Superbet Chess Classic

 This 10-player round robin is part of the Grand Chess Tour - over the board chess is back!

EDIT: Original post mistakenly had Rapport in the tournament and left out Deac. That has been fixed.

Candidates 2021

 The 2020 Candidates Tournament was postponed; the second half begins this month. Nepo and MVL were leading with 4.5/7, but in the forecast, Nepo is the favorite. That is because MVL shed 26 rating points in the 2021 Tata Steel Masters. Caruana trails at 3.5/7, but the model still thinks he has a chance due to his high rating. 

K+Q vs. K+R: One more key position to know

 A few months ago, I posted an article about queen vs. rook. I have one position to add to it. 

[Event "?"] [Site "?"] [Date "????.??.??"] [Round "?"] [White "New game"] [Black "?"] [Result "*"] [SetUp "1"] [FEN "8/8/8/8/1K6/8/rk6/3Q4 w - - 0 1"] [PlyCount "5"] {If it is Black to move, then it's zugzwang. If it is White's turn, then the best move is} 1. Qd5 $1 ({Not} 1. Qb3+ Ka1 2. Kc3 $4 Rc2+ $1 3. Kd3 Rd2+ $1) ( 1. Qd2+ Kb1 2. Qe1+ {hopes for} Kb2 3. Qd1 { zugzwang, but Black can avoid this with 2...Kc2}) 1... Kb1 2. Kb3 Rb2+ 3. Ka3 { and the rest is straightforward} *

Converting Q vs. R was critical to becoming the #1 endgame benchmark player on ChessTempo

Tata Steel Forecast

 We are back to forecasting chess tournaments!! The model was designed for classical games, so I could not use it for all the online rapid tournaments that we saw over the last year. World Champion Magnus Carlsen is the top seed in the 14-player round robin.

Trends in Social Distancing - Part 2

A few weeks ago, I wrote Part 1 of this series. It looked at anonymous smartphone data from several different sources. In all cases, I found that social distancing started after WHO declared a pandemic, even though the shutdowns did not begin until a week or two later. In this update, I now have data on Thanksgiving. Many feared that there would be a surge in cases after people celebrated the holiday together. But it looks like there was little change in social distancing. 

One of my sources, SafeGraph, changed its methodology, so I am not using it anymore. I still have data from the adjusted device exposure index (DEXA). Every day, it tracks how many smartphones were in each store (more information in Part 1). In the graph, time (t) is zero on January 20, when the first case in the US was confirmed. So Thanksgiving is around t = 300. There isn't a big spike during the holiday. But perhaps this is not the best data source to capture that. Gatherings happened in people's homes, not in stores. However, it should pick up a Black Friday surge. It is hard to spot it on the graph, so this means that people were shopping online instead.

DEXA

If social distancing fell during Thanksgiving, it should show up in the trips data (more information in Part 1). This is collected by the Department of Transportation. If you look closely, there does seem to be an increase around t = 300. However, it is pretty small.

Number of Trips

The Department of Transportation also estimates how many people left their homes. It was actually trending downwards before Thanksgiving. That isn't surprising; cases were rising, so people became more cautious. The trend briefly reversed for the holiday, but now it is heading back down. Once again, Thanksgiving only has a small effect.

Percent of people who left home

I don't have data on Christmas yet - when the Department of Transportation posts an update, there is a lag of about one or two weeks. Stay safe 

Comments

 I just saw that there were a bunch of comments on old articles that I never noticed. Blogspot was putting comments on hold until they could be moderated, but somehow I didn't see any notification to check them. I changed the settings so it should work better now.

Trends in Social Distancing

I came across some interesting data while researching the coronavirus. Social contact is a key factor in explaining the disease's spread. About a week or two before the shutdowns, social contact fell dramatically. After a while, it started to rise, but it is still well below normal. Ideally, we would track everyone and measure how many times they got within 6 feet of someone else, weighted by the amount of time that they were in close contact. That data does not exist. There is measurement error in the available data. However, all my sources tell the same story. That's why I think this pattern is real.

My first source is the Device Exposure Index (DEX) (link to the methodology). It uses smartphone location data. When you go to a store, how many other devices were in that store? One issue is that if someone stays at home, their smartphone drops out of the sample. The Adjusted DEX fixes that problem. I averaged the Adjusted DEX across all US counties, weighting by population. 

The big drop that you see is March 11. That is when the WHO declared pandemic. Shutdowns did not begin until a week or two later, but people had already started social distancing. The average value for the Adjusted DEX plummets from around 200 to roughly 50. It's about 100 now, so life is still very far from normal. 

My next data source is the Department of Transportation (link). It uses smartphone data to count how many times people leave their homes and how far that they travel. I calculated trips per person for each county. Then I averaged across all counties, weighting by population. I was surprised to see that the average person took almost 4 trips per day before the pandemic. That seems suspiciously high. But then I looked into the methodology. Each time you go somewhere, that is counted as a separate trip. So if you (1) grab coffee from Starbucks in the morning and then (2) go to work and (3) take a walk after lunch and (4) buy groceries on the way home, that is counted as 4 different trips. 

A similar pattern emerges. A big drop that preceded the shutdowns, then a gradual recovery, but it's still far below January and February. June 1 corresponds to Ndate=22067, and we see the protests showing up in the graph.

My last source is data from SafeGraph (downloaded from Carnegie Mellon: link). If a smartphone leaves the house for 3-6 hours, they assume you are working part-time. If it's away for 6+ hours, then it's full-time.

Part-time:

Full-time:

The numbers are suspiciously low. Back in February, only 9% of people worked full-time and 13% worked part-time? That can't be right. I almost threw out this dataset due to the measurement error. However, it might still have some uses. It does display the same trend: social distancing began a week or two before the shutdowns. Contact starts rising again, but it's far from normal. 

Social distancing began voluntarily, but that doesn't prove that government policies were unnecessary. Right now, I'm studying optimal policy. No results yet - just sharing some data that I found along the way. Take care