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2014 Record 2015 Record My record 2016: Total (weeks 1-2) – SU: 21-11 ATS: 17-14-1 O/U: 14-16-2 Week 1 – SU: 12-4 ATS: 10-5-1 O/U: 5-10-1 Week 2 – SU: 9-7 ATS: 7-9 O/U: 9-6-1 NY Jets at Buffalo
Prediction: Bills 21-19 (56.5%)Pick: Bills +3 Total: Under 40.5
Tampa Bay at Arizona
Prediction: Cardinals 24-19 (62.5%)
Pick: Buccaneers +6.5
Total: Under 50.5
San Francisco at Carolina
Prediction: Panthers 22-19 (56.4%)
Pick: 49ers +13.5
Total: Under 45.5
Baltimore at Cleveland
Prediction: Ravens 23-21 (54.5%)
Pick: Browns +7
Total: Over 42.5
Indianapolis at Denver
Prediction: Broncos 26-21 (63.8%)
Pick: Colts +6
Total: Over 45.5
Tennessee at Detroit
Prediction: Lions 25-18 (63.8%)
Pick: Lions -5.5
Total: Under 47
Kansas City at Houston
Prediction: Texans 21-20 (52.8%)
Pick: Chiefs +2
Total: Under 43.5
Miami at New England
Prediction: Patriots 26-21 (64.3%)
Pick: Dolphins +6.5
Total: Over 41.5
New Orleans at NY Giants
Prediction: Saints 27-26 (51.7%)
Pick: Saints +4.5
Total: Under 53.5
Atlanta at Oakland
Prediction: Falcons 23-22 (51.3%)
Pick: Falcons +4.5
Total: Under 50
Cincinnati at Pittsburgh
Prediction: Steelers 24-22 (54.5%)
Pick: Bengals +3.5
Total: Under 48.5
Jacksonville at San Diego
Prediction: Chargers 26-19 (68.1%)
Pick: Chargers -3
Total: Under 47
Seattle at Los Angeles (nee St. Louis)
Prediction: Seahawks 22-17 (64.2%)
Pick: Seahawks -3.5
Total: Over 39
Dallas at Washington
Prediction: Washington Football Team 23-22 (50.0%)
Pick: Cowboys +3.5
Total: Under 45.5
Green Bay at Minnesota
Prediction: Packers 23-21 (55.9%)
Pick: Vikings +2.5
Total: Under 44
Philadelphia at Chicago
Prediction: Bears 25-24 (50.8%)
Pick: Eagles +3
Total: Over 43 PUSH
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Key: Team -Median Record (Mean Wins)
AFC
East
New England: 12-4 (11.562)
Buffalo: 7-9 (7.388)
NY Jets: 7-9 (7.068)
Miami: 6-10 (6.243)
North
Cincinnati: 10-6 (10.348)
Pittsburgh: 10-6 (10.249)
Baltimore: 9-7 (8.666)
Cleveland: 5-11 (4.557)
South
Houston: 8-8 (8.399)
Indianapolis: 8-8 (7.962)
Tennessee: 5-11 (4.621)
Jacksonville: 4-12 (3.666)
West
Denver: 12-4 (12.228)
Kansas City: 10-6 (10.127)
Oakland: 5-11 (5.107)
San Diego: 8-8 (8.212)
NFC
East
Dallas: 8-8 (8.036)
Philadelphia: 8-8 (7.549)
NY Giants: 7-9 (6.913)
Washington: 5-11 (5.347)
North
Green Bay: 13-3 (12.476)
Detroit: 9-7 (8.978)
Minnesota: 9-7 (8.542)
Chicago: 7-9 (7.042)
South
Carolina: 11-5 (10.757)
New Orleans: 8-8 (8.295)
Atlanta: 6-10 (6.510)
Tampa Bay: 4-12 (4.386)
West
Seattle: 13-3 (13.386)
Arizona: 9-7 (9.089)
San Francisco: 7-9 (6.724)
Los Angeles (nee St. Louis): 6-10 (5.567)
Playoff Predictions
AFC
- Denver
- New England
- Cincinnati
- Houston
- Pittsburgh
- Kansas City
NFC
- Seattle
- Green Bay
- Carolina
- Dallas
- Arizona
- Detroit
Wild Card Games
Kansas City (6) beats Cincinnati (3)
Pittsburgh (5) beats Houston(4)
(3) Carolina beats (6) Detroit
(5) Arizona beats (4) Dallas
