Welcome to the Deep Dive. We are so glad you
can join us today because we are taking a really
fascinating statistical journey. through just
a single document. Yeah, literally one single
Wikipedia list. Right. It is a comprehensive
Wikipedia list of United States Senate elections
in Alabama. And today we are going to look past
the dry tables and uncover the dramatic story
of how voting pools expanded, you know, how political
monopolies shifted. And we'll look at the statistical
anomalies hidden in over a century of state election
data. It is a wild ride when you actually look
at the math. It really is. But before we get
into it, because our source material spans over
a century of political data covering both Democratic
and Republican victories, we want to be absolutely
clear with you. We're not taking any sides here.
Right. Exactly. We're not endorsing any of the
left wing or right wing viewpoints or candidates
mentioned in these historical records. Our goal
is strictly to impartially report on the factual
data provided in the source material. And convey
the statistical shifts as they occurred. Yeah,
we are just looking at the numbers. And to lay
the foundation for those numbers, we should explain
how the Senate works based on the text here.
Go for it. So each state gets two senators. They
serve staggered six -year terms. And those seats
are divided into three classes. Right, which
creates a really unique data set. Exactly. When
Alabama joined the union back in 1819, it was
assigned class two and class three seats. So
the data we are looking at tracks those two specific
overlapping electoral cycles. But there is a
massive systemic change we have to highlight
right up front. The 17th Amendment. Yes. Before
1913, senators were selected by state legislatures.
You don't see direct voter turnout numbers in
the early tables because the voters weren't directly
making the choice. It was the 17th. Amendment
that finally gave the power directly to the voters.
That is the moment the tables switch from appointments
to actual raw voter data. Exactly. Okay, let's
unpack this. Because the numbers are crazy. They
really are. When we look at the earliest data
on the list, the margins are shocking. You know,
you and I are used to modern elections where
someone wins by a couple of percentage points,
right? Yeah, 55 % win today is a huge landslide.
But look at the data from 1918. We have the class
two Democrat, John H. Bankhead. He won his election
with literally 100 % of the vote. One hundred
percent. One hundred percent. The table says
he got exactly fifty four thousand eight hundred
eight hundred eighty votes. Zero opposition on
the board. Just a total shutout. And it wasn't
a one time fluke either. If you scroll down the
class two table to 1942, you see John H. Bankhead
the second. The second. Right. Yeah. And he also
won with one hundred percent. It is just an unbroken
wall of single party dominance in that era. And
you see it in class three too. Jay Lister Hill.
Right. Jay Lister Hill won with one hundred percent
in a 1938 special election. And then he does
it again in the 1956 regular election. He pulled
in 330 ,182 votes and again captured 100 percent
of the electorate. Which is just staggering to
think about. What's fascinating here is the absolute
dominance of the Democratic Party during this
era. Republicans were barely making a dent in
the data. For instance, in 1936, you have Republican
H .E. Burke's stressor running against Bankhead
II. And what did he get? Only 12 .24%. Wow. Yeah,
that was the entire footprint of the opposition.
You know, when we talk about these percentages,
I want to direct your attention to the sheer
volume of the voting pool. The raw numbers are
just as important as the percentages. The denominator.
Right, the denominator. In 1918, a 100 % victory
meant capturing just 54 ,880 votes. Which is
tiny. It's incredibly tiny. Think about that
from a modern perspective. Fifty four thousand
people is essentially the capacity of a mid -sized
college football stadium. Yeah. You just had
to convince one stadium's worth of voters and
you secured a 100 percent monopoly on the United
States Senate seat. The voting base was so extremely
small compared to the state's population today.
It makes every single individual vote carry so
much mathematical weight. It does. But here's
where it gets really interesting. Because even
in this era of small voting pools and 100 % sweeps,
there are these totally unexpected statistical
anomalies. Oh, the third party intruders? Yes.
They just pop up in the tables and completely
disrupt the map. The 1930 class two race is the
perfect example of this. You track James Thomas
Heflin in the tables. The data shows he won the
seat as a Democrat in 1920. He wins it again
as a Democrat in 1924. He is part of that dominant
monopoly. Exactly. But then you look at the 1930
data and Heflin suddenly appears as an inattentive
runner up. And he doesn't just get a handful
of votes. No, he pulls in a massive 40 .07 %
of the vote. That is 100 ,952 votes. He ran against
Democrat John H. Bankhead II, and an independent
just casually walks away with 40 % of the electorate.
A huge fracture in that 100 % wall. Totally.
And you see it again in the 1950 Class III race.
You have independent John G. Cromlin. He captured
23 .46 % of the vote against Jay Lister Hill.
So even when one party is sweeping the board,
There are these massive chunks of the voter base
willing to cast a protest vote. Right. It proves
the electorate was never a pure monolith. But
my absolute favorite anomaly in this data set,
and I know you love this one too, is the Prohibition
Party. It is so bizarre to see them there. Right.
You think of the Prohibition Party as a movement
from the 1920s. But look at the data in the 1970s.
They are still on the board. Very much on the
board. In the 1974 Class 3 election, a candidate
named Alvin Abercrombie took 4 .16 % of the vote
running for the Prohibition Party. In 1974. Yes.
And then four years later, in the 1978 Class
2 race, Jerome B. Couch ran for the Prohibition
Party and secured 6 .01 % against Howell Heflin.
When you look closely at that raw data, you realize
what that percentage actually means. It's a lot
of people. It is. A 6 % poll in that 1978 race
means tens of thousands of individual voters
went to the polls and actively voted for a prohibitionist.
