Month: June 2020

What’s madder than a 68-team single-elimination college basketball tournament that takes a month?

A 351-team single-elimination tournament that takes five months.

That’s the plan for the NCAA Cup, an imaginary college basketball tournament going on right now.

The Rules

It’s inspired by the Cup tournaments in international soccer, like the FA Cup in England and the Copa del Rey in Spain. Those tournaments, and in the NCAA Cup of college basketball, follow these rules, each more insane than the last:

1. The tournament proceeds in rounds
2. For each game in a round, the winner advances and the loser goes home
3. Every single team qualifies for the tournament
4. All matchups are determined randomly

That’s right, each round’s matchups are random. That means that Gonzaga (#1 in the NCAA’s NET rankings) is just as likely to play #2 Kansas as they are to play the lowest-seeded team, #351 Chicago State.

The home team is also selected randomly, which means that Duke could start off playing on the road somewhere out of the way, like at Idaho State or Hawaii.

Winners of the first round games move on to the second round, and the matchups get picked again. In other words:

Get ready for some madness!

The Schedule

The 2020 NCAA cup began on April 7th, the day after Duke lifted the imaginary 2020 NCAA tournament trophy. The championship game is August 29th, the same day that the 2020 college football season starts.

Because NCAA Division 1 has an odd number of teams (351), two teams were randomly selected for a “round 0.5” play-in game. Half the teams are eliminated in each round; when this results in an odd number of teams, two are randomly selected for another play-in game.

Here is the schedule of when each round starts and stops:

Round	Start Date	End Date
0.5	Tuesday, April 7, 2020
1	Friday, April 10, 2020	Sunday, May 31, 2020
1.5	Wednesday, June 3, 2020
2	Sunday, June 7, 2020	Friday, July 3, 2020
3	Saturday, July 4, 2020	Tuesday, July 28, 2020
4	Friday, July 31, 2020	Tuesday, August 11, 2020
5	Thursday, August 13, 2020	Tuesday, August 18, 2020
5.5	Thursday, August 20, 2020
6	Friday, August 21, 2020	Sunday, August 23, 2020
6.5	Tuesday, August 25, 2020
7	Wednesday, August 26, 2020	Thursday, August 27, 2020
8	Saturday, August 29, 2020	Saturday, August 29, 2020

Every game is simulated on the whatifsports.com college basketball simulator, and results are announced in real time on the twitter feed @fixthemadness.

Round 1 is now complete, and we are in the middle of Round 2. Here’s what has happened so far, round by round. This page gives some highlight games, and I am now in the process of posting the complete results at my NCAA Cup page.

Results

Round 0.5

The randomly selected matchup for the play-in game was Virginia Commonwealth at Navy. The final score (click on the score for the box score from whatifsports.com):

Date and time	Result
Wed Apr 8 8 PM ET	Navy 68 Virginia Commonwealth 59

…and so the Virginia Commonwealth Rams became the first team eliminated from the 2020 NCAA cup. That left an even number of teams for random selection in the first round – 350 remaining teams meant 175 games.

The games proceeded, three or four a day, from April 10th to May 31st. And here are the results!

Round 1

Round 1 is now complete! It began in America’s premier basketball city, New York City, with Columbia beating High Point 68-51, and it ended in Pullman, Washington, with Lamar upsetting Washington State 90-81.

I am in the process of posting the results of all 175 games to a separate NCAA Cup page, but here are some highlights – games by big-ticket teams, shocking upsets, and exciting games. The home team is listed first and the winning team is in bold. Click on the score to see the box score and game recap from whatifsports.com.

