I’ve been writing about how Twitter Sentiment affects NFL Games for a few weeks on Medium now. It’s been quite an interesting dataset. My initial hypothesis going into this was that teams with higher pregame Twitter sentiment would win. I was shown wrong in the first 5 games I analyzed. From weeks 12 to 15, I analyzed 5 NFL games and in all 5 the team with the lower Twitter sentiment won. These were the 5 games:

• Week 12, Browns vs Ravens
• Week 13, Cowboys vs Saints
• Week 14, Rams at Cardinals
• Week 15, Packers at Ravens
• Week 15, Vikings at Bears

In this post, we’re going to do a mathematical/numerical analysis on the sentiments of these teams. We want to see if there is a mathematical reason that teams with lower sentiment won more often. The current ratio is 11 to 8, with lower sentiment teams winning 11 games and higher sentiment teams winning 8. 

NFL Week 16 Games

In week 16, the team with the higher sentiment won 5 games while the team with the lower sentiment won 6 games.

1. Twitter Sentiment: Steelers at Chiefs, Week 16, 2021 — Lower sentiment team (Chiefs) win
2. Twitter Sentiment: Broncos at Raiders, Week 16, 2021 — Lower sentiment team (Raiders) win
3. Twitter Sentiment: Bears at Seahawks, Week 16, 2021 — Lower sentiment team (Bears) win
4. Twitter Sentiment Analysis: Ravens at Bengals, Week 16, 2021 — Lower sentiment team (Bengals) win
5. Twitter Sentiment Analysis: Rams at Vikings, Week 16, 2021 — Higher sentiment team (Rams) win
6. Twitter Sentiment Analysis: Chargers at Texans, Week 16, 2021 — Lower sentiment team (Texans) win
7. Twitter Sentiment Analysis: Buccaneers at Panthers, Week 16, 2021 — Higher sentiment team (Bucs) win
8. Twitter Sentiment Analysis: Jaguars at Jets, Week 16, 2021 — Higher sentiment team (Jets) win
9. Twitter Sentiment Analysis: Giants at Eagles, Week 16, 2021 — Lower sentiment team (Eagles) win
10. Twitter Sentiment: Washington Football Team vs Cowboys, Week 16 — Higher sentiment team (Cowboys) win
11. Twitter Sentiment: Dolphins at Saints, Week 16 | by Yujian Tang – Higher sentiment team (Dolphins) win

Twitter Sentiment Values vs Actual Outcomes

Clearly Twitter sentiment isn’t a strong enough predictor by itself to predict outcomes of games. This leads us to another question though, can it be used? Let’s take a look at the numerical analysis.

When Did Lower Twitter Sentiment Teams Win?

These are the six games in which the lower sentiment team won fro week 16

1. Twitter Sentiment: Steelers at Chiefs, Week 16, 2021 — Lower sentiment team (Chiefs) win
2. Twitter Sentiment: Broncos at Raiders, Week 16, 2021 — Lower sentiment team (Raiders) win
3. Twitter Sentiment: Bears at Seahawks, Week 16, 2021 — Lower sentiment team (Bears) win
4. Twitter Sentiment Analysis: Ravens at Bengals, Week 16, 2021 — Lower sentiment team (Bengals) win
5. Twitter Sentiment Analysis: Chargers at Texans, Week 16, 2021 — Lower sentiment team (Texans) win
6. Twitter Sentiment Analysis: Giants at Eagles, Week 16, 2021 — Lower sentiment team (Eagles) win

Team Record

Game	Pre Game Win Differential
Steelers at Chiefs	Chiefs Up 3 W
Broncos at Raiders	Same record
Bears at Seahawks	Bears Down 1 W
Ravens at Bengals	Same record
Chargers at Texans	Texans Down 5 W
Giants at Eagles	Eagles Up 3 W

Average win differential for when team with lower Twitter sentiment wins: 0

Sentiment Value Difference

Game	Sentiment Difference
Steelers at Chiefs	0.1874 vs 0.1249 → -0.0625
Broncos at Raiders	0.1674 vs 0.1310 → -0.0364
Bears at Seahawks	0.0378 vs 0.0699 → -0.0321
Ravens at Bengals	0.1477 vs 0.1322 → -0.0155
Chargers at Texans	0.0451 vs 0.0392 → -0.0059
Giants at Eagles	0.1280 vs 0.0711 → -0.0569

Average sentiment difference when team with lower Twitter sentiment wins: -0.0295

Point Differentials

Game	Point differential prior to game
Steelers at Chiefs	-3.1 to 6.4 → 9.5
Broncos at Raiders	3.0 to -5.4 → -8.4
Bears at Seahawks	-7.8 to 0.0 → -7.8
Ravens at Bengals	1.4 to 4.7 → 3.3
Chargers at Texans	0.6 to -11.8 → -12.4
Giants at Eagles	-6.6 to 4.0 → 10.6

Average game point differential when the team with the lower Twitter sentiment won: -5.2

Interesting note: in the 6 games that teams with lower sentiment won, 5 of those were home games.

