Spurious correlation #4,191 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Cristiano Ronaldo's domestic league goal tally and the second variable is The price of gold. The chart goes from 2004 to 2014, and the two variables track closely in value over that time.

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Cristiano Ronaldo's domestic league goal tally and the second variable is The price of gold. The chart goes from 2004 to 2014, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As Ronaldo scores more goals, he creates a higher demand for soccer balls. This leads to a shortage of rubber, making it more profitable to mine for gold, thus increasing the price of gold. It's the golden touch of Ronaldo's scoring prowess!

^{Show image generation prompt} Model: dalle-3
Prompt: An image that looks like it is a scene from a Pixar movie, featuring a bustling football stadium filled with excited fans. In one corner, Cristiano Ronaldo celebrates a goal, with a digital display showing his domestic league goal tally increasing. Meanwhile, in another section, a hectic market scene features investors and traders closely watching the price of gold shooting upwards on digital screens. Fans wearing gold-colored merchandise are eagerly purchasing Ronaldo-themed memorabilia, contributing to the gold price surge. This unexpected connection between Ronaldo's performance and the price of gold leaves everyone intrigued. The depiction should include only scenes, people, and objects, it should not include text or speech bubbles.

This image generation prompt was also generated by AI, using the following sequence:

Model: gpt-3.5-turbo-1106
System prompt: You select one of a few potential scene descriptors that seems to go along with the variables described. You respond only with the scene descriptions provided and say nothing else.
User prompt: Here are two variables: Cristiano Ronaldo's domestic league goal tally and The price of gold. Given these, which of the following image style descriptions seems most appropriate? Pick the one that seems to be related to one of the variables at hand. Please respond with only one of the following potential descriptions: Magic realism An image that looks like it is a scene from a Pixar movie An image that looks like it is a scene from 'Star Wars' Cutsy graphics A scene from Skyrim
ChatGPT: An image that looks like it is a scene from a Pixar movie

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Cristiano Ronaldo's domestic league goal tally and The price of gold, in the following situation: As Ronaldo's goal tally rose, fans felt the "golden" touch of excitement, leading to increased spending on merchandise. This surge in demand for gold-colored memorabilia put pressure on the market, causing the price of gold to "kick off" and rise. As Ronaldo's stellar performance continued, more fans wanted to get their hands on anything related to the "golden" player, further fueling the gold price hike. This unexpected connection left economists and football fans alike wondering if Ronaldo's scoring abilities had turned him into a "golden" goose for the gold industry.. Keep the description simple.
ChatGPT: Picture a bustling football stadium filled with excited fans. In one corner, Cristiano Ronaldo celebrates a goal, with a digital display showing his domestic league goal tally increasing. Meanwhile, in another section, a hectic market scene features investors and traders closely watching the price of gold shooting upwards on digital screens. Fans wearing gold-colored merchandise are eagerly purchasing Ronaldo-themed memorabilia, contributing to the gold price surge. This unexpected connection between Ronaldo's performance and the price of gold leaves everyone intrigued.

Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ An image that looks like it is a scene from a Pixar movie ] and depicting this scene: Picture a bustling football stadium filled with excited fans. In one corner, Cristiano Ronaldo celebrates a goal, with a digital display showing his domestic league goal tally increasing. Meanwhile, in another section, a hectic market scene features investors and traders closely watching the price of gold shooting upwards on digital screens. Fans wearing gold-colored merchandise are eagerly purchasing Ronaldo-themed memorabilia, contributing to the gold price surge. This unexpected connection between Ronaldo's performance and the price of gold leaves everyone intrigued. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: An image that looks like it is a scene from a Pixar movie, featuring a bustling football stadium filled with excited fans. In one corner, Cristiano Ronaldo celebrates a goal, with a digital display showing his domestic league goal tally increasing. Meanwhile, in another section, a hectic market scene features investors and traders closely watching the price of gold shooting upwards on digital screens. Fans wearing gold-colored merchandise are eagerly purchasing Ronaldo-themed memorabilia, contributing to the gold price surge. This unexpected connection between Ronaldo's performance and the price of gold leaves everyone intrigued.

*Variations in the User Prompts from chart to chart are just the result of random number generation in Python. I wrote a few arrays of various styles and methods to ask questions to change up the results. Every time this site writes an explanation or generates an image, the script picks from each at random.

I sequence the requests into multiple prompts because I find GPT 3.5 to perform much better with short, well-managed contexts. Thus, I track the context directly in Python and only ask ChatGPT targeted questions.
^{Show prompt for explanation} Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how an increase in Cristiano Ronaldo's domestic league goal tally caused The price of gold to increase.

AI academic paper

(Because p < 0.01)

Kicking Around Karats: A Gold-Scoring Connection Between Cristiano Ronaldo's League Goals and Price of Gold

The Journal of Sports Economics and Precious Metal Dynamics

Jan 2024

Reminder: This paper is AI-generated. Not real!

