Motivation

Division 1 NCAA women’s volleyball is the highest level of collegiate competition for women’s volleyball in the United States. With well over 300 teams compete at the Division 1 level, there is fierce competition each year as only 64 teams make the post-season Volleyball Championship. The division demands high-level athletic performances, teamwork, and strategic game play from a variety of aspects. With each team having their own strengths and weaknesses, there is no exception of exciting matchups and and shocking results.

In volleyball, a kill is awarded to a player any time their attack is unreturnable by the opposition because it is the direct cause of the opponent not returning the ball. An assist is awarded when a set, pass, or dig to a teammate results in that teammate attacking the ball for a kill.

Data

The data set contains 334 rows and 14 columns. Each row represents a team at the NCAA Division 1 level from the 2022-2023 season.

• Team college of the volleyball team
• Conference conference to which the team belongs
• region region to which the team belongs
• aces_per_set the average amount of balls served that directly lead to a point not including errors by the opponent per set
• assists_per_set the average amount of sets, passes, or digs to a teammate that directly result in a kill per set
• team_attacks_per_set the average amount of times the ball is sent to the other team’s court per set
• blocks_per_set the average amount of times the ball is blocked from being hit on to the teams side per set
• digs_per_set average amount of times the ball is passed by a player successfully after an opponents attack per set
• hitting_pctg total team kills minus team hitting errors all divided by total attempts
• kills_per_set average amount of hits that directly result in a point per set
• opp_hitting_pctg the average hitting percentage of the teams opponent per set
• W the amount of team wins for the season
• L the amount of team losses for the season
• win_loss_pctg the amount of total wins divided by the total matches of the season

Questions

• What variables are most highly correlated with win/loss percentage of a team?
• How are assists and kills related?
• What model is best for predicting win/loss percentage?

References

NCAA - Women’s Volleyball

https://www.ncaa.com/stats/volleyball-women/d1

Acknowlegement

Foto von Vince Fleming auf Unsplash

https://www.fivb.org/Vis2009/Images/GetImage.asmx?No=81682&type=Press" width="1080">

Context

I’m from Brazil, the country of soccer, we’re famous for being the only country to win five FIFA World Cups. But another sport that is very popular here is volleyball, I’m a volleyball maniac, I started to play when I was 10 and never stopped, I even tried to go pro, but my height didn’t allow me.

I’ve started an engineering course and there I’ve became a Data Science maniac. Then an idea came to my mind why not play with both my passions? That is the story behind this dataset.

Content

This dataset contains information about men and women stats from FIBV 2020 Preliminary Round, the data is subdivided into specific datasets. Those are: Best Attackers, Best Blockers, Best Diggers, Best Receivers, Best Scorers, Best Servers and Best Setters, which of them with their on specialized stats.

Acknowledgements

I wouldn’t be here without the help of other people materials; I would like to acknowledge Luis Felipe Bueno for his Medium Article that was my starting point to make this dataset. Luis Article

Inspiration

I hope to help fellow Volleyball and Data Science maniacs like me to have a little fun, so I would like to see the answers for some questions: 1. Based in this dataset what would be the Men and Women Dream Teams? * 2. Which are the 5 countries with more players within the highest ranks?

*obs: (2 - Setters, 4 - Hitters, 2 - Opposite Hitters, 4 – Middle Blockers, 2 – Liberos)