Welcome to the deep dive. We are really thrilled
you could join us today. Yeah, absolutely. Thrilled
to have you listening in. So I want you to picture
a scenario. You're doing some research or maybe
you're just, you know, falling down one of those
late night Internet rabbit holes and you land
on a Wikipedia page. We have all been there.
Right. And at first glance, it is. Well, it's
the most dry, standard looking page imaginable.
It's simply titled List of United States Senate
Elections in Wyoming. Which, I mean, doesn't
exactly sound like a thriller. No, not at all.
You see standard navigation menus, a chronological
list of dates, a grid of raw numbers. Your first
instinct might be to just close the tab and move
on to something flashier. And honestly, nobody
would blame you. It looks like a sterile spreadsheet.
Exactly. But hold on. Today, we're going to show
you how that seemingly sterile spreadsheet is
actually a roadmap of human behavior. It's entirely
too easy to look at a data table and see nothing
but statistics. But numbers on a page, especially,
you know, voting records, they're the footprints
of a society making decisions over time. They
really are. When you look closely at the architecture
of a page like this, it reveals patterns that
are entirely invisible if you're just skimming
for a single fact. And that is exactly the mission
for this deep dive. We're going to look beneath
the surface of this specific data set. We want
to uncover the hidden stories of political momentum.
Right. The things hiding behind the percentages.
Yes. We're going to look at the sheer, undeniable
power of incumbency. And we're going to see how
the very rules of American democracy shifted
in a massive way over a century ago. All of which
is hiding in plain sight on this one single page.
OK, let's unpack this. Where exactly are we starting
with this document? Well, our core timeline centers
on the primary data table provided by the source.
That table tracks the United States Senate election
results in Wyoming from 1988 up through 2020.
So that's really the meat of the data. Exactly.
It details the candidates, their party affiliations,
the total raw votes they received, and of course,
the percentage breakdown of the race. But there's
something else before we even get to that table,
right? Yeah, before digging into that late 20th
century data, the source presents a set of navigational
clues in the sidebar menus. I love those sidebars.
They're so easy to miss. Right. But these menus
situate our 30 -year snapshot within a much broader
institutional framework. one that actually dates
all the way back to the 1700s. And that historical
framework frames the modern table perfectly.
It really does. If you look at the navigation
sidebar under the heading United States Senate
Elections, the page neatly divides the entire
history of these elections into two distinct
eras. Which is a very subtle formatting choice
by the editors. It's just a couple of dates and
parentheticals, but it represents a fundamental
constitutional pivot. The division in the sidebar
is stark. The first era is listed as spanning
from 1788 to 1913. And right beneath those dates,
there's this brief parenthetical note. It reads,
elected by state legislatures. Right. Then there's
a hard break in the timeline. The second era
begins in 1914 and runs to the present day. And
the parenthetical note for that era shifts to
a new phrase. It says popular election. As a
modern voter, it's almost jarring to read that.
It really is. You just assume that going to the
ballot box and picking your senator is this baked
in feature of the system from day one. Right.
Like it's just always been that way. But this
sidebar is explicitly documenting that for a
massive chunk of American history, that direct
line between the citizen and the Senate simply
did not exist. If we connect this to the bigger
picture, it completely reorients how we interpret
the data that follows. We take casting a ballot
for a senator as an absolute given today. Oh,
totally. But for the first 125 years of U .S.
history, from 1788 all the way to 1913, everyday
citizens in Wyoming and everywhere else in the
country, for that matter, did not directly vote
for their senators. The state legislatures held
that power. Exactly. The source highlights this
shift starting in 1914 as the foundational rule
change of modern Senate elections. It marks the
transition of the Senate from a body chosen by
local lawmakers to a body chosen directly by
the general public. And that transition to the
popular vote is what makes the 1988 to 2020 data
table so compelling to analyze. Because now we
have a direct measurement of the public's will.
