Spurious correlation #2,412 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Detroit Tigers' number of lost games in a specific season of the American League and the second variable is Total Runs Scored by Chicago Cubs Team in National League (Central and East Division). The chart goes from 1975 to 2022, 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 Detroit Tigers' number of lost games in a specific season of the American League and the second variable is Total Runs Scored by Chicago Cubs Team in National League (Central and East Division). The chart goes from 1975 to 2022, and the two variables track closely in value over that time.

Download png, svg

AI explanation

The Detroit Tigers' losing streak coincided with a spike in stray cat sightings in the Chicago area. These feline fans, seeking new homes after their team allegiances led to disappointment, found their way to the vicinity of the Chicago Cubs' stadium. Their presence seemed to bring good luck to the Cubs, as if they were the team's own furry, four-legged mascots. The increase in Total Runs Scored by the Chicago Cubs may have been a result of this unexpected, but undeniably adorable, form of infield purr-suasion. So, the next time the Tigers had a ruff game, the Cubs were feline fine and ready to pounce on the opportunity to pad their stats. Whisker you believe it or not, it seems like these meow-velous creatures were the catalyst for a paw-sitively delightful turn of events in the world of baseball. It's a true tail of how the game can be influenced by the most unexpected and a-meow-zing factors.

^{Show image generation prompt} Model: dalle-3
Prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3. Style: A surreal, vibrant painting depicting a cosmic baseball scene. Scene: In a universe where baseball defies reality, the Detroit Tigers' stadium is shrouded in an ominous, swirling vortex representing their losses, while the Chicago Cubs are surrounded by a radiant energy, their players hitting home runs with cosmic joy. The air crackles with a mystical link between the Tigers' struggles and the Cubs' offensive explosion, as if their fates are intertwined by the enigmatic force of the baseball cosmos. 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: Detroit Tigers' number of lost games in a specific season of the American League and Total Runs Scored by Chicago Cubs Team in National League (Central and East Division). 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: Low poly Cyber folk a funny image macro Hyper-realistic A Discovery magazine cover image
ChatGPT: A Discovery magazine cover image

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 Detroit Tigers' number of lost games in a specific season of the American League and Total Runs Scored by Chicago Cubs Team in National League (Central and East Division), in the following situation: Due to a little known fact about quantum entanglement, the Tigers' losing streak actually caused a disruption in the space-time continuum, leading to a temporary surge in the Cubs' offensive capabilities. It's like losing games created a rip in the fabric of the baseball universe, allowing the Cubs to tap into a parallel dimension where they were unstoppable at the plate. Plus, the cosmic sympathy for the Tigers' struggles somehow translated to cosmic glee for the Cubs, resulting in an inexplicable boost in their run production. It's a strange but true case of interleague entanglement!. Keep the description simple.
ChatGPT: In a surreal baseball universe, the Detroit Tigers' series of lost games is symbolized by a dark, swirling vortex of defeat hovering over their stadium. Meanwhile, the Chicago Cubs are portrayed as a team surrounded by a dazzling aura of energy, with their players smashing home runs and crossing home plate with smiles of cosmic joy. The air crackles with a strange connection between the Tigers' struggles and the Cubs' sudden offensive explosion, as if their fates are inexplicably intertwined by the mysteries of the baseball cosmos.

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: [ A Discovery magazine cover image ] and depicting this scene: In a surreal baseball universe, the Detroit Tigers' series of lost games is symbolized by a dark, swirling vortex of defeat hovering over their stadium. Meanwhile, the Chicago Cubs are portrayed as a team surrounded by a dazzling aura of energy, with their players smashing home runs and crossing home plate with smiles of cosmic joy. The air crackles with a strange connection between the Tigers' struggles and the Cubs' sudden offensive explosion, as if their fates are inexplicably intertwined by the mysteries of the baseball cosmos. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3. Style: A surreal, vibrant painting depicting a cosmic baseball scene. Scene: In a universe where baseball defies reality, the Detroit Tigers' stadium is shrouded in an ominous, swirling vortex representing their losses, while the Chicago Cubs are surrounded by a radiant energy, their players hitting home runs with cosmic joy. The air crackles with a mystical link between the Tigers' struggles and the Cubs' offensive explosion, as if their fates are intertwined by the enigmatic force of the baseball cosmos.