^{Show prompt used to generate this paper} Quick note: This sequence is long and repetitive. That's how the prompt engineering works for this one. I manage the output in Python to format it into this PDF.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft a literature review section of an academic research paper, that starts out dry for the first few sentences but then becomes hilarious and goofy.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up a literature review section of an academic research paper presenting the findings of the connection between Cristiano Ronaldo's domestic league goal tally and The price of gold. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Speak in the present tense for this section (the authors find...), as is common in academic research paper literature reviews. Name the sources in a format similar to this: In "Book," the authors find lorem and ipsum.

Make up the lorem and ipsum part, but make it sound related to the topic at hand.

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then devolve ever further, and mention something completely ridiculous, like you conducted literature review by reading the backs of shampoo bottles.

Here is the title and abstract of the paper:
[[TITLE]]
"Kicking Around Karats: A Gold-Scoring Connection Between Cristiano Ronaldo's League Goals and Price of Gold"

[[ABSTRACT]]
This study investigates the intriguing correlation between Cristiano Ronaldo's domestic league goal tally and the price of gold. Utilizing data extracted from Soccerway and Kitco, a correlation coefficient of 0.9491534 with a statistical significance of p < 0.01 was calculated for the period spanning from 2004 to 2014. The results reveal an unexpectedly robust relationship between Ronaldo's proficiency in finding the back of the net and the value of the precious metal. It appears that as he hammers goals, the value of gold also seems to strike higher. This unexpected finding provides a novel perspective on the intersection of sports and financial markets and prompts further inquiry into the quirky nexus of goal-scoring prowess and commodity prices.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The interplay between sports and financial markets has long been an area of interest for researchers seeking to uncover hidden connections and unexpected correlations. In this study, we scrutinize the intriguing relationship between the domestic league goal tally of the renowned footballer Cristiano Ronaldo and the price of gold. While it may seem at first glance that these two variables have as much in common as a hedgehog and a telescope, our findings reveal a striking association between Ronaldo's goal-scoring prowess and the value of the precious metal.
As we embark on this investigation, it is important to acknowledge the seemingly disparate nature of our variables. On one side, we have the prodigious goal-scoring ability of the footballing maestro, a feat that has garnered him international acclaim and multiple prestigious accolades. On the other side, we have the enigmatic and alluring allure of gold, a commodity that has captivated human fascination for millennia and has wielded substantial influence over the flux of financial markets.
Attempting to reconcile these seemingly incongruent elements has led us down a path that is as unpredictable as a particle in quantum mechanics. However, the pursuit of knowledge often involves navigating through uncharted territory, and our journey into the unexplored terrain of sport and commodity pricing has certainly been no exception. We have ventured into this realm armed with patience, an array of statistical analyses, and an unyielding determination to unravel the mystery behind this surprising relationship.
One cannot help but marvel at the unexpected twist in the narrative that our data has unveiled. The discovery of a significant correlation between Ronaldo's goal-scoring exploits and the price of gold is as remarkable as stumbling upon a unicorn in a field of statistical haystacks. It prompts not only a reevaluation of our prior assumptions but also an appreciation of the quirks and intricacies that underpin the web of connections in the world of data.
The implications of this unforeseen connection stretch beyond the boundaries of the football pitch and the trading floor. It raises questions about the far-reaching impact of individual sporting performances on global economic dynamics and challenges the traditional boundaries that demarcate the realms of sports and finance.
As we delve deeper into the labyrinth of data and analysis, we invite the reader to join us on this expedition of discovery, where the unexpected converges with the empirical and where the goals of a footballer may hold the key to unlocking the mysteries of the commodities market.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

To explore the connection between Cristiano Ronaldo's domestic league goal tally and the price of gold, the authors have engaged with an array of studies and scholarly works that delved into the realms of sports analytics, financial markets, and seemingly incongruous correlations. In "The Relationship Between Sporting Achievements and Commodity Prices," Smith et al. present a framework for analyzing the potential influence of athletic performances on commodity markets, though the specific case of a footballer's goal-scoring prowess and its impact on gold prices remains unexplored. Similarly, Doe's "Moneyball Meets Metal Market" offers insights into the application of statistical models from sports to finance, yet the spark that ignites the relationship between a player's on-field performance and the value of a precious metal remains uninvestigated.

Moving beyond the conventional boundaries of academic studies, a broader exploration of related literature reveals a variety of non-fiction works with tangential connections to our subject matter. "The Gold Standard: The History and Legacy of Gold in Finance," by Jones, provides a historical overview of gold's role in economic systems, offering an intriguing backdrop to our investigation of the metal's unexpected dance with football prowess. We also find "The Art of Goal-Scoring: A Statistical Analysis," a definitive guide to the quantification of scoring proficiency in football, which, although not directly related to commodities, offers a glimpse into the statistical intricacies of our central variable.

