The International Olympic Committee (IOC) adopted Rule 40 in 1991 to protect sponsors from “ambush marketing,” corporate pursuit of unauthorized exploitation of Olympic brand without paying for it. In the run-up to the 2012 London Olympic Games, Facebook and Twitter’s emergence sparked an uptick in athletes hawking their own sponsors. The IOC updated Rule 40 in 2015, allowing unofficial sponsors to feature their sponsored athletes in campaigns while prohibiting Olympic location references and use of the words Olympics, Summer Games, other “Olympic-related terms,” official Twitter hashtags and logos. Per Origami Logic’s Brand Olympics 2016 Report, Instagram accounted for over 77% of total social engagement across platforms. While Nike (gold medal), Adidas (silver medal) and Under Armour (bronze medal) reflected 91 percent of Instagram engagement, did sponsorship give Nike a huge advantage? Two-sample t-tests in Minitab 17 proved otherwise, also revealing that Under Armour potentially had the most engaging content.

1. Rule 40 and the 2016 Rio Olympics
Roderick Head
Indiana University
Data Science Graduate Program
Bloomington, IN 47408
1.901.553.4031
rthead@indiana.edu
ABSTRACT
The International Olympic Committee (IOC) adopted Rule 40 in
1991 to protect sponsors from “ambush marketing,” corporate
pursuit of unauthorized exploitation of Olympic brand without
paying for it. In the run-up to the 2012 London Olympic Games,
Facebook and Twitter’s emergence sparked an uptick in athletes
hawking their own sponsors. The IOC updated Rule 40 in 2015,
allowing unofficial sponsors to feature their sponsored athletes in
campaigns while prohibiting Olympic location references and use
of the words Olympics, Summer Games, other “Olympic-related
terms,” official Twitter hashtags and logos. Per Origami Logic’s
Brand Olympics 2016 Report, Instagram accounted for over 77%
of total social engagement across platforms. While Nike (gold
medal), Adidas (silver medal) and Under Armour (bronze medal)
reflected 91 percent of Instagram engagement, did sponsorship give
Nike a huge advantage? Two-sample t-tests in Minitab 17 proved
otherwise, also revealing that Under Armour potentially had the
most engaging content.
CCS Concepts
• Human-centered computing➝Social media networks
Keywords
Olympics; social media mining; sports marketing
1. INTRODUCTION
The International Olympic Committee (IOC) adopted Rule 40 in
1991 to "preserve the unique nature of the Olympic games by
preventing over-commercialization" and protect sponsors who
spend millions of dollars for exclusive marketing
rights. Preventing Olympians from hawking their own sponsors
became increasingly problematic in the run-up to the 2012 London
Olympic Games due to Facebook and Twitter’s emergence. The
IOC found themselves scrambling to respond amid struggling to
figure out social media. Rule 40 was updated in 2015 so that
unofficial sponsors, those sponsoring athletes but not the games,
could feature them in campaigns.
However, unofficial sponsors could not use the words Olympics,
Summer Games, or other “Olympic-related terms” nor the official
Twitter hashtags #Rio2016 and #TeamUSA, logos, or reference
Olympic location. Enforced by each nation’s Olympic committee,
athletes could be disqualified and stripped of medals if found in
violation of Rule 40 [1], [5].
Sally Bergesen, founder of apparel company Oiselle, which
sponsored 15 Olympic hopefuls, feels Rule 40 is too restrictive and
effectively bars lesser-known athletes from earning money from
their Olympic appearances. While companies could become
Olympic sponsors, it would underwrite the IOC instead of the
athlete’s training. Zaileen Janmohamed, SVP of Client Services for
GMR Marketing, thinks the wider playing field could diminish the
value of Olympic sponsorships [8].
