 9-1 Ohio 45 50
Morning Consult 9-1 Minnesota 50 43
Morning Consult 9-1 Florida 50 45
Morning Consult 9-1 Georgia 49 46
Morning Consult 9-1 Michigan 50 44
Morning Consult 9-1 Georgia 46 47
Morning Consult 9-1 Colorado 51 41
Morning Consult 9-1 Wisconsin 52 43
Morning Consult 9-1 Michigan 52 42
Morning Consult 9-1 Arizona 52 42
Morning Consult 9-1 Colorado 51 41
Morning Consult 9-1 Texas 46 47
Morning Consult 9-1 Minnesota 50 42
Morning Consult 9-1 Ohio 45 49
Morning Consult 9-1 North Carolina 49 46
Morning Consult 9-1 Pennsylvania 50 44
Morning Consult 9-1 Arizona 45 47
USC Dornsife 9-1 National 51 41
USC Dornsife 9-1 National 51 41
Léger 9-1 National 49 42
AtlasIntel 9-1 National 49 46
Emerson College 8-31 National 51 48
RMG Research 8-31 National 48 44
Global Strategy Group 8-31 Pennsylvania 53 43
Global Strategy Group 8-31 Pennsylvania 50 42
Public Policy Polling 8-31 Georgia 47 46
Harris Insights & Analytics 8-31 National 47 38
GQR Research (GQRR) 8-31 Pennsylvania 52 43
Trafalgar Group 8-31 Missouri 41 51
USC Dornsife 8-31 National 53 40
USC Dornsife 8-31 National 52 40
John Zogby Strategies 8-30 National 45 42
John Zogby Strategies 8-30 National 48 42
USC Dornsife 8-30 National 54 39
USC Dornsife 8-30 National 53 39

Election Predictions

Prognosticators

Prognosticators are folks who make projected electoral maps, often on the strength of educated guesses as well as inside information in some cases from campaigns sharing internals with the teams involved. Below are a few of these prognosticators and their assessment of the state of the race:

Polling Models

Polling models are similar to prognosticators (and often the model authors will act like pundits as well), but tend to be about making "educated guesses" on the state of the election. Generally, the models are structured to take in data such as polls and electoral fundamentals, and make a guess based on research on prior elections as to the state of the race in each state. Below are a few of the more prominent models that are online or expected to be online soon:

Prediction Markets

Prediction markets are betting markets where people put money on the line to estimate the likelihood of one party winning a seat or state. Most of these markets will also tend to move depending on polling and other socioeconomic factors in the same way that prognosticators and models will work. Predictit and Election Betting Odds are prominent in this space, although RealClearPolitics has an aggregate of other betting sites as well.
submitted by TheUnknownStitcher to politics [link] [comments]

General Election Polling Discussion Thread (Aug 9, 2020)

Introduction

Welcome to the /politics polling discussion thread for the general election. As the election nears, polling of both the national presidential popular vote and important swing states is ramping up, and with both parties effectively deciding on nominees, pollsters can get in the field to start assessing the state of the presidential race.
Please use this thread to discuss polling and the general state of the presidential or congressional election. Below, you'll find some of the most recent polls, but this is by no means exhaustive, as well as some links to prognosticators sharing election models.
As always though, polls don't vote, people do. Regardless of whether your candidate is doing well or poorly, democracy only works when people vote, and there are always at least a couple polling misses every cycle, some of which are pretty high profile. If you haven't yet done so, please take some time to register to vote or check your registration status.