In the realm of fiction, we encounter works that, on the surface, seem unrelated but harbor subtle parallels to our inquiry. "The Alchemist" by Paulo Coelho, a captivating tale of self-discovery and personal legend, metaphorically mirrors the enigmatic quest to unravel the hidden connections between Ronaldo's goals and the fluctuations of gold prices, though without the literal statistical underpinnings. Meanwhile, "The Goldfinch" by Donna Tartt offers a narrative centered around a stolen painting, which, although not directly related to the price of gold or the art of scoring goals, inadvertently inspires novel perspectives on the intersections of value and human endeavor.

Venturing further beyond the traditional confines of academic literature, the authors have engaged in an unorthodox exploration that involved an unexpected source of insight. In a highly unconventional approach, the team conducted a thorough review of the backs of various household products, including shampoo bottles, only to find that the purported connections between Ronaldo's goals and the price of gold were sorely lacking in such unlikely places. This unconventional tactic, while yielding no meaningful findings, underscored the inherent unpredictability of research pursuits and the indefatigable quest for unearthing knowledge from the most improbable sources.

Indeed, as the authors navigate through the labyrinthine landscape of scholarly works and unconventional sources, a tapestry of unexpected parallels, subtle tangents, and ludicrous endeavors emerges, painting a vivid backdrop to the peculiar investigation at hand.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft the methodology section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the methodology section of an academic research paper presenting the findings of the connection between Cristiano Ronaldo's domestic league goal tally and The price of gold. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Your research team collected data from all across the internet, but mostly just used information from Soccerway and Kitco . You used data from 2004 to 2014

Make up the research methods you don't know. Make them a bit goofy and convoluted.

Here is the title, abstract, and introduction of the paper:
[[TITLE]]
"Kicking Around Karats: A Gold-Scoring Connection Between Cristiano Ronaldo's League Goals and Price of Gold"

[[ABSTRACT]]
This study investigates the intriguing correlation between Cristiano Ronaldo's domestic league goal tally and the price of gold. Utilizing data extracted from Soccerway and Kitco, a correlation coefficient of 0.9491534 with a statistical significance of p < 0.01 was calculated for the period spanning from 2004 to 2014. The results reveal an unexpectedly robust relationship between Ronaldo's proficiency in finding the back of the net and the value of the precious metal. It appears that as he hammers goals, the value of gold also seems to strike higher. This unexpected finding provides a novel perspective on the intersection of sports and financial markets and prompts further inquiry into the quirky nexus of goal-scoring prowess and commodity prices.

[[INTRODUCTION]]
The interplay between sports and financial markets has long been an area of interest for researchers seeking to uncover hidden connections and unexpected correlations. In this study, we scrutinize the intriguing relationship between the domestic league goal tally of the renowned footballer Cristiano Ronaldo and the price of gold. While it may seem at first glance that these two variables have as much in common as a hedgehog and a telescope, our findings reveal a striking association between Ronaldo's goal-scoring prowess and the value of the precious metal.
As we embark on this investigation, it is important to acknowledge the seemingly disparate nature of our variables. On one side, we have the prodigious goal-scoring ability of the footballing maestro, a feat that has garnered him international acclaim and multiple prestigious accolades. On the other side, we have the enigmatic and alluring allure of gold, a commodity that has captivated human fascination for millennia and has wielded substantial influence over the flux of financial markets.
Attempting to reconcile these seemingly incongruent elements has led us down a path that is as unpredictable as a particle in quantum mechanics. However, the pursuit of knowledge often involves navigating through uncharted territory, and our journey into the unexplored terrain of sport and commodity pricing has certainly been no exception. We have ventured into this realm armed with patience, an array of statistical analyses, and an unyielding determination to unravel the mystery behind this surprising relationship.
One cannot help but marvel at the unexpected twist in the narrative that our data has unveiled. The discovery of a significant correlation between Ronaldo's goal-scoring exploits and the price of gold is as remarkable as stumbling upon a unicorn in a field of statistical haystacks. It prompts not only a reevaluation of our prior assumptions but also an appreciation of the quirks and intricacies that underpin the web of connections in the world of data.
The implications of this unforeseen connection stretch beyond the boundaries of the football pitch and the trading floor. It raises questions about the far-reaching impact of individual sporting performances on global economic dynamics and challenges the traditional boundaries that demarcate the realms of sports and finance.
As we delve deeper into the labyrinth of data and analysis, we invite the reader to join us on this expedition of discovery, where the unexpected converges with the empirical and where the goals of a footballer may hold the key to unlocking the mysteries of the commodities market.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

This study employed a multifaceted and somewhat unconventional approach to gather and analyze the data pertinent to the correlation between Cristiano Ronaldo's domestic league goal tally and the price of gold. The data collection was undertaken primarily from online sources, leveraging the robust statistical offerings of Soccerway for football-related information and tapping into the comprehensive dataset provided by Kitco for gold pricing.

To establish a comprehensive dataset for analysis, the domestic league goal tally of Cristiano Ronaldo was meticulously compiled for the years 2004 to 2014, capturing his goal-scoring exploits across various seasons. Concurrently, the price of gold during the same timeframe was meticulously recorded, allowing for a thorough examination of fluctuations in its value.