Divisional Round
(1) Denver beats (6) Kansas City
(2) New England beats (5) Pittsburgh
(1) Seattle beats (5) Arizona
(3) Carolina beats (2) Green Bay
Conference Championships
(1) Denver beats (2) New England
(1) Seattle beats (3) Carolina
Super Bowl
(1) Seattle beats (1) Denver
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Team WinDivison MakePlayoffs MakeSuperBowl WinSuperBowl ARI 3.0 48.9 3.0 0.9 ATL 3.9 10.2 1.5 0.7 BAL 13.9 35.3 3.4 0.7 BUF 4.2 13.3 1.8 0.6 CAR 79.5 87.5 15.4 9.2 CHI 1.7 12.5 1.4 0.4 CIN 44.1 71.3 11.0 4.7 CLE 0.1 0.4 0.0 0.0 DAL 42.8 46.8 4.3 1.1 DEN 76.8 95.9 25.4 12.8 DET 8.3 47.5 4.7 2.4 GB 84.7 97.2 24.6 13.7 HOU 54.1 57.2 7.7 2.4 IND 42.0 44.5 5.3 0.8 JAC 0.9 1.0 0.1 0.0 KC 19.0 67.6 8.1 3.2 MIA 1.3 5.1 0.7 0.5 MIN 5.3 37.8 3.2 1.7 NE 90.3 94.1 20.9 9.8 NO 16.4 35.8 3.8 1.5 NYG 22.6 24.4 2.6 0.6 NYJ 4.2 14.1 1.6 0.5 OAK 0.1 1.3 0.0 0.0 PHI 29.6 33.4 3.4 1.3 PIT 41.9 69.0 11.9 5.6 SD 4.1 26.8 2.0 0.7 SEA 96.8 99.9 30.5 23.6 SF 0.2 9.1 0.9 0.5 LA 0.0 2.4 0.0 0.0 TB 0.2 0.6 0.2 0.0 TEN 3.0 3.1 0.1 0.0 WAS 5.0 6.0 0.5 0.1 Team Retro Prosp PredMargin Change W L 17 SEA 50 87 5.722 9 CAR 54 72 2.402 0 1 3 DEN 58 71 3.583 1 0 24 NE 46 70 3.708 2 GB 59 66 3.474 6 KC 56 62 1.717 7 PIT 55 59 1.776 15 CIN 50 58 2.073 19 HOU 47 57 -0.140 14 SF 51 56 -0.540 4 NYJ 57 55 -0.107 21 BUF 47 54 -0.371 20 DET 47 53 0.318 28 MIN 44 53 0.071 12 NO 53 53 0.646 32 BAL 40 52 0.139 1 ARI 60 50 1.334 27 SD 45 48 -0.350 23 CHI 46 45 -1.328 5 WAS 57 43 -2.130 31 DAL 42 43 -0.486 10 PHI 53 42 -0.273 13 ATL 53 41 -0.704 8 STL 54 41 -1.449 26 MIA 45 39 -1.063 18 TB 49 38 -2.566 16 IND 50 36 -0.699 25 NYG 46 35 -1.196 29 OAK 43 34 -2.595 11 CLE 53 32 -2.849 30 TEN 42 25 -3.776 22 JAC 46 23 -4.341 -
2014 Record 2015 Record My record 2016: Total (weeks 1-16) – SU: 12-4 ATS: 10-5-1 O/U: 5-10-1 Week 1 – SU: 12-4 ATS: 10-5-1 O/U: 5-10-1 Carolina at Denver
Prediction: Broncos 23-20 (58%)
Pick: Broncos +3
Total: Over 40.5
New England at Arizona
Prediction: Patriots 24-23 (52%)Pick: Patriots +9 Total: Over 44 PUSH
Tampa Bay at Atlanta
Prediction: Falcons 25-21 (60.1%)
Pick: Falcons -2.5
Total: Under 47
Buffalo at Baltimore
Prediction: Ravens 22-20 (56.2%)
Pick: Bills +3
Total: Under 44.5
NY Giants at Dallas
Prediction: Cowboys 24-22 (56.8%)
Pick: Dallas +1 PUSH
Total: Under 47.5
Chicago at Houston
Prediction: Texans 23-20 (58%)
Pick: Bears +5.5
Total: Over 42.5
Detroit at Indianapolis
Prediction: Colts 23-22 (51.8%)
Pick: Lions +3
Total: Under 50.5
Green Bay at Jacksonville
Prediction: Packers 26-19 (67%)
Pick: Packers -3.5
Total: Under 47.5
San Diego at Kansas City
Prediction: Chiefs 24-20 (60.5%
Pick: Chargers +6.5
Total: Under 46
Oakland at New Orleans
Prediction: Saints 27-22 (63.8%)
Pick: Saints -3
Total: Under 50.5
Cincinnati at NY Jets
Prediction: Bengals 21-20 (51.5%)
Pick: Bengals -1
Total: Under 42
Cleveland at Philadelphia
Prediction: Eagles 26-22
Pick: Eagles -3.5
Total: Over 41
Miami at Seattle