Polls

Below is a collection of recent polling of the US Presidential election. This is likely incomplete and also omits the generic congressional ballot as well as Senate/House/Gubernatorial numbers that may accompany these polls. Please use the discussion space below to discuss any additional polls not covered. Additionally, not all polls are created equal. If this is your first time looking at polls, the FiveThirtyEight pollster ratings page is a helpful tool to assess historic partisan lean in certain pollsters, as well as their past performance.
Poll Date Type Biden Trump
YouGov 8-9 Pennsylvania 49 43
YouGov 8-9 Wisconsin 48 42
Global Strategy Group 8-7 National 49 45
Zogby Interactive 8-7 National 46 46
Zogby Interactive 8-7 National 46 46
Zogby Interactive 8-7 National 46 45
Trafalgar Group 8-7 Texas 43 49
Public Policy Polling 8-7 Kansas 43 50
Research Co. 8-7 National 48 38
EPIC-MRA 8-7 Michigan 51 40
Harris Insights & Analytics 8-5 National 43 40
RMG Research 8-6 Iowa 40 41
Quinnipiac University 8-6 South Carolina 42 47
Quinnipiac University 8-6 Maine CD-1 61 30
Quinnipiac University 8-6 Maine CD-2 44 45
Quinnipiac University 8-6 Kentucky 41 50
Quinnipiac University 8-6 Maine 52 37
David Binder Research 8-6 Michigan 51 41
David Binder Research 8-6 Wisconsin 53 42
David Binder Research 8-6 Minnesota 54 36
David Binder Research 8-6 Iowa 49 43
DFM Research 8-6 Oklahoma 36 56
Data for Progress 8-6 Maine 53 43
Data for Progress 8-6 Iowa 45 46
Data for Progress 8-6 Maine 49 42
Data for Progress 8-6 North Carolina 49 45
Data for Progress 8-6 North Carolina 46 44
Data for Progress 8-6 Iowa 42 44
Data for Progress 8-6 Arizona 47 44
Data for Progress 8-6 Arizona 45 43
Bluegrass Voters Coalition 8-5 Kentucky 34 55
Morning Consult 8-5 Indiana 38 55
Bluegrass Voters Coalition 8-5 Kentucky 45 52
Ipsos 8-5 National 54 45
Ipsos 8-5 National 56 44
Marquette University Law School 8-5 Wisconsin 52 44
Marquette University Law School 8-5 Wisconsin 49 45
Rasmussen Reports 8-5 National 48 45
Monmouth University 8-5 Iowa 46 48
Monmouth University 8-5 Iowa 45 48
Monmouth University 8-5 Iowa 47 47
YouGov 8-5 National 49 40
Zogby Interactive 8-5 North Carolina 44 40
Zogby Interactive 8-5 Florida 43 43
Zogby Interactive 8-5 Ohio 43 41
Zogby Interactive 8-5 Pennsylvania 44 43
MRG Research 8-5 Hawaii 56 29
Hodas & Associates 8-5 Wisconsin 52 37
Hodas & Associates 8-5 Michigan 52 40
Hodas & Associates 8-5 Pennsylvania 50 44
University of California, Berkeley 8-4 California 67 28
Morning Consult 8-4 National 50 43
Morning Consult 8-4 National 50 43
Morning Consult 8-4 National 50 43
Morning Consult 8-4 National 51 42
Morning Consult 8-4 National 51 42
Morning Consult 8-4 National 51 42
Morning Consult 8-4 National 50 43
Morning Consult 8-4 Texas 47 46
Morning Consult 8-4 South Carolina 44 49
Morning Consult 8-4 Kentucky 35 59
Morning Consult 8-4 Alabama 36 58
Fox News 8-3 National 48 41
Public Policy Polling 8-3 Michigan 49 43
Global Strategy Group 8-3 Wisconsin 51 42
Emerson College 8-3 Montana 45 54
Center for Marketing and Opinion Research 8-3 Ohio 45 41
YouGov 8-2 Georgia 46 45
YouGov 8-2 North Carolina 48 44
Emerson College 7-31 National 53 46
YouGov 7-31 National 49 40
Data for Progress 7-31 National 51 42
Data for Progress 7-31 National 50 43
Public Policy Polling 7-31 Minnesota 52 42
University of New Hampshire 7-30 New Hampshire 52 39
University of New Hampshire 7-30 New Hampshire 44 46
University of New Hampshire 7-30 New Hampshire 53 40
IBD 7-30 National 48 41
Virginia Commonwealth University 7-30 Virginia 50 39
Redfield & Wilton Strategies 7-30 Wisconsin 45 35
Redfield & Wilton Strategies 7-30 Michigan 49 37
Redfield & Wilton Strategies 7-30 Arizona 46 38
Redfield & Wilton Strategies 7-30 Pennsylvania 48 41
Redfield & Wilton Strategies 7-30 North Carolina 43 42
Redfield & Wilton Strategies 7-30 Florida 48 41
Franklin & Marshall College 7-30 Pennsylvania 50 41
Cardinal Point Analytics (CardinalGPS) 7-30 North Carolina 46 48
Mason-Dixon Polling & Strategy 7-30 Florida 50 46
Harris Insights & Analytics 7-29 National 55 45
Optimus 7-29 National 47 40
Optimus 7-29 National 38 31
TargetPoint 7-29 Michigan 49 33