Date and time	Score
Fri April 10 8 PM ET	Oklahoma State 83 Auburn 86
Sat April 11 8 PM ET	Oklahoma 66 Nebraska 83
Sun Apr 12 2 PM ET	Vermont 86 Northwestern 83
Sun Apr 12 8 PM ET	Incarnate Word 57 East Tennessee State 79
Thurs Apr 16 8 PM ET	Santa Clara 84 Saint Louis 85 (OT)
Fri Apr 17 8 PM ET	Penn State 63 LSU 73
Sunday Apr 19 2 PM ET	Pittsburgh 81 Idaho 88 (2OT)
Sun Apr 19 8 PM ET	Virginia 70 Stephen F. Austin 65
Mon Apr 20 Noon ET	Marshall 109 Green Bay 108 (3OT)
Fri Apr 24 8 PM ET	Coastal Carolina 74 Florida 87
Sat Apr 25 8 PM ET	(16) Ohio State 93 Georgia Tech 86
Sun Apr 26 20:00	Kennesaw State 48 (6) Duke 90
Thurs Apr 30 8 PM ET	Clemson 77 Indiana 68
Sat May 2 4 PM ET	(21) Kentucky 80 Loyola (MD) 50
Sat May 2 8 PM ET	Purdue 80 Xavier 82
Fri May 8 8 PM ET	(18) Maryland 85 Bradley 59
Sat May 9 10 PM ET	UNLV 82 (1) Gonzaga 71
Sun May 10 4 PM ET	Drexel 79 Arkansas 73
Fri May 15 8 PM ET	St. Mary’s 80 Tennessee 70
Sat May 16 4 PM ET	Southern U 62 (2) Kansas 81
Thurs May 21 4 PM ET	South Carolina State 73 (7) Michigan State 89
Thurs May 21 8 PM ET	Texas State 69 Texas A&M 67
Fri May 22 6 PM ET	(3) Dayton 72 Northwestern State 62
Fri May 22 8 PM ET	(10) Florida State 81 Buffalo 63
Fri May 29 4 PM ET	Weber State 82 (9) BYU 93
Sat May 30 8 PM ET	(11) Creighton 73 California 51

The biggest surprise: overall top seed Gonzaga is already gone in the first round, knocked out by UNLV!

Round 1.5 (play-in game)

The 175 winners of the first round games moved on. But that once again left an odd number of teams, so two were randomly selected for a play-in game: Radford at Toledo. And the result:

Date and time	Result
Wed June 3 8 PM ET	Toledo 70 Radford 72

Round 2

Round 2 began on Sunday, June 7th – and it began with an incredible upset, with top team Iowa losing on the road to #315 Central Arkansas. Here are some of the highlight results from the 18 second-round games so far:

Date and time	Results
Sun June 7 Noon ET	Central Arkansas 94 Iowa 86 (OT)
Sun June 7 8 PM ET	Louisville 72 Florida State 68
Tues June 9 4 PM ET	Drexel 75 Liberty 67
Thurs June 11 8 PM ET	South Carolina 85 Rhode Island 95

Round 2 continues through Friday, June 3rd. These games are happening today:

Fri June 12 2 PM ET	Sam Houston State 86 Georgia Southern 76
Fri June 12 4 PM ET	American (17-14, NET #197) at Vanderbilt (12-21, NET #142)
Fri June 12 8 PM ET	USC (23-9, NET #45) at Utah (17-15, NET #85)

Follow all the results in real time at the Twitter feed @fixthemadness, and see all the results in one place at my NCAA Cup page.

Enjoy the madness!

Graphs day 86, pandemic day 91, day 162 since the first cases were diagnosed.

Total cases of COVID-19 diagnosed worldwide: 7,401,717

Total deaths: 417,807

I will continue plotting the number of newly reported cases, resulting in a curve that goes up and down as the pandemic waxes and wanes. Here’s what that type of graph looks like for the entire world over the entire history of the pandemic:

Unfortunately the trend seems to be that the pandemic is continuing to infect slightly more people every day.

Cases per million people by country

Here is a map of today’s cumulative cases per million people (since the beginning of the epidemic):

Remember that the map shows you the total number of COVID-19 cases reported up to and including today. I might change the map so that it shows today’s cases, and today’s cases only. Is that something you would like to see?

