2022 RB Analytical Review part 3

Author: Billy Jones

Introduction 

Welcome back to the third installment of my blog series where I perform an analytical review for running back fantasy performance from 2022. In this blog, we will be exploring the relationships between data points that commonsense logic would assume are closely linked, such as rushing yards and rushing touchdowns, receptions and receiving yards, and more. We will be using visualization tools to help us determine if these relationships actually exist and if there are any outliers or anomalies in the data. From there I will comment on what this might mean about their performance in 2023.

I'm particularly excited about this blog, as we start to get a little deeper into the realm of data science-y things. This blog touches on topics of correlation and anomalies, and how they can be used when evaluating player performance. These are easy concepts and tools which help towards a comprehensive understanding of what happened in 2022 and what could be in 2023. Let's get started!

Statistics 101

In today’s blog we will be adding two new data science terms into our study, correlation, outlier, and anomaly. 

Correlation is a statistic that describes the relationship between data points. It is expressed as a number between -1 and 1, with 1 being a perfect positive relationship, -1 being a perfect negative relationship, and 0 indicating no relationship between the data points. A positive correlation means that as one data point increases, the other data point tends to increase. A negative correlation is the opposite whereas one data point increases, the other tends to decrease.

An outlier is an observation in a data set that lies far away from other values. Outliers can have a significant impact on the results of statistical analyses and can sometimes be indicative of measurement error or data entry errors (or football fluky results). An anomaly, on the other hand, is an observation that deviates significantly from the expected pattern in a data set. Outliers and anomalies are often interchanged but for this blog outliers will be based upon general observations whereas anomalies will be based upon statistical measures.

Ground Rules

Read post #1 in series for ground rules explanation.

Visualizations and Analysis

With the admin stuff now out of the way, let’s get into analyzing some relationships. 

In this analysis, we are examining some commonly assumed relationships in offensive production. Although we acknowledge that these are simplified views of offensive production, our scatterplots provide clear indications that these assumptions hold true. They also help us understand which players are most/least efficient with their touches.

Analysis: Upon examining the data, it's evident that there is a strong relationship between the number of receptions and yards gained. This finding may seem obvious, but it's important to note that there are no significant outliers in the yards-to-receptions ratio. I do want to highlight we should be targeting players above the line as they are able to do more with less volume. One player who surprised me by falling below the line was Austin Ekeler. This raises concerns about his potential performance in the new Kellen Moore offense, especially if he must take a reduction in volume. Despite finishing as the RB1 in 2022, Ekeler will not be my top choice for RB1 entering 2023.

Analysis: The correlation between rushing attempts and yards is once again not surprising, but there are some noteworthy takeaways from the data. Breece Hall consistently appears on the high side of the line, indicating that he was highly efficient both on the ground and as a receiver. It's worth noting that in previous years, Derrick Henry would have been a strong outlier due to his exceptional yards per attempt. However, in 2023, Henry's yards per attempt moved back towards traditional running back ratios, suggesting that he may be showing signs of slowing down. Despite this, Henry maintained his league-leading rushing workload in 2022 which made him a valuable fantasy producer.

Analysis: In this visual, we're examining the correlation between total touchdowns and total yards. Although the relationship between the two is still positive, it's considerably weaker than the previous two correlations we analyzed. While this could be attributed to factors such as good/bad luck or the offensive role of the player, we're looking to lower the value of players whose fantasy points were primarily driven by touchdowns and increase the value of those whose points were driven by yardage output. Given that touchdowns are somewhat random, this approach allows us to identify players on either side of the central line whose value should be increased or decreased accordingly.

Analysis: In our last correlation analysis shows an almost zero correlation coefficient between rushing attempts and receptions. It’s a bit of an “amoeba”. While a near 0 correlation might suggest that this variable is not useful for analysis, the inclusion of our scoring tiers reveals some valuable insights. In the visual we can observe distinct "bands" of players, with RB1s primarily falling on the upper right band, RB2s in the middle band, and RB3+s in the bottom left band. This illustrates that a player's success isn't solely determined by their touch count, but rather the type of touches they receive. When searching for a potential RB1 candidate, it's crucial to target players who possess the desired offensive touch profile. This would ideally include roughly 18+ carries per week, OR 12+ carries and 4+ receptions per week. In this visual, Javonte Williams stood out as someone who is on the cusp of our desired profile.

Conclusion

To summarize, our examination of the correlation between various stats has provided us with valuable insights into the offensive output of different running backs from 2022. This marks the end of our mini-series on 2022 running back fantasy performance. Moving forward, we're excited to delve deeper into other position groups, so stay tuned for next week's post, as we continue this analytical series with a focus on the tight end position!

*This blog post was enabled by ChatGPT. The text was generated by me, and the content is my own, but some sentences and wording were provided by the model. I take full responsibility for all information produced in this blog. More information about OpenAI and their technology can be found at https://openai.com.*