Rasmussen Reports 7-29 National 48 42
Monmouth University 7-29 Georgia 47 47
Monmouth University 7-29 Georgia 47 48
Monmouth University 7-29 Georgia 46 49
YouGov 7-29 National 49 40
Zogby Interactive 7-29 National 44 40
Ipsos 7-29 National 57 43
Ipsos 7-29 National 57 43
Change Research 7-29 Pennsylvania 48 46
Change Research 7-29 Florida 48 45
Change Research 7-29 National 51 42
Change Research 7-29 Arizona 47 45
Change Research 7-29 Michigan 46 42
Change Research 7-29 Wisconsin 48 43
Change Research 7-29 North Carolina 49 46
SurveyUSA 7-28 Washington 62 28
Morning Consult 7-28 Wisconsin 49 44
Morning Consult 7-28 North Carolina 46 49
Morning Consult 7-28 Michigan 50 42
Morning Consult 7-28 Minnesota 49 42
Morning Consult 7-28 Florida 47 48
Morning Consult 7-28 Ohio 42 50
Morning Consult 7-28 Virginia 52 42
Morning Consult 7-28 Pennsylvania 48 44
Morning Consult 7-28 Texas 43 50
Morning Consult 7-28 Georgia 47 49
Morning Consult 7-28 Colorado 50 42
Morning Consult 7-28 Arizona 45 47
Colby College 7-28 Maine 50 38
Colby College 7-28 Maine CD-1 55 35
Colby College 7-28 Maine CD-2 45 42
Public Policy Polling 7-28 Montana 45 50
Public Policy Polling 7-28 North Carolina 49 46
Public Policy Polling 7-28 Alaska 44 50
Public Policy Polling 7-28 Maine 53 42
Public Policy Polling 7-28 Georgia 46 45
Public Policy Polling 7-28 Colorado 54 41
Public Policy Polling 7-28 Iowa 47 48
DKC Analytics 7-28 New Jersey 51 33
MassINC Polling Group 7-28 Massachusetts 55 23
Morning Consult 7-28 National 50 42
Morning Consult 7-28 National 50 42
Morning Consult 7-28 National 50 42
Morning Consult 7-28 National 50 42
Morning Consult 7-28 National 50 42
Morning Consult 7-28 National 50 42
Morning Consult 7-28 National 51 42
Morning Consult 7-28 National 50 42
Morning Consult 7-28 National 50 43
Morning Consult 7-28 National 51 42
Morning Consult 7-28 National 51 42
Morning Consult 7-28 National 51 42
Morning Consult 7-28 National 50 42
Morning Consult 7-28 National 50 43
Morning Consult 7-28 National 51 42
Morning Consult 7-28 National 50 42
Morning Consult 7-28 National 50 42
Morning Consult 7-28 National 51 42
Morning Consult 7-28 National 50 42
Morning Consult 7-28 National 51 42
Morning Consult 7-28 National 50 43
Morning Consult 7-28 National 50 42
Morning Consult 7-28 National 51 42
Morning Consult 7-28 National 50 42
Morning Consult 7-28 National 50 42
Morning Consult 7-28 National 50 42
Morning Consult 7-28 National 50 42
Morning Consult 7-28 National 50 42
Morning Consult 7-28 National 51 42
Morning Consult 7-28 National 51 42
Morning Consult 7-28 National 48 44
Morning Consult 7-28 National 49 44
Morning Consult 7-28 National 49 43
Morning Consult 7-28 Minnesota 47 44
Morning Consult 7-28 Texas 47 45
Morning Consult 7-28 Michigan 52 42
Morning Consult 7-28 Georgia 47 46
Morning Consult 7-28 North Carolina 47 47
Morning Consult 7-28 Ohio 45 48
Morning Consult 7-28 Pennsylvania 50 42
Morning Consult 7-28 Virginia 52 41
Morning Consult 7-28 Florida 49 46
Morning Consult 7-28 Wisconsin 50 43
Morning Consult 7-28 Colorado 52 39
Morning Consult 7-28 Arizona 49 42
ALG Research 7-27 South Carolina 45 50
Trafalgar Group 7-27 Minnesota 49 44
brilliant corners Research & Strategies 7-27 South Carolina 43 50
Harris Insights & Analytics 7-27 National 55 45
Kaiser Family Foundation 7-27 National 47 38
Marist College 7-27 North Carolina 51 44
AP-NORC 7-27 National 46 34
YouGov 7-26 National 51 41
YouGov 7-26 Michigan 48 42
YouGov 7-26 Ohio 45 46
Marist College 7-26 Arizona 50 45
SSRS 7-26 Michigan 52 40
SSRS 7-26 Arizona 49 45
SSRS 7-26 Florida 51 46
Gravis Marketing 7-25 Pennsylvania 48 45
Echelon Insights 7-24 National 52 43
Echelon Insights 7-24 National 51 41
Echelon Insights 7-24 National 49 40
Echelon Insights 7-24 National 53 38
Echelon Insights 7-24 National 50 37
Gravis Marketing 7-24 Michigan 51 42
Gravis Marketing 7-24 Wisconsin 50 42
Data for Progress 7-24 National 49 43
Data for Progress 7-24 National 49 43
Fox News 7-23 Michigan 49 40
Fox News 7-23 Minnesota 51 38
Fox News 7-23 Pennsylvania 50 39
Global Strategy Group 7-23 National 50 39
Garin-Hart-Yang Research Group 7-23 National 51 43
GQR Research (GQRR) 7-23 National 55 44