When Did Higher Twitter Sentiment Teams Win?

1. Twitter Sentiment Analysis: Rams at Vikings, Week 16, 2021 — Higher sentiment team (Rams) win
2. Twitter Sentiment Analysis: Buccaneers at Panthers, Week 16, 2021 — Higher sentiment team (Bucs) win
3. Twitter Sentiment Analysis: Jaguars at Jets, Week 16, 2021 — Higher sentiment team (Jets) win
4. Twitter Sentiment: Washington Football Team vs Cowboys, Week 16 — Higher sentiment team (Cowboys) win
5. Twitter Sentiment: Dolphins at Saints, Week 16 | by Yujian Tang – Higher sentiment team (Dolphins) win

Team Record

Game	Pre game Win Differential
Rams at Vikings	Rams Up 3 W
Bucs at Panthers	Bucs Up 5 W
Jaguars at Jets	Jets Up 1 W
WFT at Cowboys	Cowboys Up 4 W
Dolphins at Saints	Same

In the games where the team with the higher Twitter sentiment won, the winning team was up by an average of 2.6 wins.

Sentiment Value Difference

Game	Sentiment Difference
Rams at Vikings	0.2115 vs 0.0636 → 0.1479
Bucs at Panthers	0.1600 vs 0.0891 → 0.0709
Jaguars at Jets	0.0383 vs 0.0927 → 0.0544
WFT at Cowboys	0.1499 vs 0.1730 → 0.0231
Dolphins at Saints	0.1877 vs 0.1435 → 0.0442

The average sentiment difference for the games where the team with the higher Twitter sentiment won in Week 16 was 0.0681.

Point Differential

Game	Pre game Point Differential
Rams at Vikings	5.9 to 1.4 → 4.5
Bucs at Panthers	7.4 to -3.0 → 10.4
Jaguars at Jets	-12.4 to -12.7 → 0.3
WFT at Cowboys	-4.9 to 7.7 → 12.6
Dolphins at Saints	-1.9 to 2.0 → -3.9

The average point differential for higher Twitter sentiment teams that won is 4.78.

An interesting thing to note here is that away teams won 3 out of 5 times when the higher sentiment team won.

Graph of Sentiment Differential vs Higher Twitter Sentiment Wins

Here are the graphs of the Twitter Sentiment Differential, Pregame Point Differential, and Win Differentials against whether or not the team with the higher sentiment won:

From the graphs we can tell that NONE of these individual predictors are good by themselves, but will a multivariate logistic regression with principal component analysis provide a better predictor? We’ll find out next time.

Code

Here’s the code we used for the Twitter Sentiment and Pulling the Tweets. 

Here’s the code for the graphs:

import matplotlib.pyplot as plt
 
# sentiment difference wins and losses
# team with higher sentiment win = 1, team with higher sentiment loss = 0
# x value = sentiment difference
x = [0.0625, 0.0364, 0.0321, 0.0155, 0.0059, 0.0569, 0.1479, 0.0709, 0.0544, 0.0231, 0.0442]
y = [0,0,0,0,0,0,1,1,1,1,1]
plt.scatter(x, y)
plt.title("Twitter Sentiment Differential")
plt.xlabel("Twitter Sentiment Difference")
plt.ylabel("Win/Loss")
plt.show()
# point difference wins and losses
# x value = point differential of winning team
# y value = win/loss
x = [9.5, -8.4, -7.8, 3.3, -12.4, 10.6, 4.5, 10.4, 0.3, 12.6, -3.9]
y = [0,0,0,0,0,0,1,1,1,1,1]
plt.scatter(x, y)
plt.title("Pre-game Point Differential")
plt.xlabel("Pre-game Point Difference")
plt.ylabel("Win/Loss")
plt.show()
 
# win differential wins and losses
# x value = winning team's win difference
# y value = did higher twitter sentiment team win
x = [3, 0, -1, 0, -5, 3, 3, 5, 1, 4, 0]
plt.scatter(x, y)
plt.title("Pre-game Win Differential")
plt.xlabel("Pre-game Win Difference")
plt.ylabel("Win/Loss")
plt.show()

Summary

What did we learn? It’s hard to predict NFL games.

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