Pancake Analytics LLC

As the Super Bowl concludes, a flood of content creators armed with free access to Market Movers will inundate the digital sphere, offering their perspectives on Patrick Mahomes’ cards, often delving into charts and graphs they may not fully grasp. In this cacophony, akin to proclaiming it’s raining during a downpour, I aim to leverage my extensive experience as a data scientist to provide you with sophisticated analytical solutions for your sports card collecting endeavors.

Drawing from my previous work, particularly in analyzing Steve Aoki’s influence on markets such as Star Wars, Marvel, and Lorcana trading cards using causal impact time-series methodology, I intend to employ a similar approach. In this analysis, I will delve into the past three years of data pertaining to championship winners and losers in football, baseball, and basketball. Through this, I aim to uncover the causal impact of winning or losing on the grandest stage of these sports.

Let me refresh everyone on the approach and why it’s more accurate than the pre versus post an event approach these content creators show.

A causal impact time series analysis offers a more accurate assessment compared to a simple pre and post comparison for several reasons, particularly in the context of market analysis:

1. Dynamic Effects: A causal impact model accounts for dynamic effects, recognizing that changes in one variable can have a ripple effect on others. This is crucial in market analysis, where numerous factors can influence outcomes.
2. Control Variables: By incorporating control variables, a causal impact model can isolate the specific impact of an event or intervention, filtering out the noise from other concurrent changes in the market environment. This helps in attributing changes accurately.
3. Counterfactual Estimation: The model estimates what would have happened in the absence of the event, providing a baseline for comparison. This is essential in markets where multiple factors can influence outcomes, making it difficult to assess the true impact of a single event.
4. Statistical Rigor: Causal impact models are based on rigorous statistical methods, such as Bayesian structural time series models. These methods provide more reliable estimates and account for uncertainty in the data, offering a more robust analysis.
5. Long-Term Effects: Unlike a simple pre and post comparison, a causal impact analysis can assess the long-term effects of an event, capturing how the market adapts and changes over time in response to the event.

In summary, a causal impact time series analysis provides a more nuanced and accurate understanding of how events impact markets, making it a valuable tool for businesses and investors seeking to make informed decisions.

Before delving into the specifics of individual sports and players, the results of my analysis reveal some compelling insights. On average, sports championship winners experience a modest 3% increase in trading card prices. Conversely, if a player’s team loses the championship, there is an average 5% decrease in trading card value. These averages, however, will vary based on the sport and the individual player. To illustrate, I will start by discussing the impact of the World Series on trading card values.

Overall, winning or losing the World Series doesn’t show a significant difference in the impact on trading card values. Both the winner and the loser of the World Series observe, on average, a modest 1% increase in trading card value. This suggests that, in the context of the World Series, the outcome doesn’t have a substantial effect on the trading card market for the players involved.

Winning an NBA championship has the most significant impact on trading card values among the sports analyzed. On average, winning a championship results in a 3% increase in trading card values. However, if a player’s team loses the championship, there is an average decrease of 9% in trading card value. This 12 percentage point swing highlights the substantial influence of NBA championship outcomes on the trading card market for the players involved.

The impact of the NFL championship tells a particularly intriguing story, especially for individual players. Despite the perception of a lack of parity in Super Bowl winners, the data reveals interesting trends. On average, Super Bowl winners see a 4% increase in trading card values. Surprisingly, Super Bowl losers experience an even greater increase, with an average of 7%. This dynamic suggests that the Super Bowl outcome may have a more nuanced effect on trading card values than initially perceived. Next, I will delve into the details of individual player impacts, starting with baseball.

let’s dive into the 2021 Major League Baseball season and the Atlanta Braves’ victory in the World Series. Ronald Acuna Jr.’s injury was a significant moment, and it’s interesting to consider his collectibility, especially among casual fans.

When analyzing the broader sports card market, it’s crucial to consider the perspectives of both casual fans and collectors. In this context, Ronald Acuna Jr.’s cards experienced only a 1% decrease, contrasting with the 4.7% increase seen across the entire Baseball CardLadder index during the same period. This underperformance by Acuna may reflect the strong prospect focus within baseball card collecting and the enduring popularity of vintage trading cards.

Here’s the math behind the 1% decline :

In my analysis, I began by forecasting the value of Acuna baseball cards before the World Series. The next step was to apply exponential smoothing to these forecasted values. Then, I applied the same exponential smoothing (with a damping factor of 0.9) to the actual values. This smoothing process helps to control for all the outside factors beyond the World Series that could affect the card values. Finally, I compared the actual smoothed value to the forecasted smoothed value to assess the accuracy of the forecast.