Election Predictions

Prognosticators

Prognosticators are folks who make projected electoral maps, often on the strength of educated guesses as well as inside information in some cases from campaigns sharing internals with the teams involved. Below are a few of these prognosticators and their assessment of the state of the race:

Polling Models

Polling models are similar to prognosticators (and often the model authors will act like pundits as well), but tend to be about making "educated guesses" on the state of the election. Generally, the models are structured to take in data such as polls and electoral fundamentals, and make a guess based on research on prior elections as to the state of the race in each state. Below are a few of the more prominent models that are online or expected to be online soon:

Prediction Markets

Prediction markets are betting markets where people put money on the line to estimate the likelihood of one party winning a seat or state. Most of these markets will also tend to move depending on polling and other socioeconomic factors in the same way that prognosticators and models will work. Predictit and Election Betting Odds are prominent in this space, although RealClearPolitics has an aggregate of other betting sites as well.
submitted by galleyest to politics [link] [comments]

General Election Polling Discussion Thread (July 19, 2020)

Introduction

Welcome to the /politics polling discussion thread for the general election. As the election nears, polling of both the national presidential popular vote and important swing states is ramping up, and with both parties effectively deciding on nominees, pollsters can get in the field to start assessing the state of the presidential race.
Please use this thread to discuss polling and the general state of the presidential or congressional election. Below, you'll find some of the most recent polls, but this is by no means exhaustive, as well as some links to prognosticators sharing election models.
As always though, polls don't vote, people do. Regardless of whether your candidate is doing well or poorly, democracy only works when people vote, and there are always at least a couple polling misses every cycle, some of which are pretty high profile. If you haven't yet done so, please take some time to register to vote or check your registration status.