*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 increases in Detroit Tigers' number of lost games in a specific season of the American League positively influenced Total Runs Scored by Chicago Cubs Team in National League (Central and East Division).\Make it sound serious until the end.

AI academic paper

(Because p < 0.01)

Batting the Odds: The Correlation Between Detroit Tigers' Lost Games and Chicago Cubs' Total Runs Scored

The Journal of Sports Statistic Analysis and Probability

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 Detroit Tigers' number of lost games in a specific season of the American League and Total Runs Scored by Chicago Cubs Team in National League (Central and East Division). You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

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 name a few real TV shows that sound like they might be relevant to the topic that you watched as research.

Here is the title and abstract of the paper:
[[TITLE]]
Batting the Odds: The Correlation Between Detroit Tigers' Lost Games and Chicago Cubs' Total Runs Scored

[[ABSTRACT]]
This study examines the statistical relationship between the number of lost games by the Detroit Tigers in a specific season of the American League and the total runs scored by the Chicago Cubs Team in both the National League Central and East Divisions. Using data from Baseball Reference and Baseball Reference, our research team conducted a thorough analysis covering the years 1975 through 2022. A correlation coefficient of 0.6381028 and a p-value of less than 0.01 were identified, indicating a significant association between the two variables. To put it in baseball terms, the correlation was "pitcher-perfect" – strong and reliable, much like a seasoned Major League hurler. This study provides valuable insights into the interconnectedness of performance across different divisions, offering a home run for researchers interested in the dynamics of interleague play.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The world of baseball is replete with statistical analyses, each seeking to uncover the myriad connections and patterns that underlie the game's dynamic and often enigmatic nature. As researchers in the field, we are constantly reminded of the words of Yogi Berra, who famously quipped, "Baseball is 90% mental and the other half is physical." In this study, we delve into the statistical relationship between the number of lost games by the Detroit Tigers and the total runs scored by the Chicago Cubs, a journey that reveals both the serious and comical dimensions of this beloved sport.
Anecdotal evidence and popular belief often swirl around the idea that a team's ability to prevent losses is closely linked to the offensive prowess of another team, much like the way a catcher's mitt is paired with a pitcher's throw. And yet, despite the prevalence of such beliefs, empirical evidence to support or debunk this relationship has been as elusive as a knuckleball in the strike zone. As our investigation unfolds, we aim to bring clarity to this seemingly paradoxical connection, exploring the data with the precision of a seasoned umpire and the keen eye of a seasoned batter.
The correlation coefficient emerged from our rigorous analysis as a shocking revelation, akin to a slugger hitting a curveball out of the park. One might even say it was a "hit and run" in the realm of statistical relationships – surprising, but undeniably effective. Our findings present a compelling case for the interconnectedness of performance across different leagues, offering a new and intriguing perspective on the dynamics of baseball competition. In the words of Babe Ruth, "It's hard to beat a person who never gives up," and we, as researchers, have persisted in uncovering this association, undeterred by the occasional curveball or unexpected "foul play."

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

In "Smith et al.," the authors find a significant correlation between the number of lost games by the Detroit Tigers and the total runs scored by the Chicago Cubs. This study provides an important foundation for our research, aligning with our own findings, although lacking the delightful puns and baseball metaphors that we have sprinkled throughout our work.

Doe and Jones explore the relationship between baseball teams' performance metrics across different leagues. Their investigation sheds light on the intricate interplay between the outcomes of teams in disparate divisions, yet regrettably lacks the humor we aspire to infuse into our research.

Shifting our focus to broader baseball literature, "Moneyball" by Michael Lewis offers insightful perspectives on statistical analysis and its impact on baseball. Paralleling the innovative approach espoused in this acclaimed work, our research seeks to unravel the enigmatic connections between the Detroit Tigers' lost games and the Chicago Cubs' total runs scored - all while weaving in as many puns as a stand-up comedian at a baseball game.

In the domain of fictional accounts, "The Art of Fielding" by Chad Harbach and "The Natural" by Bernard Malamud resonate with the spirit of competition and the intricate web of relationships within baseball. While our research delves into the empirical realm, it strives to capture the essence of these compelling narratives through a lens that is as entertaining as a seventh-inning stretch.

In conducting thorough research, we have explored television shows such as "Brockmire" and "Pitch," which provide captivating portrayals of baseball dynamics. While these shows are not direct sources of data, they have certainly heightened our appreciation for the drama and humor inherent in the sport, inspiring our own blend of statistical analysis and whimsy.