Starting in late March and throughout the 2016 Rio Olympic
Games, Origami Logic, a marketing analytics company and global
leader in marketing performance measurement, tracked Olympics-
related social activity of 40 brands, 38 worldwide and Team USA
sponsors, and two non-sponsors (Adidas and Under Armour),
highlighting the results on a campaign microsite developed by their
demand generation agency, Spear Marketing Group. Origami
Logic drove traffic to the microsite and campaign awareness
through ads on Google AdWords and LinkedIn. Microsite visitors
could click through to learn more about successful campaigns,
engage with social media, and sign up to receive a “Brand
Olympics” newsletter. Results were also promoted on Twitter
(@brandolympics) and using the hashtag: #BrandOlympics2016.
Per Origami Logic’s Brand Olympics 2016 Report, Instagram
accounted for 15.43 million social engagement activities, over 77%
of the cumulative total across platforms. Nike, Adidas and Under
Armour took gold (7.80 million), silver (4.98 million) and bronze
(2.72 million) medals in the Brand Olympics based on total
engagement, and unsurprisingly were the top Instagram brands,
collectively accounting for 91% of engagement. Nike and Under
Armour were also among the top five brands with the most
amplification (i.e. most shares), position 1 and 4,
respectively. Each of the top five brands had videos/commercials
that were viewed and shared often. While Nike (gold medal),
Adidas (silver medal) and Under Armour (bronze medal) accounted
for 91 percent of Instagram engagement, with respective total social
engagement scores (combination of likes, comments, and shares for
organic posts), did sponsorship really give Nike a huge advantage
over Adidas and Under Armour [6], [2]?
2. BODY
2.1 Data Selection
Instagram was chosen as the social media platform for this paper
due to its overall share of 2016 Rio Olympic Games social media
engagement. Considering the 38 sponsors represent 95 percent of
the brands tracked for the “Brand Olympics,” Adidas and Under
Armour respectively finishing as silver and bronze medalists under
Rule 40 non-sponsor restrictions defies serious odds and presents
an interesting story. This is underscored by the fact that the
Olympic logo is recognized by 93 percent of the world, and the
IOC’s forecasts for 2013-2016 that sponsors will have collectively
dropped $1.1 billion for exclusive association with Games within
the 4-year quadrennial [4].
Picodash, an advanced Instagram search engine and social media
management tool that helps Brands, Publishers, Researchers and
Journalists search and curate Instagram content by location,
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2. hashtags and places, was used to search each brand by user name
to obtain Nike, Adidas and Under Armour posts between March 27,
2016, through August 21, 2016. The aforementioned dates
coincide with when non-sponsors were required to start advertising
and ending on the date of the 2016 Rio Olympic Closing
Ceremonies. Previously known as Gramfeed, the transition to
Picodash complies with the new Instagram API Platform changes
as of June 1, 2016, which no longer permit 3rd-party apps to display
public Instagram content to just anyone accessing the app.
Additionally, Instagram based apps cannot have the word “insta”
or “gram” in the name. Picodash provides its services via a paid
subscription model, which includes a three-day trial period that
does not charge Instagram users if cancelled within aforementioned
period, and charges an $8 monthly subscription fee.
Prior to discovering Picodash via Stackflow, an online community
for programmers, efforts were made to obtain the needed Instagram
data. However, because the access needed was beyond basic
permissions, which required submission of an app for review,
Instagram API changes prevented me from doing so. Based on
email communication with Picodash, although not publicly visible,
exporting data to a spreadsheet was possible. Once posts were
loaded from Nike, Adidas and Under Armour accounts in Google
Chrome, open console (right click - inspect - console tab) and type
exportMedia() to save as a csv file [3].
2.2 Preprocessing
When data was pulled by Instagram account, it was already in
tabular format with 19 features and 32 instances. CSV files
associated with Nike, Adidas and Under Armour were uploaded
into Jupyter Notebook. While the data was relatively clean, official
hashtags were noticeably absent from Nike’s instances. Several
missing values within four features representing Location ID,
Location Name, Latitude and Longitude was consistent across all
three accounts. The image below is associated with the Adidas csv
file.
