Update analyze-baseball-stats-with-pandas-and-matplotlib.mdx

Author: sonnynomnom

projects/analyze-baseball-stats-with-pandas-and-matplotlib/analyze-baseball-stats-with-pandas-and-matplotlib.mdx

@@ -22,12 +22,12 @@ tags:
 
 ## Introduction
 
+> It's about getting things down to one number. Using stats to reread them, we'll find the value of players that nobody else can see. - Peter Brand, Moneyball
+
 In the early 2000s, the [Oakland A's](https://en.wikipedia.org/wiki/Athletics_(baseball)) changed baseball forever. 
 
 As seen in the movie _Moneyball_ (2011), general manager Billy Bean and advisor Peter Brand, used a new strategy of data analysis to find players that were hidden gems. By diving deep into often overlooked statistics, like on-base percentage, the team was able to sign undervalued players and make a deep run into the 2002 playoffs on a shoestring budget.
 
-> It's about getting things down to one number. Using stats to reread them, we'll find the value of players that nobody else can see. - Peter Brand, Moneyball
-
 The success of the A's helped usher in an era of advanced data analysis in baseball. Every year, more and more stats about the game are being collected, and every club is hungry for a team of statisticians to help them crack the code.
 
 In this project tutorial, we're going to step into the shoes of Bean and Brand and use [Python](https://codedex.io/python), [Pandas](https://codedex.io/pandas), and [Matplotlib](https://codedex.io/matplotlib) to explore the world of baseball! ⚾️