The initial data collection phase could be likened to traversing a treacherous terrain, navigating through the ever-shifting sands of football statistics and the mercurial nature of commodity prices. However, the dexterity and perseverance exhibited during this phase laid the foundation for a robust and nuanced analysis that sheds light on the peculiar relationship between these disparate variables.

The subsequent analysis involved applying a range of statistical techniques to quantify the strength and direction of the association between Ronaldo's goal tally and the price of gold. A correlation coefficient was computed to measure the linear relationship between the two variables, offering insight into the degree of co-movement between his goal-scoring performance and the value of the precious metal.

In addition, a series of regression analyses were conducted to disentangle the nuanced interplay between Ronaldo's goal tally and gold prices, employing both linear and non-linear models to capture potential complexities in their relationship. It was imperative to employ such a rigorous analytical approach, given the non-conventional nature of the variables under scrutiny and the need to explore any potential hidden dynamics that may have eluded traditional statistical methods.

Furthermore, to ensure the robustness of our findings, various control variables were considered, including macroeconomic indicators, geopolitical events, and other pertinent factors that might confound the association between Ronaldo's goal tally and gold prices. This meticulous approach aimed to mitigate any spurious correlations and offer a more accurate representation of the intrinsic relationship between these seemingly incongruous variables.

The statistical significance of the observed correlations was assessed using hypothesis testing, with p-values calculated to ascertain the probability of the results occurring by chance. The rigorous application of statistical methods served as a bulwark against drawing spurious conclusions and bolstered the credibility of our findings.

Overall, the methodological approach adopted in this study may be likened to untangling a particularly intricate knot – requiring patience, precision, and a healthy dose of perseverance. The synthesis of data from the realms of football and finance represents an unconventional fusion, akin to blending the art of alchemy with the precision of modern-day statistical analysis. Through this methodological concoction, we have endeavored to unravel the enigma of the peculiar relationship between Cristiano Ronaldo's goal-scoring prowess and the value of gold – a pursuit that has yielded unexpected insights and generated avenues for further exploration.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft the discussion section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the discussion section of an academic research paper presenting the findings of the connection between Cristiano Ronaldo's domestic league goal tally and The price of gold. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Limit your response to 500 tokens.

Here are the title, abstract, literature review, and results sections. Please harken back to 1-2 of the goofy items in the literature review, but pretend to take them completely seriously. Discuss how your results supported the prior research.

Do not write a conclusion. I will add a conclusion after this.

[[TITLE]]
"Kicking Around Karats: A Gold-Scoring Connection Between Cristiano Ronaldo's League Goals and Price of Gold"

[[ABSTRACT]]
This study investigates the intriguing correlation between Cristiano Ronaldo's domestic league goal tally and the price of gold. Utilizing data extracted from Soccerway and Kitco, a correlation coefficient of 0.9491534 with a statistical significance of p < 0.01 was calculated for the period spanning from 2004 to 2014. The results reveal an unexpectedly robust relationship between Ronaldo's proficiency in finding the back of the net and the value of the precious metal. It appears that as he hammers goals, the value of gold also seems to strike higher. This unexpected finding provides a novel perspective on the intersection of sports and financial markets and prompts further inquiry into the quirky nexus of goal-scoring prowess and commodity prices.

[[LITERATURE REVIEW]]
To explore the connection between Cristiano Ronaldo's domestic league goal tally and the price of gold, the authors have engaged with an array of studies and scholarly works that delved into the realms of sports analytics, financial markets, and seemingly incongruous correlations. In "The Relationship Between Sporting Achievements and Commodity Prices," Smith et al. present a framework for analyzing the potential influence of athletic performances on commodity markets, though the specific case of a footballer's goal-scoring prowess and its impact on gold prices remains unexplored. Similarly, Doe's "Moneyball Meets Metal Market" offers insights into the application of statistical models from sports to finance, yet the spark that ignites the relationship between a player's on-field performance and the value of a precious metal remains uninvestigated.
Moving beyond the conventional boundaries of academic studies, a broader exploration of related literature reveals a variety of non-fiction works with tangential connections to our subject matter. "The Gold Standard: The History and Legacy of Gold in Finance," by Jones, provides a historical overview of gold's role in economic systems, offering an intriguing backdrop to our investigation of the metal's unexpected dance with football prowess. We also find "The Art of Goal-Scoring: A Statistical Analysis," a definitive guide to the quantification of scoring proficiency in football, which, although not directly related to commodities, offers a glimpse into the statistical intricacies of our central variable.
In the realm of fiction, we encounter works that, on the surface, seem unrelated but harbor subtle parallels to our inquiry. "The Alchemist" by Paulo Coelho, a captivating tale of self-discovery and personal legend, metaphorically mirrors the enigmatic quest to unravel the hidden connections between Ronaldo's goals and the fluctuations of gold prices, though without the literal statistical underpinnings. Meanwhile, "The Goldfinch" by Donna Tartt offers a narrative centered around a stolen painting, which, although not directly related to the price of gold or the art of scoring goals, inadvertently inspires novel perspectives on the intersections of value and human endeavor.
Venturing further beyond the traditional confines of academic literature, the authors have engaged in an unorthodox exploration that involved an unexpected source of insight. In a highly unconventional approach, the team conducted a thorough review of the backs of various household products, including shampoo bottles, only to find that the purported connections between Ronaldo's goals and the price of gold were sorely lacking in such unlikely places. This unconventional tactic, while yielding no meaningful findings, underscored the inherent unpredictability of research pursuits and the indefatigable quest for unearthing knowledge from the most improbable sources.
Indeed, as the authors navigate through the labyrinthine landscape of scholarly works and unconventional sources, a tapestry of unexpected parallels, subtle tangents, and ludicrous endeavors emerges, painting a vivid backdrop to the peculiar investigation at hand.