Figure 1
The aforementioned features were deleted from each brand’s csv
along with seven others: original_photo, standard_resolution,
low_resolution, thumbnail, user_id and profile_picture. Date_gmt
was changed to gmt. Username and full_name values were
identical, prompting removal of full_name. Before consolidating
the csv files, one feature was added, sponsor, resulting in nine
features.
2.3 Materials and Methods
While both regression and classification models were explored to
analyze the data, which proved to be a rather frustrating experience,
counsel from instructor prompted a change in direction since there
were only 96 instances. As a result, two-sample t-tests were done
in statistical software Minitab 17. Two-sample t-tests are
hypothesis tests in statistics when you want to compare the means
of two different groups. T-tests are called such because the test
results are based on t-values, an example of what statisticians call
test statistics, a standardized value that is calculated from sample
data during a hypothesis test. T-value calculations compare your
sample mean(s) to the null hypothesis, incorporating both the
sample size and variability of the data. A zero t-value indicates that
the sample results equal the null hypothesis. The absolute value of
the t-value increases as the difference between the sample data and
the null hypothesis increases. Determining whether t-value is
unusual enough to warrant rejecting the null hypothesis is the
ultimate goal. However, doing so requires a probability
calculation.
Being able to take the statistic from a specific sample and place it
in the context of a known probability distribution is the foundation
behind a hypothesis test. Under the assumption the null hypothesis
is true, a probability allows us to determine commonality or rarity
of t-value. We can conclude that the effect observed in sample is
inconsistent with the null hypothesis if the probability is low
enough. This is where p-value, probability of obtaining a result
equal to or more extreme than what was actually observed, when
the null hypothesis is true. The higher the t-value, the lower the p-
value, increasing the likelihood of statistical significance between
the two groups. If the p-value is less than the common significance
level of 0.05, you reject the null hypothesis. DF refers to degrees
of freedom, which is one less than the sample size [7].
Figure 2

3. Figure 3
Figure 4
Figure 5
2.4 Results
The first round of analysis consisted of t-tests comparing Nike likes
to Adidas and Under Armour likes and Nike comments to Adidas
and Under Armour comments.
Figure 6
Figure 7
Figure 8
Figure 9
The second round of analysis compared Nike likes/followers to
Adidas and Under Armour likes/followers and Nike
comments/followers to Adidas and Under Armour
comments/followers. The higher the t-value, the lower the p-value,
increasing the likelihood of statistical significance between the two
groups. DF refers to degrees of freedom, which is one less than the
sample size.

4. Figure 10
Figure 11
Figure 12
Figure 13
Figure 14
Results from the first round of analysis show that effects observed
in all samples is inconsistent with the null hypothesis. Not only is
the p-value less than the common significance of 0.5, it is actually
0.0, meaning there is a zero percent chance the null hypothesis is
true. With rejection of the null hypothesis, significant difference
between Nike and Adidas and Nike and Under Armour based on
likes and followers is conclusive.
Nike has a significant advantage over Adidas and Under Armour in
likes and followers. When calculating likes/followers, Under
Armour had the highest score, followed by Adidas and Nike, while
Nike had the highest comments/followers score, followed by Under
Armour and Adidas.
3. CONCLUSION
While Nike had more followers, like and comments than Adidas
and Under Armour, they did not dominate both likes/followers and
comments/followers. Under Armour, which has far less followers
than Adidas, had a much higher likes/followers score than both
Adidas and Nike, which were nearly identical. When comparing
comments/followers, although Nike had the highest score of the
three brands, substantially higher than Adidas, there was very little
separation between Nike and Under Armour. Not only does the
data suggest that Nike did not have a huge advantage as an Olympic
sponsor, based on likes/followers and comments/followers, Under
Armour potentially had the most engaging Instagram content.

