LeBron James — the unanimous 2016 Finals MVP

LeBron James was unanimously named MVP of the NBA Finals for the third time following the Cleveland Cavaliers win over the Golden State Warriors this June. Here’s why:

Over the seven-game series, James averaged 29.7 points, 11.3 rebounds and 8.9 assists with an effective field goal percentage of 53.3. He also led all players in all 5 major statistical categories, the first player to do so in NBA history. He became the third player to record a triple-double in Game 7 of the Finals, joining Jerry West in 1969 and James Worthy in 1988.

James is now 4-2 all time in Game 7s and 2-0 when the ultimate game comes in the NBA Finals.

Tableau

I used Tableau to show why Kentucky men’s basketball finished 27-9 last year.

Out of the 18 games they played, they outscored their opponents in two-pointers, two-pointers attempted, three-pointers, and three-pointers attempted to give them an overall higher amount of points scored throughout the season.

The one area where Kentucky and their opponents were almost even was in three-pointers but Kentucky beats them out by 32 making their three-point average 39.2% to their opponents 33.8%.

Even though Kentucky’s three-point average was close, the fact that their two-pointer percentage beat their opponents out by nearly 10%.

Not considering free-throws, because their percentage was only one percent above their opponents, I believe that Kentucky’s success with their two-pointers is what put them ahead last season.

Source: http://www.sports-reference.com/cbb/schools/kentucky/2016.html

Georgia gymnastics struggled on beam last year

Since I covered gymnastics last year and I spent a lot of the season writing about how bad Georgia was on beam, I decided to look further into the data that shows this.

This graph shows how Georgia’s team score was ultimately determined by its beam score. At first this seems obvious because a team score is the sum off the four events scores, but what is interesting is that the vault, bars and floor totals hardly fluctuate throughout the year. This means that whether Georgia won or lost each meet was almost always a product of whether or not the team did decent on beam. With the line graphs of the scores from every event, you can see how the beam score is the one that is usually bringing down the overall total. Apart from one meet of bad bars, no other event shows this type of fluctuation. It’s cool to look back at it this way because I felt like every week I was writing about beam. Georgia either had a disaster on beam and lost, or it somehow pulled it together on beam and it won. This graph shows that fairly simply.

Next, I looked at how Georgia’s rough year on beam compared to other teams. This graph shows all the Division I teams that averaged above a 48.5 on beam. The bars that are colored in show the teams that qualified for the NCAA championship. This is an interesting way to look at how far behind Georgia was from other top programs throughout the year on the event. This shows how abnormal it was that Georgia was able to qualify for the national championship despite such a rough showing all year on beam

Module 4: Using statistics effectively

Introduction:

This is going to be a little different as Prof. Herndon and I are partnering on offering an in-depth stats boot camp for Grady students. We aim to engage you with understanding how vital numbers are to modern work in any kind of journalism, including sports. We’ll have a couple of sessions on stats, sports, and understanding how to use the former to tell stories about the latter.

Learning objectives:

Understanding how to use data and statistics to tell sports stories
Understanding the basic principles of statistics in the context of journalism

Steps to completion:

Background:

Tableau information TK
Silver Chapter 3, “All I care about are Ws and Ls”
Class session with Jacob Pomrenke of SABR and Dash Davidson with Tableau, Thursday, Sept. 22
Basic Statistics for Journalists (9:05-9:55am or 10:10-11am Friday, Sept. 23)
Extra Credit: Intermediate statistics for journalists, (12:20-1:10pm Friday, Sept. 23)

Reflective:

Using a stats database like http://stats.nba.com, come up with a defensible story about why a player, a team or a game finished the way it did during the previous season. Use a Tableau graphic to illustrate your point. Post your story to Module 4 by Sept. 26.

Exploratory

Team budgets due Sept. 19
Team conferences during class Sept. 20
Revised story memo due Sept. 23
OPTIONAL: Develop a plan for using advanced statistics for your team or personal package.