You find entire movements still registering massive
data points decades after you expect them to
vanish entirely from the tables. They just linger
as statistical ghosts. They really do. But as
we keep scrolling down the Wikipedia list into
the 1960s and 1980s, you start to notice a creeping...
change in the core numbers, the era of the 100
% shutout starts to dissolve. The great party
shift. Exactly. The margins just start compressing.
Look at the 1962 class three race. This is a
huge tipping point in the data. It really is.
You have Jay Lister Hill, the same guy who won
with 100 % in 1956. But in 1962, Republican James
D. Martin nearly unseats him. The gap practically
vanishes. Martin captures 49 .14 % of the vote.
That's 195 ,134 votes. Hill barely holds on with
50 .86%. Out of nearly 400 ,000 votes cast, they
are separated by roughly 6 ,800 votes. Going
from 100 % sweet to a 1 .something percent margin
in just a few cycles is incredibly rapid statistical
decay. And the pressure keeps building until
the dam finally breaks in 1980. Right, the 1980
Class III election. Republican Jeremiah Denton
wins the seat. gets 50 .15 % of the vote against
Democrat Jim Folsom Jr. If we connect this to
the bigger picture, Denton's win is the catalyst
for one of the most fascinating electoral sequences
we have in this entire document. The Richard
Shelby phenomenon. The Richard Shelby phenomenon.
If you want to see how fluid party labels can
be while maintaining absolute statistical stability,
you just trace Shelby's data points. Let's do
it. Let's trace it chronologically. Okay, so
start in 1986. Richard Shelby runs as a Democrat
for that class three seat against the Republican
incumbent, Jeremiah Denton. And Shelby wins,
but it is incredibly close. Razor thin. Shelby
beats Denton 50 .28 % to 49 .7%. That is a difference
of less than 7 ,000 votes. Very fragile margin.
But then look at his next row in the table. In
1992, Shelby runs again as a Democrat and his
margin explodes. He wins with 64 .82%. So the
data is telling us, OK, the Democrats have solidly
reclaimed this class three seat. Right. The math
looks totally settled. But then you drop down
to the very next election cycle for that seat
in 1998. The data shows a wild twist. A complete
anomaly. Richard Shelby is listed as winning
the exact same seat, retaining almost the exact
same percentage of the voter pool, but he is
listed as a Republican. He wins with 63 .24 %
of the vote. As a Republican, the primary variable,
the party label, completely flips, but his share
of the electorate barely moves. And once that
label flips, the table shows him... dominating
that seat as a Republican for decades. He just
locks it down. He wins in 2004, 2010 and 2016,
consistently pulling in those mid to high 60
percent margins. The label changed, but the math
stayed relentlessly stable. That really ushers
the data set into its modern era. We are looking
at the 1990s through the 2020s now, and it becomes
a period of. Deep Republican dominance. Definitely.
Look at Jeff Sessions in the class two seat.
He establishes absolute dominance. He wins in
96, 2002 and 2008. By 2014, his hold on the numbers
is so strong that he runs unopposed. Which takes
us right back to the beginning of the list. Exactly.
He wins that 2014 race with 97 .25 percent against
just scattered write ins. It is the closest thing
to those 1920s bank head margins we've seen in
the modern era. The table projects this totally
unshakable Republican stability. But then. You
get these sudden jolts of volatility. The special
elections. Yes. Look at the 2017 special election
for that exact same class two seat. Out of nowhere,
we see a razor thin Democratic victory. It completely
disrupts the trend. Democrat Doug Jones edges
out Republican Roy Moore. The distribution is
incredibly tight. Jones gets 49 .97 % with 673
,896 votes. Moore gets 48 .34 % with 651 ,972
votes. A difference of barely 20 ,000 votes out
of over 1 .3 million cast. But the data also
shows how incredibly brief that disruption was.
By the 2020 regular election, the math aggressively
snaps back to the established trend line. Republican
Tommy Tuberville reclaims the seat. With a massive...
60 .9 % majority. He pulls in 1 ,392 ,076 votes
over Jones's 39 .74%. So what does this all mean?
When you zoom out and look at the entire arc
of this table, the most shocking thing isn't
just the party shifts. It is the sheer scale
of the math. The expansion of the pool. Yes.
Think back to that 1918 row. 100 % victory required
exactly 54 ,880 votes. That stadium -sized pool.
Right. Now contrast that with the 2020 Tuberville
versus Jones race. That single election featured
over 2 .3 million combined votes. The effort
required to capture a majority has just scaled
exponentially. And the 2022 data confirms that
massive pool is the new normal. Republican Katie
Britt won the Class 3 seat with 66 .62%. That
percentage translated to 942 ,154 raw votes for
a single candidate. Confirming that massive modern
voter pool and current Republican dominance,
we really just traced a 100 -year arc straight
through the numbers. From 54 ,000 votes to almost
a million for a single candidate. We started
in a time of single -party Democratic sweeps.
We watched the emergence of independents and
prohibitionists fracturing the data. We saw razor
-thin transitions of power. And we finally arrived
at these massive multi -million vote modern Republican
majorities. It is an incredible mathematical
journey. This raises an important question for
you to think about. How quickly can data that
feels totally permanent just flip over a few
cycles? It really makes you wonder. We've seen
the 17th Amendment change senators from being
appointed by a legislature to being elected directly
by the people. We've watched total votes surge
from 50 ,000 to over 2 .3 million. So with technology
and demographics changing faster than ever, what
were the voting mechanism or even the definition
of a majority look like in the statistical tables
of 2126? It is definitely something to ponder.
Thank you so much for joining us as we unpack
the numbers today. We will see you on the next
Deep Dive.