Prediction: Seahawks 25-17
Pick: Dolphins +10.5
Total: Under 44
Minnesota at Tennessee
Prediction: Vikings 21-19
Pick: Titans +2.5
Total: Under 40
Pittsburgh at Washington
Prediction: Steelers 25-22 (56.4%)
Pick: Steelers -2.5
Total: Under 50
Los Angeles (nee St. Louis) at San Francisco
Prediction: 49ers 21-18 (57.3%)
Pick: 49ers +2.5
Total: Under 43
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One of my colleagues, Tim O’Brien, showed a slide in the first week of his classes describing how he first found out about R:
Here is that email from 1996 (TWENTY years ago!!!) where Tim asked Ross Ihaka how to get R, and Ross helped him out. #amazing #history
Cheers.
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There is a general election happening right now and the NFL season is starting. Let’s talk about the candidates chances in terms of NFL games.
At the The Upshot they track 8 different presidential forecasts, 5 of which give actual percentages. Currently (at 11:07am on September 2nd) Clinton’s win probabilities range from a high of 94% based on the Princeton Election Consortium’s forecast to a low of 74% for FiveThirtyEight and DailyKos. (PredictWise has it at 77% and the New York Times has it at 87%).
Let’s put these probabilities in context using Pro Football Reference’s NFL win probability calculator:
Let’s start by looking at the worst case scenario for Trump: 6% chance to win. (Unless otherwise noted, I’m assuming the spread is 0.)
- 5.9%: A 21 point underdog wins the game outright.
- 5.8%: Your team is down 15 at halftime.
- 5.97%: Your team has the ball and is trailing by 7 with 2 minutes left with 1st and 10 from your own 3 yard line.
- 6.09%: Your team has the ball and is trailing by 3 with 10 seconds left with 1st and 10 from your own 10 yard line.
Now let’s look at Trump’s best case scenario for Trump: 26%
- 26.4%: An 8.5 point underdog wins the game outright.
- 26.4%: Your team is down 6 at halftime.
- 26.28%: Your team has the ball and is trailing by 7 with 2 minutes left with 1st and 10 from your opponents 13 yard line.
- 25.37%: Your has the ball and is trailing by 3 with 10 seconds left with 1st and 10 from your opponents 40 yard line.
In Clinton’s best case scenario, she has 94% chance to win the election.
- 93.78%: Your team has the ball and is up by 4 with 2 minutes left with 1st and 10 from your own 20 yard line.
- 94.2%: Your team is up 15 at halftime.
- 94.1%: A 21 point favorite wins the game outright.
In Clinton’s worst case scenario, she has 74% chance to win the election.
- 74.83%: Your team has the ball and is up by 3 with 4 minutes left with 1st and 10 from your own 20 yard line.
- 73.6%: Your team is up 6 at halftime.
- 73.6%: An 8.5 point favorite wins the game outright.
So Clinton’s chances of winning right now are comparable to a team that is somewhere between an 8.5 and 21 point favorite. Or a team that is up somewhere between 6 and 15 points at half time.