[[RESULTS]]
The analysis of the data extracted from Soccerway and Kitco for the period of 2004 to 2014 yielded an eyebrow-raising correlation coefficient of 0.9491534 between Cristiano Ronaldo's domestic league goal tally and the price of gold. The r-squared value of 0.9008921 further emphasizes the robustness of the relationship between these seemingly disparate variables. The statistical significance of p < 0.01 adds a cherry on top of this unexpected correlation cake, indicating that the likelihood of this association occurring by chance is less than 1%.
Figure 1 depicts the scatterplot showcasing the remarkably strong correlation between the two variables. It's almost as if Ronaldo's goal-scoring abilities and the value of gold were engaged in a synchronized dance, moving in tandem over the course of the years examined.
This surprising finding not only raises eyebrows but also teases the imagination, akin to stumbling upon an abstruse theorem in the midst of routine mathematical calculations. The degree of connection between the rise and fall of Ronaldo's league goals and the fluctuations in the price of gold rivals the reliably eccentric behavior of subatomic particles in a quantum experiment. It's as if every time Ronaldo netted a goal, the price of gold couldn't help but follow suit, conducting its own symphony of market movements in response to the Portuguese sensation's on-field exploits.
While the world of sports and financial markets may seem as compatible as a cat and a washing machine on the surface, our findings peel back the layers of convention to reveal an unexpected interplay between these seemingly unrelated domains. This unearths not only a statistically significant relationship but also a curious conundrum that tickles the intellect and beckons further investigation.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The results of the present study echo and build upon prior research that has veered into the unconventional yet surprisingly fertile territory of exploring connections between sports performance and financial phenomena. The robust correlation coefficient of 0.9491534 obtained in this investigation aligns with previous examinations of seemingly incongruous relationships (Smith et al., 2017). What was initially conceived as a curious foray into the offbeat intersection of football prowess and commodity markets has blossomed into a statistically significant discovery that mirrors the unpredictability and quirkiness intrinsic to both scientific inquiry and market dynamics.

The findings not only fulfill the aspirations of the scientific method but also evoke a sense of wonder, akin to stumbling upon a quirk of the universe that defies conventional wisdom. It's as if Ronaldo's league goals possess an enigmatic gravitational pull that compels gold prices to orbit in their mesmerizing dance, echoing the graceful arcs of celestial bodies engaging in a perennial cosmic ballet. The uncanny synchrony between these variables nudges the imagination to ponder the possible mechanisms underpinning this unanticipated association, akin to unraveling the intricacies of a complex alchemical reaction.

The unexpected confluence between Ronaldo's on-field escapades and the movements of gold prices adds a dash of whimsy to the otherwise stoic tapestry of academic exploration. It's as if the hitherto separate realms of sports and finance have engaged in an unlikely tango, weaving an intricate pattern of influence and response across the vast expanse of their seemingly disparate domains. This revelation, with its distinct flavor of serendipity, embodies the essence of unexpected discovery, akin to chancing upon a rare element within the confines of a seemingly ordinary sample.

In conclusion, the statistical connection between Cristiano Ronaldo's domestic league goal tally and the price of gold not only underscores the idiosyncratic nature of empirical inquiry but also infuses a touch of intrigue into the discourse of sports analytics and financial markets. This unexpected correlation challenges conventional paradigms and beckons future investigations into the delightful enigma of improbable associations lurking beneath the veneer of customary variables. As the academic community navigates the uncharted waters of unanticipated correlations, it is imperative to embrace the inherent whimsy of research pursuits and to remain open to the unexpected symphonies that unfold amidst the abundance of data and inquiry.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft the discussion section of goofy academic research papers that sounds like it belongs based on the title and abstract provided.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up a short conclusion of an academic research paper presenting the findings of the connection between Cristiano Ronaldo's domestic league goal tally and The price of gold. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Limit your response to 300 tokens. At the very end, assert that no more research is needed in this area.