As we venture further into our study, we aim to maintain the rigour of academic inquiry while injecting the wit and levity that define the spirit of baseball. With the baton of research in hand, we eagerly anticipate hitting it out of the park with this unconventional and illuminating exploration of the relationship between the Detroit Tigers' lost games and the Chicago Cubs' total runs scored.

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 Detroit Tigers' number of lost games in a specific season of the American League and Total Runs Scored by Chicago Cubs Team in National League (Central and East Division). You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Stay serious and dry most of the time, but then occasionally let your wit shine through.

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]]
Batting the Odds: The Correlation Between Detroit Tigers' Lost Games and Chicago Cubs' Total Runs Scored

[[ABSTRACT]]
This study examines the statistical relationship between the number of lost games by the Detroit Tigers in a specific season of the American League and the total runs scored by the Chicago Cubs Team in both the National League Central and East Divisions. Using data from Baseball Reference and Baseball Reference, our research team conducted a thorough analysis covering the years 1975 through 2022. A correlation coefficient of 0.6381028 and a p-value of less than 0.01 were identified, indicating a significant association between the two variables. To put it in baseball terms, the correlation was "pitcher-perfect" – strong and reliable, much like a seasoned Major League hurler. This study provides valuable insights into the interconnectedness of performance across different divisions, offering a home run for researchers interested in the dynamics of interleague play.

[[LITERATURE REVIEW]]
In "Smith et al.," the authors find a significant correlation between the number of lost games by the Detroit Tigers and the total runs scored by the Chicago Cubs. This study provides an important foundation for our research, aligning with our own findings, although lacking the delightful puns and baseball metaphors that we have sprinkled throughout our work.
Doe and Jones explore the relationship between baseball teams' performance metrics across different leagues. Their investigation sheds light on the intricate interplay between the outcomes of teams in disparate divisions, yet regrettably lacks the humor we aspire to infuse into our research.
Shifting our focus to broader baseball literature, "Moneyball" by Michael Lewis offers insightful perspectives on statistical analysis and its impact on baseball. Paralleling the innovative approach espoused in this acclaimed work, our research seeks to unravel the enigmatic connections between the Detroit Tigers' lost games and the Chicago Cubs' total runs scored - all while weaving in as many puns as a stand-up comedian at a baseball game.
In the domain of fictional accounts, "The Art of Fielding" by Chad Harbach and "The Natural" by Bernard Malamud resonate with the spirit of competition and the intricate web of relationships within baseball. While our research delves into the empirical realm, it strives to capture the essence of these compelling narratives through a lens that is as entertaining as a seventh-inning stretch.
In conducting thorough research, we have explored television shows such as "Brockmire" and "Pitch," which provide captivating portrayals of baseball dynamics. While these shows are not direct sources of data, they have certainly heightened our appreciation for the drama and humor inherent in the sport, inspiring our own blend of statistical analysis and whimsy.
As we venture further into our study, we aim to maintain the rigour of academic inquiry while injecting the wit and levity that define the spirit of baseball. With the baton of research in hand, we eagerly anticipate hitting it out of the park with this unconventional and illuminating exploration of the relationship between the Detroit Tigers' lost games and the Chicago Cubs' total runs scored.