Yes. Once the power is handed over to the voters,
we get this clear mathematical record of how
those voters behave, how their preferences solidify,
and how a state's political identity evolves
over decades. Which takes us right to the top
row of our main data table. Right. The year is
1988. We are looking at a race between Democrat
John Vinnich and the Republican incumbent Malcolm
Wallop. That 1988 race actually serves as the
perfect baseline for us. Why is that? Largely
because it's the statistical outlier of the entire
modern data set provided. Let's look at that
1988 row. The raw vote totals are almost identical.
John Vinnich, the Democrat, pulled in 89 ,821
votes. Which gave him 49 .6 % of the vote. Right.
And Malcolm Wallop, the Republican, brought in
91 ,143 votes. That gave him 50 .4%. That is
a difference of barely 1 ,300. votes. In a statewide
federal election, that is a razor -thin margin.
It's a 1 ,322 vote difference, to be exact. It
is effectively a fraction of a percent coin toss.
A complete toss -up. It really represents a moment
of peak competitive tension within the state's
electorate. We're just reporting what the numbers
say here impartially, but that is a highly competitive
race by any metric. You could probably fit the
deciding margin of voters into a large high school
gymnasium. Easily. But here's where it gets really
interesting. Look at the immediate trajectory
of the data following that race. You might expect
that after a nail -biter like that in 1988, the
subsequent election cycles would feature similar
down -to -the -wire battles. Right, like the
state is just evenly divided and it's going to
be a battleground every time. But the data shows
the exact opposite trajectory. When we trace
the numbers from 1990 onward, that competitive
tension completely evaporates. It vanishes. Let's
look at just two years later in 1990. The Democratic
candidate, Kathy Helling, receives roughly 36
% of the vote. And the Republican incumbent,
Al Simpson, wins with 64%. The gap between the
candidates widens from roughly 1 ,300 votes to
a margin of tens of thousands. Instead of a fractional
difference, we suddenly see a candidate pulling
ahead by nearly 30 points. And the trend lines
only accelerate from there as we move down the
table. They do. By the time we reach the year
2000, Democratic candidate Mel Logan receives
just 22 % of the vote. Now? Yeah. The Republican
incumbent, Craig L. Thomas, hits 74%, securing
over 157 ,000 votes. So it's not just a trend,
it's becoming a landslide. And as we move further
down the timeline into 2008 and 2012, Republican
candidates Mike Enzi and John Barrasso both hit
an astonishing 76 % of the vote against their
respective Democratic challengers. The ceiling
for the challenger drops dramatically, cycle
after cycle. Look at these names in the table.
You have candidates like Joyce Corcoran in 2002
getting 27%. Dale Groutage in 2006 getting 30%.
And Charlie Hardy in 2014 dropping to just 17
% of the vote. Looking purely at the trajectory
of the numbers, you see a rapid solidification
of voting patterns. A completely different picture
from 1988. Exactly. Within a single decade. Wyoming
Senate races transitioned from that fraction
of a percent coin toss to commanding leads for
the Republican candidates in the 70 percentile
range. Again, just looking impartially at the
data in the source, the shift is undeniable.
The data documents a shift from a highly volatile
electoral environment to an environment of absolute
mathematical certainty. It is a profound shift
in a relatively short window of time. But as
I was tracking this unbroken streak of victories
down the table, another distinct pattern emerged
in the winners column. Oh, the three little letters.
Yes. Almost every single winning name from 1988
onward has the ink tag right next to it, standing
for incumbent. Looking at this table. The incumbent
tag might as well be an invincibility cloak.
It really is. It is perhaps the most powerful
force documented in this entire source. Out of
the 13 total races detailed between 1988 and
2020, nine were won by sitting incumbents. Nine
out of 13. You see the exact same names locking
in their positions cycle after cycle. Malcolm
Wallop defends his seat in 1988. Al Simpson defends
in 1990. Craig L. Thomas wins in 1994 and then
defends that seat as an incumbent in 2000 -2006.