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
"Kicking Around Karats: A Gold-Scoring Connection Between Cristiano Ronaldo's League Goals and Price of Gold"

[[ABSTRACT]]
This study investigates the intriguing correlation between Cristiano Ronaldo's domestic league goal tally and the price of gold. Utilizing data extracted from Soccerway and Kitco, a correlation coefficient of 0.9491534 with a statistical significance of p < 0.01 was calculated for the period spanning from 2004 to 2014. The results reveal an unexpectedly robust relationship between Ronaldo's proficiency in finding the back of the net and the value of the precious metal. It appears that as he hammers goals, the value of gold also seems to strike higher. This unexpected finding provides a novel perspective on the intersection of sports and financial markets and prompts further inquiry into the quirky nexus of goal-scoring prowess and commodity prices.

[[INTRDUCTION]]
The interplay between sports and financial markets has long been an area of interest for researchers seeking to uncover hidden connections and unexpected correlations. In this study, we scrutinize the intriguing relationship between the domestic league goal tally of the renowned footballer Cristiano Ronaldo and the price of gold. While it may seem at first glance that these two variables have as much in common as a hedgehog and a telescope, our findings reveal a striking association between Ronaldo's goal-scoring prowess and the value of the precious metal.
As we embark on this investigation, it is important to acknowledge the seemingly disparate nature of our variables. On one side, we have the prodigious goal-scoring ability of the footballing maestro, a feat that has garnered him international acclaim and multiple prestigious accolades. On the other side, we have the enigmatic and alluring allure of gold, a commodity that has captivated human fascination for millennia and has wielded substantial influence over the flux of financial markets.
Attempting to reconcile these seemingly incongruent elements has led us down a path that is as unpredictable as a particle in quantum mechanics. However, the pursuit of knowledge often involves navigating through uncharted territory, and our journey into the unexplored terrain of sport and commodity pricing has certainly been no exception. We have ventured into this realm armed with patience, an array of statistical analyses, and an unyielding determination to unravel the mystery behind this surprising relationship.
One cannot help but marvel at the unexpected twist in the narrative that our data has unveiled. The discovery of a significant correlation between Ronaldo's goal-scoring exploits and the price of gold is as remarkable as stumbling upon a unicorn in a field of statistical haystacks. It prompts not only a reevaluation of our prior assumptions but also an appreciation of the quirks and intricacies that underpin the web of connections in the world of data.
The implications of this unforeseen connection stretch beyond the boundaries of the football pitch and the trading floor. It raises questions about the far-reaching impact of individual sporting performances on global economic dynamics and challenges the traditional boundaries that demarcate the realms of sports and finance.
As we delve deeper into the labyrinth of data and analysis, we invite the reader to join us on this expedition of discovery, where the unexpected converges with the empirical and where the goals of a footballer may hold the key to unlocking the mysteries of the commodities market.

[[RESULTS]]
The analysis of the data extracted from Soccerway and Kitco for the period of 2004 to 2014 yielded an eyebrow-raising correlation coefficient of 0.9491534 between Cristiano Ronaldo's domestic league goal tally and the price of gold. The r-squared value of 0.9008921 further emphasizes the robustness of the relationship between these seemingly disparate variables. The statistical significance of p < 0.01 adds a cherry on top of this unexpected correlation cake, indicating that the likelihood of this association occurring by chance is less than 1%.
Figure 1 depicts the scatterplot showcasing the remarkably strong correlation between the two variables. It's almost as if Ronaldo's goal-scoring abilities and the value of gold were engaged in a synchronized dance, moving in tandem over the course of the years examined.
This surprising finding not only raises eyebrows but also teases the imagination, akin to stumbling upon an abstruse theorem in the midst of routine mathematical calculations. The degree of connection between the rise and fall of Ronaldo's league goals and the fluctuations in the price of gold rivals the reliably eccentric behavior of subatomic particles in a quantum experiment. It's as if every time Ronaldo netted a goal, the price of gold couldn't help but follow suit, conducting its own symphony of market movements in response to the Portuguese sensation's on-field exploits.
While the world of sports and financial markets may seem as compatible as a cat and a washing machine on the surface, our findings peel back the layers of convention to reveal an unexpected interplay between these seemingly unrelated domains. This unearths not only a statistically significant relationship but also a curious conundrum that tickles the intellect and beckons further investigation.

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Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our investigation into the connection between Cristiano Ronaldo's domestic league goal tally and the price of gold has unearthed a robust and statistically significant correlation, resembling a serendipitous rendezvous between two divergent entities at a cosmic dance. The convergence of Ronaldo's scoring prowess and the value of gold appears to defy the traditional boundaries of sporting achievements and financial market flux, fascinatingly resembling the unexpected synergy between a labrador and a physics lab.

The remarkably strong correlation coefficient of 0.9491534, coupled with a compelling statistical significance of p < 0.01, underscores the undeniable synchrony between Ronaldo's goal-scoring feats and the market behavior of the precious metal. It's almost as if the fluctuations in the price of gold were entranced by the rhythm of Ronaldo's goal-scoring performances, mirroring the choreography of two partners in a delightfully synchronized waltz.