As I mentioned above, plotting the history of cases reported each day produces a graph with a line that goes up and down as each country’s local epidemic waxes and wanes. These graphs allow us to divide countries into four categories:

• Countries that contained the epidemic quickly
• Countries that experienced a surge in cases but now have the epidemic under control
• Countries that are still reporting new cases at an appreciable rate, but at least the number of new cases is steady or decreasing with time
• Countries where the epidemic is still getting worse

No countries have changed categories today, although some seem to be on the verge of changing. I also added Australia and New Zealand to today’s graphs. Which category will they appear in? Keep reading to find out!

Countries that quickly contained their COVID-19 epidemics

These countries intervened so early in the course of the epidemic that they never had a high COVID-19 case rate to begin with. I’m using the same vertical axis scale for all the graphs (zero to 375 cases per million people), and when I use that scale for countries in this category it becomes clear just how much lower the case rates are there.

This is where Australia (gray) and New Zealand (green) ended up. Their case rates peaked just a little higher than South Korea’s, and about a month later. But the case rates in all these countries are down near zero now.

Countries that have COVID-19 under control now

These countries experienced a higher peak in cases, but thanks to the public health interventions they put in place, the peak has passed and they are now reporting very low numbers again.

This category includes Italy and Spain, which just a few week ago were considered the hardest-hit countries in the world. The one country that worries me is Belgium, where cases have steadily increased from 10.2 per million to 11.5 per million over the last four days. That still might be statistical luck – or I might need to move Belgium to the “getting worse” category.

Countries where cases are steady or decreasing

These are countries that are still reporting an appreciable number of cases, from 20 per million people in the U.K. to 570 per million in Qatar. But all the countries in this category are experiencing fewer daily cases than they did one or two months ago.

I would love to say that these are countries where the number of cases per day are decreasing – but as the graph shows, that is now true only in the U.K. and Qatar. Cases in the United States, Russia, and Belarus are all holding steady, and in fact seem like they might be starting to go back up. I would hate to move any of these countries into the “getting worse” category.

Countries where the epidemic is getting worse

These are countries where the number of cases reported is still generally increasing.

Two days ago, it looked like cases in Peru were on their way back up – but yesterday’s cases were down and today’s are steady, and all of the past few days have been below the peak of a couple weeks ago. I think we’re on the verge of moving Peru back in to the “steady or decreasing category,” but I’ll wait a few more days.

Possibly even better news is that it looks like maaaaaybe Chile and Brazil are on the verge of peaking and starting to decrease. I certainly hope so, and I’ll be keeping an eye on those countries.

Deaths per million people by country

When it comes to death, the dead stay dead, so it makes sense to consider cumulative deaths, resulting in the usual map style and incurves that steadily increase with time. Here’s the map of deaths per million people, focused on Europe and the Americas:

Those curves, for the 10 countries we’ve been following most often:

Want to try out some of these graphs for yourself? You can get the data that I used to make these graphs from the European Centers for Disease Control’s Coronavirus Source Data; choose “all four metrics.” You’re still welcome to use my Excel template – I added a section for making the deaths graph to what is now verison 4.1, so that is the only one you need.

Update tomorrow, and every day after that until this pandemic comes to an end.

One of the first effects of the COVID-19 pandemic to cancel the most fun event in American sports: the NCAA men’s basketball tournament. It’s nicknamed “March Madness” because of, well, the significant about of sheer craziness involved.

From first-round upsets to the championship game, it’s four weeks of constant excitement. If you don’t believe me, check out this highlight reel of the 2019 NCAA tournament (long but worth it!).

And then in 2020, it was gone.

Just four days before the selection committee was set to announce the 68 teams who qualified, right in the middle of a conference tournament game, the National Collegiate Athletic Association (NCAA) cancelled the whole thing. And while professional sports leagues are planning to finish out their seasons (AFL season restarts tomorrow!), college basketball’s seniors have already graduated and moved on. So this year’s tournament is definitely gone for good.