[[RESULTS]]
The results of our investigation reveal a statistically significant correlation between the number of lost games by the Detroit Tigers in a specific season of the American League and the total runs scored by the Chicago Cubs Team in the National League (Central and East Divisions) for the years 1975 to 2022. The correlation coefficient of 0.6381028 indicates a moderately strong positive relationship between these two variables. In other words, as the Detroit Tigers experienced more losses in a season, the Chicago Cubs tended to score more runs – a connection as undeniable as a fly ball in the outfield. It seems that when the Tigers stumbled, the Cubs were there to pick up the pace, much like a reliable pinch hitter.
The r-squared value of 0.4071752 further supports the notion that changes in the number of lost games by the Detroit Tigers can be associated with variations in the total runs scored by the Chicago Cubs. This finding clarifies the puzzle of team performance in a way that would make even the most seasoned baseball analyst nod in approval. One might even say that our results hit a statistical "home run," capturing the essence of this relationship with the precision of a well-executed bunt.
The p-value of less than 0.01 adds weight to our findings, confirming the statistical significance of the correlation. This result is as clear as a well-played pop fly in a cloudless sky – it simply cannot be ignored. It appears that the connection between the performance of these two teams transcends mere chance, much like the enduring allure of ballpark hot dogs and seventh-inning stretches. Our research provides empirical evidence that underscores the interplay between losses and runs scored, offering a refreshing perspective on the intricacies of baseball dynamics.
In summary, the data obtained and analyzed in this study have elucidated a meaningful and noteworthy relationship between the performance of the Detroit Tigers and the Chicago Cubs, shedding light on the intriguing correlation between lost games and total runs scored. This discovery is akin to finding the perfect balance of salt and pepper for a well-seasoned dish, as it adds depth and flavor to the ongoing conversation surrounding the impact of team performance in baseball.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The findings of our study support and extend prior research that has explored the correlation between the performance of the Detroit Tigers and the Chicago Cubs. The significant correlation coefficient and p-value obtained in this investigation align with the work of Smith et al., reinforcing the notion of a robust connection between the number of lost games by the Detroit Tigers and the total runs scored by the Chicago Cubs. It seems that when one team tumbles in the standings, the other is poised to capitalize on the opportunity, not unlike a well-executed double play. This robust confirmation of the relationship between our variables is as reliable as a veteran outfielder tracking down a deep fly ball.

Moreover, the results of our study build upon the prior literature that delves into baseball dynamics, adding a layer of statistical rigor to the enthralling web of relationships within the sport. Our findings offer empirical evidence that captures the essence of the interplay between team performance metrics, enriching the ongoing conversation about the impact of losses and runs scored. The statistical significance revealed in this study is a grand slam for researchers and enthusiasts alike, underscoring the intricate dance of wins and losses in the game of baseball.

The moderately strong positive relationship identified in this investigation underscores the interconnectedness of performance metrics across different divisions and leagues, bringing to mind the harmonious rhythm of a well-coordinated infield turning a seamless double play. The r-squared value further solidifies the link between the Detroit Tigers' losses and the Chicago Cubs' runs scored, providing a compelling narrative that rivals the drama of a late-inning comeback.

Our research endeavor, while grounded in the principles of empirical inquiry, also aspires to capture the spirit of baseball through a lens of wit and levity. By infusing our work with baseball metaphors and puns, we endeavor to make statistical analysis as entertaining and engaging as a seventh-inning stretch. Just as a cleverly placed bunt can catch the defense off guard, our study seeks to surprise and delight with its unorthodox blend of statistical rigor and humor, akin to a well-timed comedic relief during an intense extra-inning game.

In conclusion, the correlation between the number of lost games by the Detroit Tigers and the total runs scored by the Chicago Cubs represents a rich tapestry of interconnectedness within the world of baseball. This study offers a fresh perspective on the dynamics of team performance, embellished with the humor and charm that make baseball a timeless American pastime. As we continue to explore the vast landscape of statistical and empirical research in sports, we remain committed to illuminating the hidden patterns and relationships that underpin the captivating drama of baseball.

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 Detroit Tigers' number of lost games in a specific season of the American League and Total Runs Scored by Chicago Cubs Team in National League (Central and East Division). You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Stay serious and dry most of the time, but then occasionally let your wit shine through.

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]]
Batting the Odds: The Correlation Between Detroit Tigers' Lost Games and Chicago Cubs' Total Runs Scored

[[ABSTRACT]]
This study examines the statistical relationship between the number of lost games by the Detroit Tigers in a specific season of the American League and the total runs scored by the Chicago Cubs Team in both the National League Central and East Divisions. Using data from Baseball Reference and Baseball Reference, our research team conducted a thorough analysis covering the years 1975 through 2022. A correlation coefficient of 0.6381028 and a p-value of less than 0.01 were identified, indicating a significant association between the two variables. To put it in baseball terms, the correlation was "pitcher-perfect" – strong and reliable, much like a seasoned Major League hurler. This study provides valuable insights into the interconnectedness of performance across different divisions, offering a home run for researchers interested in the dynamics of interleague play.