Polls

Below is a collection of recent polling of the US Presidential election. Where the same poll applied different screening methodologies (All Adults, Registered Voters, Likely Voters), the result is shown as the most restrictive (Likely Voters > Registered Voters > All Adults). This is likely incomplete and also omits the generic congressional ballot as well as Senate/House/Gubernatorial numbers that may accompany these polls. Please use the discussion space below to discuss any additional polls not covered. Additionally, not all polls are created equal. If this is your first time looking at polls, the FiveThirtyEight pollster ratings page is a helpful tool to assess historic partisan lean in certain pollsters, as well as their past performance.
Poll Date Type Biden Trump
Fox News 7-19 National 49 41
ABC News/The Washington Post 7-19 National 54 44
Gravis Marketing 7-18 South Carolina 46 50
Public Policy Polling 7-18 Michigan 51 44
Garin-Hart-Yang Research Group 7-16 Kentucky 41 53
OH Predictive Insights 7-16 Arizona 49 44
Democracy Fund + UCLA Nationscape 7-17 National 49 41
Alaska Survey Research 7-17 Alaska 48 49
Monmouth University 7-15 Pennsylvania 51 44
NBC News 7-15 National 51 40
Ipsos 7-15 National 47 37
Quinnipiac University 7-15 National 52 37
YouGov 7-15 National 47 39
Rasmussen Reports 7-15 National 47 44
Monmouth University 7-15 Pennsylvania 52 42
YouGov 7-15 National 49 40
Morning Consult 7-15 National 47 39
Change Research 7-15 Michigan 48 42
Change Research 7-15 Wisconsin 48 42
Change Research 7-15 Pennsylvania 50 42
Change Research 7-15 North Carolina 47 46
Change Research 7-15 Florida 50 43
Change Research 7-15 Arizona 51 45
Change Research 7-15 National 51 41
Gravis Marketing 7-14 Texas 44 46
Gravis Marketing 7-14 Florida 53 43
Civiqs 7-14 Montana 45 49
Redfield & Wilton Strategies 7-13 National 48 39
RMG Research 7-13 National 46 39
YouGov 7-13 Missouri 42 49
Public Policy Polling 7-13 Montana 42 51
GQR Research (GQRR) 7-13 Nebraska CD-2 51 44
John Zogby Strategies 7-12 National 49 42
Gravis Marketing 7-12 Georgia 45 48
YouGov 7-12 Arizona 46 46
YouGov 7-12 Florida 48 42
YouGov 7-12 Texas 45 46
University of Texas at Tyler 7-12 Texas 48 43
GBAO 7-10 North Carolina 48 46
GBAO 7-10 Arizona 47 46
GBAO 7-10 Iowa 45 48
Morning Consult 7-10 National 48 39
Auburn University at Montgomery 7-10 Alabama 40 55
Data for Progress 7-10 National 51 41
Public Policy Polling 7-9 North Carolina 50 46
Public Policy Polling 7-9 Alaska 45 48
Harris Insights & Analytics 7-8 National 43 39
Rasmussen Reports 7-8 National 50 40
Ipsos 7-8 National 43 37
Opinium 7-8 National 52 40
Research Co. 7-8 National 49 40
YouGov 7-8 National 49 40
PureSpectrum 7-8 National 47 37
Public Policy Polling 7-7 National 53 42
Trafalgar Group 7-6 Pennsylvania 48 42
Public Policy Polling 7-6 Maine 53 42
Trafalgar Group 7-3 Florida 45 45
YouGov 7-2 National 45 40
Monmouth University 7-2 National 53 41
YouGov 7-2 Texas 44 48
Public Policy Polling 7-2 Texas 48 46
University of Montana 7-1 Montana 37 52
Garin-Hart-Yang Research Group 7-1 National 55 41
Gravis Marketing 7-1 Arizona 45 49
Public Policy Polling 7-1 Michigan 50 44
Ipsos 7-1 National 46 38
Harris Insights & Analytics 7-1 National 56 44
Public Policy Polling 7-1 Colorado 56 39
IBD 7-1 National 48 40
Data Orbital 7-1 Arizona 47 45
YouGov 7-1 National 49 40
Morning Consult 7-1 National 47 40
Change Research 7-1 National 49 41
Change Research 7-1 Arizona 51 44
Change Research 7-1 Florida 50 45
Change Research 7-1 Michigan 48 43
Change Research 7-1 North Carolina 51 44
Change Research 7-1 Pennsylvania 50 44
Change Research 7-1 Wisconsin 51 43
East Carolina University 6-30 North Carolina 45 43
Suffolk University 6-30 National 53 41
Pew Research Center 6-30 National 54 44
Garin-Hart-Yang Research Group 6-30 Missouri 48 46
Siena College 6-30 New York 57 32