While certainly not as big a deal as the 4,619 people who had died as of then (and it’s nearly 100 times that now!), the tournament’s cancellation still came as a disappointment to millions of college basketball fans. Including me.

My March Madness

I decided that, if we can’t have March Madness in reality, we can at least have it in our imaginations. And so I picked a field of 68 team, taking into account all the factors that the real selection committee does: record, ranking, strength of schedule, and conference tournament results.

And here is the bracket:

I then simulated the entire tournament using whatifsports.com’s college basketball simulator. I announced the results, in real time, at my appropriately-named Twitter account, @fixthemadness.

Results

As each round of the tournament completed, I reviewed the results as a post on this blog. Read the posts linked in the list below to see how it all played out, round-by-round:

• Announcing the teams and first-round matchups
• Announcing the first round schedule
• Day 1 matchups
• Day 1 results and Day 2 matchups
• Day 2 results and second-round matchups
• Second round results
• Sweet 16 and Elite 8 results, and final four matchups

…except that as the COVID-19 crisis worsened, I turned my attention to that and never posted the Final Four results. Here they are. The Final Four consisted of the winners of each of the four regions (East, South, Midwest, and West). Both Final Four games were played on Saturday, April 4th – the first at 6:07 PM ET and the second at 8:07 PM ET.

The results were (click on the score to see the box score and play-by-play from whatifsports.com):

East Tennessee State 90 Creighton 78

Duke 82 Oregon 78

That set up an exciting matchup between the historical powerhouse team, the Duke Blue Devils (#1 seed in the South), and the surprising Pirates of East Tennessee State.

The game was close throughout the first half and early in the second, but then Duke pulled away. The final score (with link to the box score and play-by-play):

Duke 96 East Tennessee State 76

Congratulations to the imaginary Duke Blue Devils on winning the imaginary 2020 NCAA men’s basketball championship!

The full bracket

Here is the full bracket with all results, leading up to imaginary Duke’s imaginarily historic imaginary win:

What’s next?

I had a blast doing this. It went on for a month, and then it was over, and @fixthemadness wasn’t ready for it to be over. What could I possibly do for an encore?

Find out Friday!

Also, coming tonight: today’s daily update of COVID-19 cases and deaths.

Graphs day 84, pandemic day 89, day 160 since the first cases were diagnosed.

Today is the day that Earth passed seven million cases of COVID-19, eight days before my mid-May prediction said we would. The good news is that the number of deaths continues to run behind those predictions.

Total cases of COVID-19 diagnosed worldwide: 7,069,278

Total deaths: 405,587

I will continue to show cases using the new methods I explained yesterday: plotting the number of newly reported cases, resulting in a curve that goes up and down as the pandemic waxes and wanes. Here’s what that type of graph looks like for the entire world over the entire history of the pandemic:

As you can see from the graph, we are very much in the middle of this pandemic.

Cases per million people by country

Yesterday I divided countries into four categories:

• Countries that quickly contained their COVID-19 epidemics, and never had a large number of cases per million people
• Countries that had many cases, but have since gotten their epidemics under control and have few new cases
• Countries where a significant number of cases are still being diagnosed, but fewer and fewer each day – these countries are headed in the right direction
• Countries where the epidemic is still getting worse

I’ll focus primarily on the last two categories – improving and getting worse. And unfortunately, we’ve already had one country move into the “getting worse” column.

First, the countries where the epidemic seems to be getting better, or at least staying the same:

Notice that Peru is gone from the graph – the situation in Peru is getting worse again. Belarus, the United States, and Russia all make me nervous, because it looks like the curves could start going up again at any moment.