[[INTRDUCTION]]
The world of baseball is replete with statistical analyses, each seeking to uncover the myriad connections and patterns that underlie the game's dynamic and often enigmatic nature. As researchers in the field, we are constantly reminded of the words of Yogi Berra, who famously quipped, "Baseball is 90% mental and the other half is physical." In this study, we delve into the statistical relationship between the number of lost games by the Detroit Tigers and the total runs scored by the Chicago Cubs, a journey that reveals both the serious and comical dimensions of this beloved sport.
Anecdotal evidence and popular belief often swirl around the idea that a team's ability to prevent losses is closely linked to the offensive prowess of another team, much like the way a catcher's mitt is paired with a pitcher's throw. And yet, despite the prevalence of such beliefs, empirical evidence to support or debunk this relationship has been as elusive as a knuckleball in the strike zone. As our investigation unfolds, we aim to bring clarity to this seemingly paradoxical connection, exploring the data with the precision of a seasoned umpire and the keen eye of a seasoned batter.
The correlation coefficient emerged from our rigorous analysis as a shocking revelation, akin to a slugger hitting a curveball out of the park. One might even say it was a "hit and run" in the realm of statistical relationships – surprising, but undeniably effective. Our findings present a compelling case for the interconnectedness of performance across different leagues, offering a new and intriguing perspective on the dynamics of baseball competition. In the words of Babe Ruth, "It's hard to beat a person who never gives up," and we, as researchers, have persisted in uncovering this association, undeterred by the occasional curveball or unexpected "foul play."

[[RESULTS]]
The results of our investigation reveal a statistically significant correlation between the number of lost games by the Detroit Tigers in a specific season of the American League and the total runs scored by the Chicago Cubs Team in the National League (Central and East Divisions) for the years 1975 to 2022. The correlation coefficient of 0.6381028 indicates a moderately strong positive relationship between these two variables. In other words, as the Detroit Tigers experienced more losses in a season, the Chicago Cubs tended to score more runs – a connection as undeniable as a fly ball in the outfield. It seems that when the Tigers stumbled, the Cubs were there to pick up the pace, much like a reliable pinch hitter.
The r-squared value of 0.4071752 further supports the notion that changes in the number of lost games by the Detroit Tigers can be associated with variations in the total runs scored by the Chicago Cubs. This finding clarifies the puzzle of team performance in a way that would make even the most seasoned baseball analyst nod in approval. One might even say that our results hit a statistical "home run," capturing the essence of this relationship with the precision of a well-executed bunt.
The p-value of less than 0.01 adds weight to our findings, confirming the statistical significance of the correlation. This result is as clear as a well-played pop fly in a cloudless sky – it simply cannot be ignored. It appears that the connection between the performance of these two teams transcends mere chance, much like the enduring allure of ballpark hot dogs and seventh-inning stretches. Our research provides empirical evidence that underscores the interplay between losses and runs scored, offering a refreshing perspective on the intricacies of baseball dynamics.
In summary, the data obtained and analyzed in this study have elucidated a meaningful and noteworthy relationship between the performance of the Detroit Tigers and the Chicago Cubs, shedding light on the intriguing correlation between lost games and total runs scored. This discovery is akin to finding the perfect balance of salt and pepper for a well-seasoned dish, as it adds depth and flavor to the ongoing conversation surrounding the impact of team performance in baseball.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our study has provided compelling evidence of a significant correlation between the number of lost games by the Detroit Tigers and the total runs scored by the Chicago Cubs Team in the National League (Central and East Divisions) from 1975 to 2022. This correlation, akin to the bond between a pitcher and their favorite glove, was found to be "pitcher-perfect" – strong, reliable, and ready for the big leagues. As the Tigers stumbled, the Cubs were there to pick up the pace, demonstrating a connection as robust as a well-hit line drive.

Our findings, much like a well-executed bunt, provide a new and refreshing perspective on the dynamics of baseball competition, shedding light on the interconnectedness of performance across different leagues. It's as if we've uncovered the perfect blend of salt and pepper, adding depth and flavor to the ongoing conversation regarding team performance in baseball, much like the perfect condiments for a ballpark hot dog.

Given our compelling results, it is safe to say that no more research is needed in this area. The evidence has been presented as decisively as a strike three call, and the statistical romance between the Tigers' losses and the Cubs' runs scored has been revealed. We leave this topic with a parting dad joke: "Why don't baseball players join unions? Because they don't like to be called out on strikes!" Thank you, and until the next inning of statistical discovery!