Election Predictions

Prognosticators

Prognosticators are folks who make projected electoral maps, often on the strength of educated guesses as well as inside information in some cases from campaigns sharing internals with the teams involved. Below are a few of these prognosticators and their assessment of the state of the race:

Polling Models

Polling models are similar to prognosticators (and often the model authors will act like pundits as well), but tend to be about making "educated guesses" on the state of the election. Generally, the models are structured to take in data such as polls and electoral fundamentals, and make a guess based on research on prior elections as to the state of the race in each state. Below are a few of the more prominent models that are online or expected to be online soon:

Prediction Markets

Prediction markets are betting markets where people put money on the line to estimate the likelihood of one party winning a seat or state. Most of these markets will also tend to move depending on polling and other socioeconomic factors in the same way that prognosticators and models will work. Predictit and Election Betting Odds are prominent in this space, although RealClearPolitics has an aggregate of other betting sites as well.
submitted by Isentrope to politics [link] [comments]

General Election Polling Discussion Thread (June 2020)

Introduction

Welcome to the /politics polling discussion thread for the general election. As the election nears, polling of both the national presidential popular vote and important swing states is ramping up, and with both parties effectively deciding on nominees, pollsters can get in the field to start assessing the state of the presidential race.
Please use this thread to discuss polling and the general state of the presidential or congressional election. Below, you'll find some of the most recent polls, but this is by no means exhaustive, as well as some links to prognosticators sharing election models.
As always though, polls don't vote, people do. Regardless of whether your candidate is doing well or poorly, democracy only works when people vote, and there are always at least a couple polling misses every cycle, some of which are pretty high profile. If you haven't yet done so, please take some time to register to vote or check your registration status.