To calculate the percent difference between a smoothed actual value of 16220.41 and a smoothed forecasted value of 16409.04, I used the formula below:

Plugging in the values:

So, the percent difference, or the impact of the world series win on Ronald Acuna Jr’s baseball cards, between the smoothed actual value of 16220.41 and the smoothed forecasted value of 16409.04 is 1.15%.

Now, let’s apply the same approach to the World Series runner-up of the 2021 Major League Baseball season: Corey Seager of the Texas Rangers. The impact on Corey Seager baseball cards was also roughly 1%.

It’s interesting to note that both the World Series winner and loser under indexed against the entire baseball market. This suggests a strong indicator of the collectability of favorite teams and vintage baseball cards, which continue to hold significant appeal in the sports card market.

To calculate the percent difference between the smoothed actual value of 9231.07 and the smoothed forecast value of 9105.30, I used the following formula:

Plugging in the values:

Now let’s jump forward to the 2022 Major League baseball season and discuss the impact of the world series for a Houston Astros star and a Philadelphia Philles star.

Now, we’re delving into the realm of those who assert the blanket statement that after a championship, all cards go down in value, with the peak being the series before the World Series.

In the case of Yordan Alvarez, a player from the 2022 World Series-winning Houston Astros, his baseball cards experienced a decline of 12%. This decline challenges the notion of a universal trend and highlights the complexities of the sports card market, where individual player performance and market dynamics play significant roles in determining card values.

Here’s the math behind the 12% decrease :

To calculate the percent difference between a smoothed actual value of 5550.97 and a smoothed forecasted value of 6328, I used the formula:

Plugging in the values:

So, the percent difference between the smoothed actual value of 5550.97 and the smoothed forecasted value of 6328 is 12.27% , in other words the impact of winning the world series on Alvarez cards was a 12.27% decrease.

In a surprising turn of events, the runner-up of the 2022 World Series, Bryce Harper of the Philadelphia Phillies, saw a remarkable 11% increase in his baseball card values. This increase far exceeded the performance of the World Series winner and the entire Baseball CardLadder index during the same post-period.

Harper’s cards’ unexpected surge highlights the unpredictable nature of the sports card market, where individual player performances and market dynamics can lead to outcomes that defy conventional wisdom.

Here’s the math behind the 11% increase :

To calculate the percent difference between a smoothed actual value of 1040.49 and a smoothed forecasted value of 939.57, you can use the formula:

Plugging in the values:

So, the percent difference between the smoothed actual value of 1040.49 and the smoothed forecasted value of 939.57 is 10.74%. Usually when a world series or other sports championship ends, there’s a lot more supply and potentially in the case of Bryce Harper potentially a couple of high end cards found a new home.

Now, let’s revisit Corey Seager and analyze his 2023 World Series win and the impact on his baseball card value. Seager not only outperformed his 2021 World Series loss, but he also overindexed against the CardLadder Baseball index and the 2023 World Series loser. Corey Seager’s baseball cards saw a remarkable 26% increase in value, showcasing the strong influence of recent performance and championship victories on player collectibility in the sports card market.

The outcome of the-causal impact time-series model reveals that Corbin Carroll, a player from the Arizona Diamondbacks and a participant in the 2023 World Series, experienced a 2% decrease in his baseball card value. This analysis underscores the importance of advanced modeling techniques in understanding and predicting trends in the sports card market, where even slight fluctuations can have significant implications for collectors and investors.

Here’s the math behind the 2% decline:

To calculate the percent difference between a smoothed actual value of 4043.24 and a smoothed forecasted value of 4116.46, I used the below formula:

Plugging in the values:

So, in the case of Corbin Carroll, the percent difference between the smoothed actual value of 4043.24 and the smoothed forecasted value of 4116.46 is a decrease of 1.78%. Now let’s shift from baseball cards to basketball cards.

Let’s begin with the 2021 NBA season, where the Milwaukee Bucks clinched the NBA championship led by their superstar, Giannis Antetokounmpo. Using the causal impact time-series method, it was observed that Giannis’s basketball cards experienced a 2% decline in value following their championship victory. This illustrates the intriguing dynamics at play in the sports card market, where even major achievements like winning a championship can have varying impacts on card values.

Here’s the math behind the 2% decrease :

Devin Booker was on the losing side of the 2021 NBA championship, and his basketball card value experienced a 3% decline, which is a percentage point worse than Giannis Antetokounmpo’s decrease. This indicates that while both players saw a decrease in value, the losing player experienced a larger decline.

Here’s the math behind the 3% decrease:

Stephen Curry, a key player for the 2022 NBA champion Golden State Warriors, experienced a 3% increase in his basketball card values following the NBA championship. This increase is noteworthy, especially when contrasted with the broader trend in the basketball CardLadder index, which saw a 4% decrease in value over the same time period. Curry’s performance and status as a champion clearly had a positive impact on his card values, showcasing the influence of individual player achievements on the sports card market.