Sort of unrelated fun fact that I found when looking up Super Bowl spreads: That last three teams to be favored by more than 10 have all lost outright (2008 New England (-12), 2002 St. Louis (-14), 1998 Green Bay (-11)).
Cheers.
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Based on @predictit state electoral college markets, Clinton has about a 94.1% chance to win in November compared to a 5.6% chance for Trump (with a 0.3% chance of a tie). Details of how I estimated these probabilities are here and the code is on github here.
Overall in the past week, there has been a small shift towards Trump. Clinton hit a high of about 96.8% on August 18 and is down a few percentage points today to about 94.1% This has been pretty steady since around August 9th when clinton jumped to over 90% and she’s been above that ever since. This is good news for Clinton who, as recently as August 1st was in the low 80’s percentage wise to win the electoral college. It will be interesting to see if Trump can make any sort of comeback at all or if Clinton will hold steady in the 93-97% range up until the election.
I’ve also looked at state polling information based on the Huffington Post’s collection of polls. (You can get my scraping and plot building code here.) You can see a few new states have been added since the last time including West Virginia and Massachusetts. Not surprisingly, these are deep red and deep blue, respectively. States with no polling data in the Huffington Post data set will not appear in this graph. What I still find fascinating about this plot is how well third party candidates are doing in a few states. States like Idaho, Utah, Texas, and Delaware seem very receptive to the idea of voting for a third party candidate like Gary Johnson. It will be interesting to see if Johnson can somehow win a state like Idaho or Utah, which both have large Mormon populations and loathe both major candidates.
I’ve also put together a plot of national polling over time. The top plot here follows the race from September 2015 to present whereas the bottom plot focuses on May 1, 2016 – present. I’ve also indicated when some key events took place like debates, Super Tuesday, when each candidate got the clinching number of delegates, and their primaries.
You can see that before about May of this year, polling between Trump and Clinton was fairly sparse as they were still battling in their respective primaries. After that though more Clinton vs Trump polls were taken and the margin of error for these polls drops considerably. Both candidates continue to increase their polling numbers, but the gap between Clinton and Trump has been a pretty consistent 3-5% since right after the Democratic National Convention.
Finally, I made GIFs! Here are the state polls over time.
And here is the electoral college distribution over time.
Cheers!
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Recently, did some cool stuff by scraping the data from predictit.org estimating Clinton vs Trump win probabilities using data from their state markets (GitHub code here).
Last night, I decided to try to get some polling data and Huffington Post makes their polling data available through a very easy to use API in JSON format (GitHub code here).
This first plot uses the national polls of Trump vs Clinton. All polls that were conducted on “likely” or “registered” voters were included. Next I computed the weighted moving average of each of these polls using different moving average windows from 1, 2, 3,…, 21 days. I then plotted all of these curves on top of one another with the width, transparency, and color related to how many days were considered in the moving average. The more days included in the moving average the wider and more opaque the line is and the redder/bluer the line is. I then plotter three different confidence bands using the 7, 14, and 21 day moving averages.
I then pulled out all the state polls that were available and computed the weighted average across all polls with “likely” or “registered” voters (I did not consider the timing of the polls). I then computed a mean and standard error for each of these estimates and randomly sampled from the distribution for Trump and Clinton and plotted these random samples on the plot. The wider the spread of the plotted points for each state the fewer people have been polled in that state. So for instance, Utah has had more polling that Idaho. The color is related to what percentage each candidate is receiving in the poll (redder for Trump and bluer for Clinton. I’ve also added lines with negative slope to show what share of support third party candidates are receiving. If you follow the line y=x the states closer to the origin are more receptive to third party candidates. So for instance, Utah and Idaho are giving a lot of support to third party candidates whereas Georgia and Florida are mainly voting for the two major candidates.
Cheers.
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“There has been a great deal of hype surrounding neural networks, making them seem magical and mysterious. As we make clear in this section, they are just nonlinear statistical models, much like the projection pursuit regression model described above.” – Page 350, “The Elements of Statistical Learning”,Hastie, Tibshirani, Friedman.
Cheers.