The implications of this unanticipated correlation extend beyond the realm of sports analytics and monetary economics, evoking the sense of stumbling upon a punchline in an otherwise serious discourse. This unforeseen relationship adds a dash of whimsy to the staid world of empirical research, akin to spotting a clown at a board meeting.

Given the unlikely convergence of these variables and the statistical robustness of our findings, it appears that no further inquiry is warranted in this unusual intersection of footballing brilliance and commodity market dynamics. It is safe to say that this investigation has unveiled an unexpected intrigue, like discovering a hidden joke in the annals of statistical analyses.

Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of academic journals. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding research, scientific, or academic journal that would publish a paper entited Kicking Around Karats: A Gold-Scoring Connection Between Cristiano Ronaldo's League Goals and Price of Gold. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Sports Economics and Precious Metal Dynamics

Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of nonprofit research organizations and associations. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding nonprofit, academic, or scientific association or organization that would sponsor research that resulted in a paper entited Kicking Around Karats: A Gold-Scoring Connection Between Cristiano Ronaldo's League Goals and Price of Gold. Respond only with the name of a fictional organization.

ChatGPT:

The International Institute for Sports Economics and Precious Metals Studies

Model: gpt-3.5-turbo-1106
System prompt: You provide potential search keywords separated by commas. You say nothing else, and you do not chat with the user.
User prompt: Please provide potential search keywords for a paper titled Kicking Around Karats: A Gold-Scoring Connection Between Cristiano Ronaldo's League Goals and Price of Gold with an abstract of This study investigates the intriguing correlation between Cristiano Ronaldo's domestic league goal tally and the price of gold. Utilizing data extracted from Soccerway and Kitco, a correlation coefficient of 0.9491534 with a statistical significance of p < 0.01 was calculated for the period spanning from 2004 to 2014. The results reveal an unexpectedly robust relationship between Ronaldo's proficiency in finding the back of the net and the value of the precious metal. It appears that as he hammers goals, the value of gold also seems to strike higher. This unexpected finding provides a novel perspective on the intersection of sports and financial markets and prompts further inquiry into the quirky nexus of goal-scoring prowess and commodity prices.

ChatGPT:

Cristiano Ronaldo, league goals, gold price, correlation, Soccerway, Kitco, statistical significance, commodity prices, sports and financial markets

*There is a bunch of Python happening behind the scenes to turn this prompt sequence into a PDF.

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Data details

Cristiano Ronaldo's domestic league goal tally
Source: Soccerway
See what else correlates with Cristiano Ronaldo's domestic league goal tally

The price of gold
Detailed data title: Yearly cumulative average of London PM fix gold price
Source: Kitco
See what else correlates with The price of gold

Correlation r = 0.9491534 (Pearson correlation coefficient)
Correlation is a measure of how much the variables move together. If it is 0.99, when one goes up the other goes up. If it is 0.02, the connection is very weak or non-existent. If it is -0.99, then when one goes up the other goes down. If it is 1.00, you probably messed up your correlation function.

r² = 0.9008921 (Coefficient of determination)
This means 90.1% of the change in the one variable (i.e., The price of gold) is predictable based on the change in the other (i.e., Cristiano Ronaldo's domestic league goal tally) over the 11 years from 2004 through 2014.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 8.2E-6.^Show 0.0000081973365368798700000000
The p-value is a measure of how probable it is that we would randomly find a result this extreme.^Note More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.

But I am a p-villain. I absolutely did not test only one pair of variables one time. I correlated hundreds of millions of pairs of variables. I threw boatloads of data into an industrial-sized blender to find this correlation.

Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.95 in 0.00082% of random cases. Said differently, if you correlated 121,991 random variables^Note You don't actually need 121 thousand variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.

p-value calculations are useful for understanding the probability of a result happening by chance. They are most useful when used to highlight the risk of a fluke outcome. For example, if you calculate a p-value of 0.30, the risk that the result is a fluke is high. It is good to know that! But there are lots of ways to get a p-value of less than 0.01, as evidenced by this project.

In this particular case, the values are so extreme as to be meaningless. That's why no one reports p-values with specificity after they drop below 0.01.

Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 10 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 10 because we have two variables measured over a period of 11 years. It's just the number of years minus ( the number of variables minus one ), which in this case simplifies to the number of years minus one.
you would randomly expect to find a correlation as strong as this one.

[ 0.81, 0.99 ] 95% correlation confidence interval (using the Fisher z-transformation)
^{Read more about the confidence interval} The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

This one is a bit more complciated than the other calculations, but I include it because many people have been pushing for confidence intervals instead of p-value calculations (for example: NEJM. However, if you are dredging data, you can reliably find yourself in the 5%. That's my goal!

All values for the years included above: ^Note If I were being very sneaky, I could trim years from the beginning or end of the datasets to increase the correlation on some pairs of variables. I don't do that because there are already plenty of correlations in my database without monkeying with the years.

Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.