Here’s the math behind the 3%:

Now, let’s examine one of the most significant negative impacts on basketball card values, which occurred with Jayson Tatum of the Boston Celtics, the losing team of the 2022 NBA Championship. Tatum’s basketball card value plummeted by 20% since the championship series, significantly underindexing against the basketball Cardladder index. This stark decline underscores the market’s sensitivity to performance outcomes, where players on losing teams can experience substantial decreases in card values despite their individual talents and achievements.

Here’s the math behind the 20% loss:

Now, let’s conclude our deep dive into basketball cards with the 2023 NBA Season, starting with the NBA Champion Denver Nuggets and their star player, Nikola Jokic. According to the causal impact time-series analysis, Jokic’s cards experienced a 5% decrease in value. This decline, despite his team’s championship victory, highlights the nuanced nature of the sports card market, where various factors can influence player card values, even after major achievements like winning a championship.

Here’s the math behind the 5% decrease :

In contrast, the runner-up of the 2023 NBA Championship, Jimmy Butler, experienced a significant 12% decrease in his basketball card value. Butler’s decrease in value was notably larger than Jokic’s and also under indexed compared to the overall CardLadder Basketball card index. This disparity highlights the market’s sensitivity to performance outcomes and the differential impact on player card values based on team success.

Here’s the math behind the 12% decrease :

Now I’ll tackle football card impact from the Super Bowl.

Given the limited post-Super Bowl data for the 2023 season, I’ll focus on the results of the 2021 and 2022 Super Bowls. Matthew Stafford of the L.A. Rams, after winning the Super Bowl, observed a 1% decrease in his football card value. This minor decrease underscores the varied impacts of championship wins on player card values and highlights the complexities of the sports card market. Do keep in mind the entire Football CardLadder index was down nearly a percentage point during this same time period.

Here’s the math behind the 1% decrease :

Joe Burrow of the Cincinnati Bengals experienced a notable 10% increase in his football card value. Despite the Bengals losing the Super Bowl, this outcome demonstrates the ongoing speculation and excitement among football card collectors. It highlights the market’s focus on individual player performance and potential future success, even in the face of team losses in major events like the Super Bowl.

Here’s the math behind the 10% increase :

When examining the details of football card values, it’s important to consider a caveat regarding the 10% increase observed in Joe Burrow’s case. This increase may be more about scale than a significant change in value. When a number is low, even slight shifts can result in large percentage changes. This is a crucial nuance that many content creators often leave out or may not be aware of.

As a collector, sports card investor, or flipper, I advise you to tread cautiously with content creators who showcase lines and graphs in market update videos. Many of these creators may not have the career experience or expertise to provide accurate and meaningful insights into these graphs. It’s important to conduct your own research and consider multiple factors before making any decisions based on such information.

Turning to the 2022 NFL Season, we find the champion Patrick Mahomes of the Kansas City Chiefs. Mahomes saw a 4% increase in his football card value since winning the Super Bowl. The output of the causal impact time-series suggests that Mahomes’ cards would have been down at least 4% more from the beginning of the season if he hadn’t won the Super Bowl. This insight highlights the impact of major achievements, like winning the Super Bowl, on player card values and the market’s perception of success in the NFL. Pair this tidbit with the fact of the Football CardLadder index being down 2% over the same time period, the 4% increase for Mahomes is a bigger win.

Here’s the math behind the 4% :

For our final player deep dive, let’s analyze the impact of the Super Bowl loss on Jalen Hurts of the Philadelphia Eagles’ football card value. Hurts’s football card value experienced a 6% loss, underperforming both against Mahomes’s 4% increase and the 2% decrease of the Football CardLadder index. This highlights the market’s reaction to team performance and individual player outcomes, showing how Super Bowl results can significantly influence card values in the sports card market.

Here’s the math behind the 6% loss :

Thank you for joining me on this in-depth analysis and for investing in empowering your collection with data science and advanced analytics. The key takeaways from this analysis are clear: winning a sports championship tends to drive a 3% increase in sports card values, while losing a sports championship leads to a 5% decrease in sports card values.

However, it’s important to note that in any analysis of the broader sports card market, there will always be outliers and niche individual sports card examples that defy these trends. This underscores the complexity and dynamic nature of the sports card market, where various factors can influence card values beyond just the outcome of a championship.

Please use the interactive charts and table to conduct your own analysis if needed. Updating the filters to these charts and table will not update the aforementioned parts of this analysis. So feel free, you won’t break anything.

Champions Table All Sports – Players Individual Lift