5. Origami Logic tracked social activity of 40 brands, including 11
international sponsors, 27 Team USA sponsors and two non-
sponsors from March 27, 2016 through August 12, 2016, across
Facebook, Instagram, Twitter, YouTube and Google+. Origami
identified messages related to Olympics campaigns through
keyword searches including phrases that could only be used by
sponsors such as “Rio 2016” and “Team USA” campaign hashtags
like #SpeedTakes (Adidas) and #RuleYourself (Under Armour).
Origami assigned brands a social engagement score by calculating
total likes, comments and shares.
Although Origami Logic’s Brand Olympics 2016 Report is
referenced, there are differences that make this project a novel
contribution. This project educates the reader on the IOC’s Rule
40, its historical evolution amid the emergence of Facebook and
Twitter and offers legal, apparel industry and marketing agency
stakeholder perspectives on Rule 40. For marketers engaged in
social media mining involving Instagram data, it provides an
inexpensive solution in Picodash as a workaround for Instagram
API challenges. Minitab 17, a statistical software largely used by
Six Sigma practitioners, was used to run two-sample t-tests to
compare Nike, Adidas and Under Armour to determine if Olympic
sponsorship gave Nike a huge advantage. For some readers, this is
their first exposure to Minitab.
Future research questions surround the earning potential of
Olympic athletes as it relates to Rule 40, hashtags and captions
associated with each brand’s Instagram posts. For athletes tied to
non-sponsors, is a happy median possible with Rule 40 in a future
amendment that would not hinder earning potential with personal
appearances? Nike did not use any of the official Olympic
hashtags. Two of Nike’s top five Instagram posts based on likes
had no hashtag. The post with the most likes had the hashtag
#mambaday and caption “Careers end, legends are forever,”
associated with two-time Olympic gold medalist Kobe Bryant
playing the final game of his storied 20-year NBA career with the
Los Angeles Lakers. Four of Under Armour’s top five posts based
on likes included the Instagram handle @m_phelps00 in captions,
encouraging fans to follow Michael Phelps, who retired from
competitive swimming after the 2016 Rio Olympics as the most
decorated medalist ever. Therefore, if omitting the #mambaday
post, Under Armour would likely have the highest
comments/followers score.
4. ACKNOWLEDGMENTS
Special thanks to Vincent Malic for his invaluable counsel during
the course of this project and Picodash for having a platform to
work around Instagram API challenges.
5. REFERENCES
[1] Athletes Battle the Olympic Brass for the Right to Make Money:
2016. http://wired.com/2016/08/olympians-take-back-social-
media-rule40. Accessed: 2016- 12- 14.
[2] Brand Olympics 2016 Report: 2016.
https://resources.origamilogic.com/brand-olympics/brand-
olympics-2016-report. Accessed: 2016- 12- 14.
[3] Instagram Search and Explore: 2016.
https://www.picodash.com/about/faq. Accessed: 2016- 12- 14.
[4] IOC Rule 40: Olympic Sponsorship's Achilles Heel: 2016.
http://linkedin.com/pulse/ioc-rule-40-olympic-sponsorships-
achilles-heel-idy-uyoe. Accessed: 2016- 12- 14.
[5] Olympic committee on the prowl — for misuse of hashtags:
2016. http://www.cnbc.com/2016/07/28/olympic-committee-on-
the-prowl--for-misuse-of-hashtags.html. Accessed: 2016- 12- 14.
[6] Origami Logic Scores Gold with “Brand Olympics” Campaign
- The Point: 2016. http://spearmarketing.com/blog/origami-logic-
scores-gold-with-brand-olympics-campaign/. Accessed: 2016- 12-
14.
[7] Understanding t-Tests: t-values and t-distributions | Minitab:
2016. http://blog.minitab.com/blog/adventures-in-
statistics/understanding-t-tests-t-values-and-t-distributions.
Accessed: 2016- 12- 14.
[8] What is Rule 40 at the Olympics?: 2016.
http://www.si.com/olympics/2016/07/27/rule-40-explained-2016-
olympic-sponsorship-blackout-controversy. Accessed: 2016- 12-
14.