Mike Enzi wins in 1996 and defends it in 2002
-2008 and 2014. And John Barrasso wins in 2008
and defends in 2012 and 2018. It's clockwork.
It is. But wait, you mentioned 9 out of 13 races
went to incumbents. That leaves a few gaps in
the timeline where the seat was entirely open.
Right, where there was no incumbent. I would
assume those open years without a sitting politician
defending the office would look more like that
1988 nail biter. But the numbers here tell a
slightly different story. We can isolate those
specific open seat elections in the data set.
They happened in 1994, 1996 and 2020. OK, let's
look at 1994. Mike Sullivan ran against Craig
L. Thomas for an open seat. And Thomas won with
59 percent of the vote. Then in 1996, Kathy Karpin
ran against Mike Enzi. Enzi won with 54%. And
skipping ahead to 2020, Marav Ben -David ran
against Cynthia Loomis. Where Loomis secured
the seat with 72 % of the vote. So even without
the built -in advantage of already holding the
office, the candidates from the dominant party
still comfortably secured the seats. They did.
But those numbers do highlight a fascinating
nuance in the momentum. What do you mean? Well,
look at 94 and 96. Those open seat margins are
in the mid -50s. That's noticeably lower than
the incumbent victories in the 70s that immediately
follow them. Ah, I see. That makes me think of
an analogy to help visualize the sheer force
of this data. I want you to think of incumbency
like a moving freight train. A freight train.
Okay, the physics of that actually map quite
well to electoral momentum. Right. Getting an
open seat is like trying to get a massive train
moving from a dead stop. It takes an incredible
amount of energy, resources, and fuel. The slightly
lower margins of victory, like that 54 or 59
percent, show that it is a heavier lift to win
when you're starting from zero. Exactly. But
once that politician is in the seat, they become
the incumbent. The train is moving down the track.
We have the machinery of the office, the established
donor networks, the universal name recognition.
And trying to unseat them is like trying to stand
on the tracks and push a moving freight train
backward. It's nearly impossible. The repetitive
streak of incumbent victories in this source
hitting 70, 73, 76 percent cycle after cycle
clearly demonstrates how hard it is to stop that
train once it has reached cruising speed. The
incumbent advantage operates as a compounding
force in this data set. It does. However, this
established predictability introduces a fascinating
paradox regarding voter behavior. Oh, a paradox.
Yeah. If the percentages become so stable, if
the electorate knows the freight train is going
to keep rolling with Sully. 70 % of the vote
standard political theory might suggest that
voter interest would decline. Right. People might
start showing up to the polls if the outcome
feels predetermined. Why bother voting if you
already know the results? Exactly. But standing
down the raw vote totals, I noticed an anomaly
that proves the exact opposite is happening here.
Let's isolate the year 2008. 2008 is a very interesting
year in this table. There's a strange formatting
choice. There are actually two distinct elections
listed for the exact same year. The source explains
this 2008 double feature quite clearly, actually.
One of the 2008 entries is explicitly marked
as a special election. Right, so special, right
in parenthesis. This special election was won
by John Barrasso. He secured 73 % of the vote
against Nick Carter's 27%. But then the very
next line is the regular 2008 election. Correct.
Where incumbent Mike Enzi secured 76 percent
of the vote against Chris Rothfuss's 24 percent.
And the source's navigation sidebar is designed
to explicitly track these even year specials
alongside the regular election cycles. Seeing
two massive statewide federal races happening
side by side on the same ballot is a highly unique
data point. It is. But the element that truly
stands out to me about 2008 and the years that
follow it is. The sheer volume of participation.
The raw numbers. Yes. The percentage spreads
might look identical year after year, just hovering
in that 70 -30 split. But the raw numbers tell
a story of massive undeniable growth. Let's rewind
back to that 1988 baseline for a second. Okay.
If you add the raw votes together for Vinnich
and Wallop, you get roughly 180 ,000 total votes
cast in the state. 180 ,964 total votes in 1988,
to be precise. No. Fast forward to the bottom
of our table, the year 2020. This is the open
seat race between Murat Ben -David and Cynthia
Loomis. Ben -David pulled in roughly 72 ,700
votes. Loomis brought in over 198 ,000 votes.
