I created this dataset as a first project with several goals, including becoming more familiar with SQL, populating a dataset, and just as an overall learning experience.

I used the VNL 2024 data because I like volleyball and thought this would be fun to work with, and also give me some insight into the highest level of the sport.

You can read my write-up on this dataset here.

In 2024, approximately *** million people participated in volleyball in the United States, representing an increase on the previous year, which had over *** million participants.

Context

As a fan of volleyball I wanted to make a data science project around it, but couldn't find any datasets available, so I made one on my own. I hope that every volleyball fan will be able to use this data for themselves!

Content

The data was collected from the official PlusLiga's website, and contains matches played from seasons 2008/2009 to 2022/2023. Some team names were changing as the years went by, but here they were all combined. For example: Grupa Azoty ZAKSA Kędzierzyn-Koźle and ZAKSA Kędzierzyn-Koźle were both renamed to ZAKSA Kędzierzyn-Koźle Information about past team names came from each team's wiki page

Column names explanation (T1 refers to Team_1 and T2 refers to Team_2): - Date - Date and time at which the match was played - Team_1 and Team_2 - Name of the teams - Score - Number of sets won - Sum - Total number of points gained - BP - Points scored in a counterattack on your own serve - Ratio - Points gained - points lost - Srv_Sum - Number of all serves - Srv_Err - Number of serve errors - Srv_Ace - Number of points gained from an ace - Srv_Eff - Serve effectiveness in % - Rec_Sum - Number of all serve receptions - Rec_Err - Number of serve reception errors - Rec_Pos - Percent of postive serve receptions - Rec_Perf - Percent of perfect serve receptions - Att_Sum - Total number of attacks - Att_Err - Number of attack errors - Att_Blk - Number of attacks that were blocked - Att_Kill - Total number of points scored in attack - Att_Kill_Perc - Percent of attacks that scored a point - Att_Eff - Attack effectiveness in % - Blk_Sum - Number of points gained with a block - Blk_As - Number of blocks that allow a team which was blocking to do a counterattack - Winner - 0 if Team 1 won, 1 if Team 2 won

Dataset contains game level data from the 2025 NCAA Division 1 men's volleyball season. Each row represents one game with match outcomes coded as win or loss, measured against 19 performance variables including kills, errors, assists, service aces, and other key performance indicators.

Hi!

Inspired by @yeganehbavafa 's Men's VNL 2023 dataset, I've created this new one for the Women's VNL 2024 using the same source (volleyballworld.com) for personal purposes. Now, here it is for everybody who find it useful.

I encourage all to visit @yeganehbavafa 's dataset for a much detailed explanation of the data.

ABSTRACT Introduction Non-intelligent factors include learning habits, motivation, interest, emotion, attitude, and student characteristics. Many sports practices have demonstrated that creating excellent athletic performance and winning intense competition depends on various factors. Among them, physical quality is the physiological and material basis to ensure the quality of exercise. Movement technique is the essential condition. However, non-Intelligent factors are the internal motivators for both to function. Objective Analyze the non-Intelligent factors that affect the performance of volleyball players. Methods Several volleyball players were selected as research objects. The non-Intelligent factors that affect volleyball performance are analyzed by questionnaire survey and experimental method. Finally, this paper uses mathematical statistics to analyze the experimental data. Results Volleyball players are easily disturbed by external factors. These non-Intelligent factors can easily lead to large fluctuations in the athlete’s psychology. These reasons will affect the stability of volleyball players’ serving skills. Conclusion The non-Intelligent factors that affect the performance of volleyball players are the proficiency of serving technique, the degree of psychological relaxation, and the ability of emotional control. Level of evidence II; Therapeutic studies - investigation of treatment results.

Volleyball Action Finder

## Overview

Volleyball Action Finder is a dataset for object detection tasks - it contains Actions annotations for 868 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

Financial overview and grant giving statistics of Volleyball Academy of America

Comprehensive YouTube channel statistics for Spike Volleyball , featuring 173,000 subscribers and 40,699,526 total views. This dataset includes detailed performance metrics such as subscriber growth, video views, engagement rates, and estimated revenue. The channel operates in the Gaming category and is based in DE. Track 976 videos with daily and monthly performance data, including view counts, subscriber changes, and earnings estimates. Analyze growth trends, engagement patterns, and compare performance against similar channels in the same category.

The number of volleyball players in U.S. high schools has grown steadily over the past decade. In the 2023-24 school year, the number of participants exceeded *** thousand, with the vast majority of players being girls.

Between November 2023 and November 2024, approximately ****** people took part in Volleyball in England. This marked an increase from the previous period, during which ****** individuals participated.

Comprehensive YouTube channel statistics for Beach Volleyball World, featuring 526,000 subscribers and 505,659,489 total views. This dataset includes detailed performance metrics such as subscriber growth, video views, engagement rates, and estimated revenue. The channel operates in the Lifestyle category and is based in CH. Track 4,629 videos with daily and monthly performance data, including view counts, subscriber changes, and earnings estimates. Analyze growth trends, engagement patterns, and compare performance against similar channels in the same category.

Financial overview and grant giving statistics of Carolina One Volleyball

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

Financial overview and grant giving statistics of Beach Cities Volleyball Club

Big Time Hoops is a dedicated sports analytics company that provides in-depth statistics and data on basketball teams and players. Founded on the principles of innovation and expertise, the company has established itself as a go-to source for basketball enthusiasts and professionals alike. With a strong focus on accuracy and reliability, Big Time Hoops aggregates and analyzes vast amounts of data to deliver actionable insights that help teams and individuals gain a competitive edge.

By leveraging advanced data harvesting techniques and expert analysis, Big Time Hoops creates a vast repository of basketball data that spans from player performance metrics to game-winning statistics. The company's dedication to harnessing the power of data has led to the development of proprietary algorithms and modeling techniques that enable users to gain nuanced understanding of the game. With Big Time Hoops, users can tap into a vast pool of knowledge to inform their decisions, whether it's for fantasy leagues, coaching, or simply staying ahead of the competition.

Comprehensive YouTube channel statistics for Mr Love Volleyball, featuring 664,000 subscribers and 460,651,256 total views. This dataset includes detailed performance metrics such as subscriber growth, video views, engagement rates, and estimated revenue. The channel operates in the Sports category and is based in IN. Track 2,398 videos with daily and monthly performance data, including view counts, subscriber changes, and earnings estimates. Analyze growth trends, engagement patterns, and compare performance against similar channels in the same category.

Comprehensive YouTube channel statistics for Epic Volleyball, featuring 921,000 subscribers and 452,862,780 total views. This dataset includes detailed performance metrics such as subscriber growth, video views, engagement rates, and estimated revenue. The channel operates in the Lifestyle category and is based in UA. Track 2,181 videos with daily and monthly performance data, including view counts, subscriber changes, and earnings estimates. Analyze growth trends, engagement patterns, and compare performance against similar channels in the same category.

In 2024, court volleyball was the sport's most popular variety in the United States, with approximately *** million participants. This was more than double the number of grass volleyball participants in the same year.

Dataset

This dataset was created by Zoe Huertas

Contents