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 Batting the Odds: The Correlation Between Detroit Tigers' Lost Games and Chicago Cubs' Total Runs Scored. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Sports Statistic Analysis and Probability

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 Batting the Odds: The Correlation Between Detroit Tigers' Lost Games and Chicago Cubs' Total Runs Scored. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Quirky Sports Analytics Research

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 Batting the Odds: The Correlation Between Detroit Tigers' Lost Games and Chicago Cubs' Total Runs Scored with an abstract of This study examines the statistical relationship between the number of lost games by the Detroit Tigers in a specific season of the American League and the total runs scored by the Chicago Cubs Team in both the National League Central and East Divisions. Using data from Baseball Reference and Baseball Reference, our research team conducted a thorough analysis covering the years 1975 through 2022. A correlation coefficient of 0.6381028 and a p-value of less than 0.01 were identified, indicating a significant association between the two variables. To put it in baseball terms, the correlation was "pitcher-perfect" – strong and reliable, much like a seasoned Major League hurler. This study provides valuable insights into the interconnectedness of performance across different divisions, offering a home run for researchers interested in the dynamics of interleague play.

ChatGPT:

Detroit Tigers, lost games, Chicago Cubs, total runs scored, American League, National League, Baseball Reference, correlation coefficient, p-value, interleague play

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

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Data details

Detroit Tigers' number of lost games in a specific season of the American League
Source: Baseball Reference
See what else correlates with Detroit Tigers' number of lost games in a specific season of the American League

Total Runs Scored by Chicago Cubs Team in National League (Central and East Division)
Source: Baseball Reference
See what else correlates with Total Runs Scored by Chicago Cubs Team in National League (Central and East Division)

Correlation r = 0.6381028 (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 = 0.4071752 (Coefficient of determination)
This means 40.7% of the change in the one variable (i.e., Total Runs Scored by Chicago Cubs Team in National League (Central and East Division)) is predictable based on the change in the other (i.e., Detroit Tigers' number of lost games in a specific season of the American League) over the 48 years from 1975 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 1.07E-6.^Show 0.0000010672959643281098000000
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 0.64 in 0.000107% of random cases. Said differently, if you correlated 936,947 random variables^Note You don't actually need 936 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 47 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 47 because we have two variables measured over a period of 48 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.

[ 0.43, 0.78 ] 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.

	1975	1976	1977	1978	1979	1980	1981	1982	1983	1984	1985	1986	1987	1988	1989	1990	1991	1992	1993	1994	1995	1996	1997	1998	1999	2000	2001	2002	2003	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021	2022
Detroit Tigers' number of lost games in a specific season of the American League (Games Lost)	102	87	88	76	76	78	49	79	70	58	77	75	64	74	103	83	78	87	77	62	84	109	83	97	92	83	96	106	119	90	91	67	74	88	77	81	67	74	69	72	87	75	98	98	114	35	85	96
Total Runs Scored by Chicago Cubs Team in National League (Central and East Division) (Runs Scored)	712	611	692	664	706	614	370	676	701	762	686	680	720	660	702	690	695	593	738	500	693	772	687	831	747	764	777	706	724	789	703	716	752	855	707	685	654	613	602	614	689	808	822	761	814	265	705	657

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.
Confounding variable: 2020 is particularly different from the other years on this graph. Confounding variables (like global pandemics) will cause two variables to look connected when in fact a "sneaky third" variable is influencing both of them behind the scenes.

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([102,87,88,76,76,78,49,79,70,58,77,75,64,74,103,83,78,87,77,62,84,109,83,97,92,83,96,106,119,90,91,67,74,88,77,81,67,74,69,72,87,75,98,98,114,35,85,96,])
array_2 = np.array([712,611,692,664,706,614,370,676,701,762,686,680,720,660,702,690,695,593,738,500,693,772,687,831,747,764,777,706,724,789,703,716,752,855,707,685,654,613,602,614,689,808,822,761,814,265,705,657,])
array_1_name = "Detroit Tigers' number of lost games in a specific season of the American League"
array_2_name = "Total Runs Scored by Chicago Cubs Team in National League (Central and East Division)"

# 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 Detroit Tigers' number of lost games in a specific season of the American League
Line chart for only Total Runs Scored by Chicago Cubs Team in National League (Central and East Division)
AI-generated correlation image
The spurious research paper: Batting the Odds: The Correlation Between Detroit Tigers' Lost Games and Chicago Cubs' Total Runs Scored

View another random correlation

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Correlation ID: 2412 · Black Variable ID: 369 · Red Variable ID: 206


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