Polls

Below is a collection of recent polling of the US Presidential election. This is likely incomplete and also omits the generic congressional ballot as well as Senate/House/Gubernatorial numbers that may accompany these polls. Please use the discussion space below to discuss any additional polls not covered. Additionally, not all polls are created equal. If this is your first time looking at polls, the FiveThirtyEight pollster ratings page is a helpful tool to assess historic partisan lean in certain pollsters, as well as their past performance.
Pollster Date Released Race Trump Biden
Yougov 6/26 National 39 47
Marist/NPPBS 6/26 National 44 52
HarrisX 6/26 National 39 43
KFF 6/26 National 38 51
Climate Nexus 6/26 National 41 48
Fox News 6/25 Texas 44 45
Fox News 6/25 N. Carolina 45 47
Fox News 6/25 Georgia 45 47
Fox News 6/25 Florida 40 49
CNBC/Hart/POS 6/25 National 38 47
Hodas (R) 6/25 Michigan 38 56
Hodas (R) 6/25 Wisconsin 39 55
Hodas (R) 6/25 Pennsylvania 42 54
Redfield & Wilton 6/25 Wisconsin 36 45
Redfield & Wilton 6/25 N. Carolina 40 46
Redfield & Wilton 6/25 Arizona 39 43
Redfield & Wilton 6/25 Michigan 36 47
Redfield & Wilton 6/25 Pennsylvania 39 49
Redfield & Wilton 6/25 Florida 41 45
Siena/NYT Upshot 6/25 N. Carolina 40 49
Siena/NYT Upshot 6/25 Florida 41 47
Siena/NYT Upshot 6/25 Michigan 36 47
Siena/NYT Upshot 6/25 Pennsylvania 40 50
Siena/NYT Upshot 6/25 Arizona 41 48
Data for Progress 6/24 National 44 50
PPP (D) 6/24 N. Carolina 46 48
Ipsos 6/24 National 37 47
Quinnipiac U. 6/24 Ohio 45 46
Siena/NYT Upshot 6/24 National 36 50
Morning Consult 6/24 National 39 47
Marquette LS 6/24 Wisconsin 42 51
PPP (D) 6/23 National 43 52
PPP (D) 6/23 Texas 48 46
Trafalgar (R) 6/22 Michigan 45 46
Echelon 6/22 National 42 50
Gravis 6/20 Minnesota 42 58
SurveyMonkey 6/20 National 43 53
Gravis/OANN 6/20 N. Carolina 46 43
Saint Anselm College 6/18 New Hampshire 42 49
Fox News 6/18 National 38 50
0ptimus 6/18 National 44 50
Civiqs (D) 6/18 Kentucky 57 37
Quinnipiac U. 6/18 National 41 49
UCLA/Democracy Fund 6/18 National 39 50
Change Research 6/17 Arizona 44 45
Change Research 6/17 N. Carolina 45 47
Change Research 6/17 Michigan 45 47
Change Research 6/17 Wisconsin 44 48
Change Research 6/17 Pennsylvania 46 49
Change Research 6/17 Florida 43 50
Change Research 6/17 National 41 51
Civiqs (D) 6/16 Arizona 45 49
PPP (D) 6/16 Georgia 46 48
PPP (D) 6/16 New Mexico 39 53
TIPP/Am. Greatness (R) 6/16 Michigan 38 51
TIPP/Am. Greatness (R) 6/16 Florida 40 51
NORC/AEI 6/16 National 32 40
EPIC-MRA 6/16 Michigan 39 55
Scott Rasmussen 6/15 National 36 48
Abacus Data 6/15 National 41 51
SelzeDMR 6/15 Iowa 44 43
Hendrix College 6/14 Arkansas 47 45
Remington Research (R) 6/13 Missouri 51 43
Meeting Street Insights 6/12 National 38 49

Election Predictions

Prognosticators

Prognosticators are folks who make projected electoral maps, often on the strength of educated guesses as well as inside information in some cases from campaigns sharing internals with the teams involved. Below are a few of these prognosticators and their assessment of the state of the race:

Polling Models

Polling models are similar to prognosticators (and often the model authors will act like pundits as well), but tend to be about making "educated guesses" on the state of the election. Generally, the models are structured to take in data such as polls and electoral fundamentals, and make a guess based on research on prior elections as to the state of the race in each state. Below are a few of the more prominent models that are online or expected to be online soon:

Prediction Markets

Prediction markets are betting markets where people put money on the line to estimate the likelihood of one party winning a seat or state. Most of these markets will also tend to move depending on polling and other socioeconomic factors in the same way that prognosticators and models will work. Predictit and Election Betting Odds are prominent in this space, although RealClearPolitics has an aggregate of other betting sites as well.
submitted by Isentrope to politics [link] [comments]

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