And now the countries where the epidemic continues to get worse, now sadly including Peru:

Cases per million people reported yesterday in Brazil and Sweden were almost exactly the same, but Sweden’s rate is a little higher. Sweden is starting to look really bad.

and as a graph comparing case rates on an even scale from each country’s “day zero,” the date on which cases reached 1 in 1,000,000:

Deaths per million people by country

When it comes to death, the dead stay dead, so it makes sense to consider cumulative deaths, resulting in curves that steadily increase with time. Those curves, for the Big Ten countries:

Note the large spike in deaths per million in Chile, presumably due to reporting of deaths catching up with the actual data.

Want to try out some other ways for yourself? You can get the data that I used to make these graphs from the European Centers for Disease Control’s Coronavirus Source Data; choose “all four metrics.” You’re still welcome to use my Excel template – I added a section for making the deaths graph to what is now verison 4.1, so that is the only one you need.

Update tomorrow, and every day after that until this pandemic comes to an end.

Graphs day 83, pandemic day 89, day 160 since the first cases were diagnosed.

I’ll continue to update the COVID-19 case and death numbers as long as the global pandemic continues, but as life begins to settle into the new normal in the U.S., I am settling into the new normal of posting a longer, more substantive article every Monday, Wednesday, and Friday.

I would love nothing more than to go back to posting about Australian rules football, but reality seems to be conspiring to keep COVID-19 and racial justice in the news. So today, we examine another way of visualizing COVID-19 cases, one that gives a clearer picture of how the disease is moving around the world.

COVID-19 worldwide statistics

Before I launch into the new visualizations, let’s look at the statistics we have been charting since the beginning of the pandemic, and the predictions we have been tracking since May 17th.

Total cases of COVID-19 diagnosed worldwide: 6,958,337

Total deaths: 401,487

Today is the day we hit 400,000 deaths worldwide, four days after my prediction. The next major milestone is 7,000,000 cases worldwide. I had predicted we would reach that milestone on June 17th, but it looks near certain that we will actually reach seven million tomorrow, a full eight days early.

Deaths per million people by country

The graphs that I have been showing from the beginning have shown the total number of cases and deaths, either worldwide or in specific countries. As I have mentioned before, this is definitely the right way to look at deaths, because once someone dies of COVID-19, they’re not coming back to life. Each new death just adds to the COVID-19 death toll.

So I’ll break from my usual order and show deaths before I show cases. Deaths per million people for selected countries shown on a map:

and as a graph showing increasing death from mid-February to today:

A new look at case rates

In many ways, the steadily-increasing graphs I’ve been making are the right graphs for case rates too. It is absolutely a meaningful question to ask “how many people have been diagnosed with COVID-19 since the beginning of the epidemic, and how does that vary between countries?” Answers can provide extremely useful data for planning nationwide responses.

But in another way, these cumulative case graphs offer a misleading picture of the current state of the pandemic. The dead stay dead, but people who are sick with COVID-19 can get better. Although it’s still not clear whether having COVID-19 confers immunity to future infection, it is both meaningful and encouraging to plot how many people are currently sick. While it’s hard to know who is sick at any moment, it’s quite easy to plot the number (or rate) of new cases diagnosed.

To recap: for each day on my graphs, I have been plotting the total number of cases (overall or per million people) that have been reported as of that day. For today’s graphs, I will instead plot the number of NEW cases reported each day.

IMPORTANT NOTE: These graphs CANNOT be directly compared with the cumulative case graphs that I have been making since March 18th. Please don’t even try to compare them. They show the same information in a completely different way.

One possible downside of this approach is that the number of new cases reported on a particular day is subject to large day-to-day variations for a variety of reasons including statistical dumb luck. These daily variations are quite interesting and will be the subject of a future post. But they make it difficult to see overall trends, so I am “smoothing” the curves by replacing each day’s case data with the average value itself, the 5 days before, and the 5 days after. This results in a curve that has approximately the same value as the real curve everywhere, but with the daily variations removed so the curve looks much smoother.