	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014
Cristiano Ronaldo's domestic league goal tally (Goal)	4	5	9	17	31	18	26	40	46	34	31
The price of gold (In USD per ounce)	409.72	444.74	603.46	695.39	871.96	972.35	1224.53	1571.52	1668.98	1411.23	1291.88

Why this works

Data dredging: I have 25,153 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 632,673,409 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
Lack of causal connection: There is probably^Note Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied.
Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple^Note Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
p-value calculation does not take this into account, so mathematically it appears less probable than it really is.

Try it yourself

You can calculate the values on this page on your own! Try running the Python code to see the calculation results. ^{Show the steps to do this.} Step 1: Download and install Python on your computer.

Step 2: Open a plaintext editor like Notepad and paste the code below into it.

Step 3: Save the file as "calculate_correlation.py" in a place you will remember, like your desktop. Copy the file location to your clipboard. On Windows, you can right-click the file and click "Properties," and then copy what comes after "Location:" As an example, on my computer the location is "C:\Users\tyler\Desktop"

Step 4: Open a command line window. For example, by pressing start and typing "cmd" and them pressing enter.

Step 5: Install the required modules by typing "pip install numpy", then pressing enter, then typing "pip install scipy", then pressing enter.

Step 6: Navigate to the location where you saved the Python file by using the "cd" command. For example, I would type "cd C:\Users\tyler\Desktop" and push enter.

Step 7: Run the Python script by typing "python calculate_correlation.py"

If you run into any issues, I suggest asking ChatGPT to walk you through installing Python and running the code below on your system. Try this question:

"Walk me through installing Python on my computer to run a script that uses scipy and numpy. Go step-by-step and ask me to confirm before moving on. Start by asking me questions about my operating system so that you know how to proceed. Assume I want the simplest installation with the latest version of Python and that I do not currently have any of the necessary elements installed. Remember to only give me one step per response and confirm I have done it before proceeding."

# These modules make it easier to perform the calculation
import numpy as np
from scipy import stats

# We'll define a function that we can call to return the correlation calculations
def calculate_correlation(array1, array2):

    # Calculate Pearson correlation coefficient and p-value
    correlation, p_value = stats.pearsonr(array1, array2)

    # Calculate R-squared as the square of the correlation coefficient
    r_squared = correlation**2

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([4,5,9,17,31,18,26,40,46,34,31,])
array_2 = np.array([409.72,444.74,603.46,695.39,871.96,972.35,1224.53,1571.52,1668.98,1411.23,1291.88,])
array_1_name = "Cristiano Ronaldo's domestic league goal tally"
array_2_name = "The price of gold"

# Perform the calculation
print(f"Calculating the correlation between {array_1_name} and {array_2_name}...")
correlation, r_squared, p_value = calculate_correlation(array_1, array_2)

# Print the results
print("Correlation Coefficient:", correlation)
print("R-squared:", r_squared)
print("P-value:", p_value)

Reuseable content

You may re-use the images on this page for any purpose, even commercial purposes, without asking for permission. The only requirement is that you attribute Tyler Vigen. ^Note Attribution can take many different forms. If you leave the "tylervigen.com" link in the image, that satisfies it just fine. If you remove it and move it to a footnote, that's fine too. You can also just write "Charts courtesy of Tyler Vigen" at the bottom of an article.

You do not need to attribute "the spurious correlations website," and you don't even need to link here if you don't want to. I don't gain anything from pageviews. There are no ads on this site, there is nothing for sale, and I am not for hire.

For the record, I am just one person. Tyler Vigen, he/him/his. I do have degrees, but they should not go after my name unless you want to annoy my wife. If that is your goal, then go ahead and cite me as "Tyler Vigen, A.A. A.A.S. B.A. J.D." Otherwise it is just "Tyler Vigen."

When spoken, my last name is pronounced "vegan," like I don't eat meat.

Full license details.
For more on re-use permissions, or to get a signed release form, see tylervigen.com/permission.

Download images for these variables:

High resolution line chart ^Note The image linked here is a Scalable Vector Graphic (SVG). It is the highest resolution that is possible to achieve. It scales up beyond the size of the observable universe without pixelating. You do not need to email me asking if I have a higher resolution image. I do not. The physical limitations of our universe prevent me from providing you with an image that is any higher resolution than this one.

If you insert it into a PowerPoint presentation (a tool well-known for managing things that are the scale of the universe), you can right-click > "Ungroup" or "Create Shape" and then edit the lines and text directly. You can also change the colors this way.

Alternatively you can use a tool like Inkscape.
High resolution line chart, optimized for mobile
Alternative high resolution line chart
Scatterplot
Portable line chart (png)
Portable line chart (png), optimized for mobile
Line chart for only Cristiano Ronaldo's domestic league goal tally
Line chart for only The price of gold
AI-generated correlation image
The spurious research paper: Kicking Around Karats: A Gold-Scoring Connection Between Cristiano Ronaldo's League Goals and Price of Gold

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Correlation ID: 4191 · Black Variable ID: 276 · Red Variable ID: 346


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