So if you add those together. Total turnout surged
to over 270 ,000 votes. What's fascinating here
is the duality of the data. How so? On one hand,
the political outcome demonstrates incredible
stability. The percentage margin stayed remarkably
stable in the 70 percentile range during the
later years of the data set. Very predictable.
But beneath that static percentage, the dynamic
reality is that the raw number of citizens participating
grew by leaps and bounds. An increase from roughly
180 ,000 to over 270 ,000. That is a surge of
nearly 100 ,000 voters in a state with a historically
small population. It's massive. It is. The narrative
that mathematically predictable elections automatically
lead to widespread voter apathy is directly contradicted
by the source material. Civic engagement actually
deepened as the margins widened. It really forces
you to rethink the relationship between competitiveness
and turnout. People aren't just voting because
they think their single ballot will be the tiebreaker.
Right. They aren't waiting for another 1988.
Exactly. They are voting to participate in the
established momentum of their state. It's about
being part of the process. So we have covered
a massive amount of ground here, from a century
-old constitutional rule change and a 1 ,300
-vote cliffhanger. To the unstoppable freight
train of incumbency. And a massive counterintuitive
surge in voter turnout. So what does this all
mean? If we synthesize this entire deep dive,
the overarching takeaway is that this single
Wikipedia table transcends being just a list
of names and numbers. It's far more than a spreadsheet.
It functions as a clear empirical timeline of
political evolution. It shows us the precise
window where a state's political identity rapidly
solidifies over a 30 -year period. And it mathematically
proves the undeniable compounding advantage of
holding an office once you win it. And perhaps
most importantly, it maps a complex evolution
of voter turnout, showing a populace that became
increasingly engaged in the democratic process.
A popular vote process that... As the sidebar
reminded us at the very beginning, they were
entirely excluded from for the first 125 years
of the nation's history. It gives you a profound
appreciation for the meticulous cataloging happening
in these databases. It really does. The structure
of the page tells the story just as loudly as
the numbers do. But before we wrap up, I want
to leave you with a final thought. Yeah, drawn
directly from one last very subtle detail tucked
away in the source material. There is always
one more detail hiding in the architecture of
the page. Always. Think back to that navigation
box we discussed at the very beginning, the one
that split history into the legislative era and
the popular vote era. Right. 1788 to 1913 and
then 1914 to present. Underneath the section
for 1914 present, there is a whole separate category
listed. It is simply titled odd year specials.
The source lists a specific cadence of them.
Years like 1913, 1921, 1925, 1931. And skipping
ahead, you see 1974, 75, 2013, and 2017. And
I want you to... Ponder this. We just spent this
entire deep dive analyzing how incredibly stable
and predictable the regular even year incumbent
victories are in this data set. The freight train
just keeps rolling on a reliable six year schedule.
Protected by the power of incumbency and a highly
engaged voting base. Exactly. But that list of
odd year specials is sitting right there in the
sidebar, proving that the schedule is fragile.
What kind of sudden unexpected event causes a
United States Senate seat to abruptly open up
in an odd year? Completely. bypassing the normal
predictable election cycle. Right. And how does
that sudden injection of chaos disrupt the very
political momentum and mathematical certainty
we just spent all this time exploring? It is
a stark reminder that no matter how stable and
unyielding the data looks on a screen, the real
world is always capable of throwing a wrench
into the gears. It's a critical question to reflect
on. Data perfectly captures the solidifying trends
of the past, but the architecture of the system
always leaves room for the unpredictable disruptions
of the future. Thank you so much for joining
us on this deep dive today. It's been a fascinating
look at the numbers behind the names. We hope
we've changed the way you look at a simple table
of numbers and the sidebars that surround them.
Keep questioning the data, keep looking for the
hidden momentum, and most importantly, keep exploring.
We will catch you next time.