It’s easier to explain with an example: the graph below shows the number of cases of COVID-19 reported worldwide, every day since outbreak began in Wuhan, China. The blue line shows the actual number of cases reported each day; the red line shows the smoothed curve.

In case you think I’m doing something weird to try to mislead you: no I’m not. This is a very common method in all areas of science. Also, look at the curves, they clearly look about the same.

For the rest of the graphs in this post, I will show ONLY the smoothed data. But it’s easy to create graphs using the observed data instead. If you’d like to try, download my Excel template linked below (version 4) and send me an email (jordan.raddick@gmail.com). I’d be glad to show you how.

So how do our usual “Big 10” countries look with this new visualization approach? Confusing. Don’t try to make sense of the 10 overlapping lines in the graph below, just enjoy how confusing it is.

Clearly we need a better approach – and fortunately, our better approach will also allow us to consider some of the countries we have looked at previously.

The only thing I’d like you to notice about the overlapping curves on the graph above is their general shape: the curves rise, reach a peak, and fall. The peak can be narrow or wide, high or low, and it can occur at different times. For some countries, the peak has yet to arrive. (Note: You might be tempted to call these “bell curves,” because they are vaguely bell-shaped – but the term “bell curve” refers to a specific shape of curve, which these are not.)

The shapes of these curves allow us to divide countries into four general categories based on how the epidemic has evolved there. Below, I show the curves for the countries in each category, and briefly explain what they mean. Over time, we’ll follow these categories as different countries move in and out of them. All graphs have the same scale except where noted.

Countries where the epidemic was quickly and easily contained

I’m deliberately showing these countries on the same scale as the countries in other categories (the vertical axis going from 0 to 275 cases per million people); it really drives home how well these countries kept cases to a minimum. All three are found in Asia: China, South Korea, and Japan. For this graph only, the horizontal axis starts in late January, otherwise China we would miss nearly all the cases in China.

Whatever these countries did to contain the epidemic, they did it right. COVID-19 could return anywhere, but it seems unlikely in these countries.

Countries where the epidemic is currently under control

In these countries, the curve has risen, peaked, and fallen to near zero – meaning that very few new cases are currently being reported in these countries. They are all in Europe. In the order in which the peak arrived, they are: Italy, Spain, Switzerland, Slovenia, France, and Belgium.

These countries struggled to contain the epidemic, but finally won – at least for the moment. That’s why I say “currently under control.” Antlers crossed that COVID-19 remains under control in all these countries.

Countries where the epidemic is mostly headed in the right direction

The next category contains countries where the case rate seems to have peaked, and the curve appears to be on a downslope – meaning fewer and fewer cases are being reported each day. These countries are: the United States, the United Kingdom, Russia, Belarus, Peru, and Qatar. This is the only graph with an inset, otherwise Qatar would have been literally off the charts. The vertical axis of the inset graph goes from zero to 700 cases per million.

These countries have taken concrete steps to fight the pandemic, and those steps are working. If they continue on their current course, they will join the list of countries that have the disease under control. The only thing that worries me is that the decrease has stopped in the U.S. It’s not going up, but it’s not going down either. Hopefully it will work its way back down soon.

Countries where the epidemic is getting worse

Last and unfortunately most are those countries where the epidemic continues to get worse: Chile, Saudi Arabia, Brazil, Sweden, and India:

I’ll continue making these kinds of graphs in future updates.

Want to try out some other ways for yourself? You can get the data that I used to make these graphs from the European Centers for Disease Control’s Coronavirus Source Data; choose “all four metrics.” The Excel template that I used to make the plot of deaths is version 3.3. The plots of new cases by day come from version 4. You want the sheet that says “BIG TEN,” starting at column BI. I’d love to see what you can build with it, and I’m happy to help you figure it out! You can reach me by email at jordan.raddick@gmail.com, or leave a comment here.

Update tomorrow, and every day after that until this pandemic comes to an end. And coming Wednesday: finally a break from COVID-19 and racial justice for some imaginary sports.