NCAA college football games always attract millions of television viewers in the United States and the games of the 2024 regular season were no different. The game between Georgia and Texas, broadcast on ABC and ESPN on December 7, 2024, was watched by an average of 16.6 million viewers.

Our NFL Data product offers extensive access to historic and current National Football League statistics and results, available in multiple formats. Whether you're a sports analyst, data scientist, fantasy football enthusiast, or a developer building sports-related apps, this dataset provides everything you need to dive deep into NFL performance insights.

Key Benefits:

Comprehensive Coverage: Includes historic and real-time data on NFL stats, game results, team performance, player metrics, and more.

Multiple Formats: Datasets are available in various formats (CSV, JSON, XML) for easy integration into your tools and applications.

User-Friendly Access: Whether you are an advanced analyst or a beginner, you can easily access and manipulate data to suit your needs.

Free Trial: Explore the full range of data with our free trial before committing, ensuring the product meets your expectations.

Customizable: Filter and download only the data you need, tailored to specific seasons, teams, or players.

API Access: Developers can integrate real-time NFL data into their apps with API support, allowing seamless updates and user engagement.

Use Cases:

Fantasy Football Players: Use the data to analyze player performance, helping to draft winning teams and make better game-day decisions.

Sports Analysts: Dive deep into historical and current NFL stats for research, articles, and game predictions.

Developers: Build custom sports apps and dashboards by integrating NFL data directly through API access.

Betting & Prediction Models: Use data to create accurate predictions for NFL games, helping sportsbooks and bettors alike.

Media Outlets: Enhance game previews, post-game analysis, and highlight reels with accurate, detailed NFL stats.

Our NFL Data product ensures you have the most reliable, up-to-date information to drive your projects, whether it's enhancing user experiences, creating predictive models, or simply enjoying in-depth football analysis.

Football Game

## Overview

Football Game is a dataset for object detection tasks - it contains Object Detection HCxS annotations for 785 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).

The National Football League (NFL) is a professional football league in the United States. The league was founded in 1920 as the American Professional Football Association and played its inaugural season with eleven teams. Nowadays, the NFL comprises 32 teams spread out over two conferences, the National Football Conference (NFC) and the American Football Conference (AFC), that each consist of four divisions. In a September 2020 survey in the United States, 12 percent of male respondents stated that they attended about one game per season on average.

The NFL is one of the most widely televised sporting leagues in the world. The average television viewership of a regular season NFL game in 2024 was calculated to be 17.5 million. Attendance In addition to this record-breaking TV viewership, the NFL attracts thousands of fans to the stadiums each week to see their favorite teams in action. The NFL has consistently been the major American sports league with the highest average attendance, with an average of almost 70 thousand people attending each game in the 2023 season. Moreover, during the 2024 regular season, the average total home attendance per team across the entire NFL was calculated to be 588,088. The franchise with the highest total attendance for its eight regular-season home games was the Dallas Cowboys, perhaps in part to their comparatively reasonably priced tickets, costing nearly 117 U.S. dollars on average, just less than the average ticket price across the NFL at 120 U.S. dollars per ticket. Best players Since 1957, the Associated Press NFL Most Valuable Player Award has been given to the NFL player considered to have been the most outstanding during the season. Since the award's introduction, Peyton Manning has received the award the greatest number of times during his career, closely followed by Aaron Rodgers, who has received the award on four occasions. One other potential indicator of the success of an NFL player is their annual salary. The highest-paid NFL player in 2024 was Dak Prescott, quarterback for the Dallas Cowboys, who earned 86.3 million U.S. dollars from salary and bonuses and 14 million U.S. dollars from endorsement deals during the 2024 season.

FPM outperforms the baseline prediction based on win-loss standings every season in our dataset. The overall accuracy of our system is 63.4%.

Here are a few use cases for this project:

1. Player Performance Analysis: Use the "Football Player Tracker" to analyze individual player performances during football games. This could include tracking their movements, analyzing their tactical decisions, or assessing the overall efficiency of the team's formations and strategies.

2. Automated Sports Coverage: Employ this computer vision model for automated, real-time sports-broadcast coverage. It could provide detailed tracking information about players to sports commentators to enhance their analysis during live broadcasts.

3. Learning and Coaching: Coaches can use this model to educate players by visually demonstrating their movements and activities on the field. This could be incredibly beneficial for training sessions, providing a unique method to improve player's understanding of their role and performance.

4. Sports Betting: Sports betting companies could use this model to provide real-time data and analytics to their customers, enhancing their betting experience by supplying in-depth information about player performances and behaviors.

5. Game Strategy Development: Use the data gathered by this computer vision model to assist in the creation or tweaking of a team's game strategies. By understanding which player/classes are performing well in certain roles, the coaching staff can better plan their strategies for future games.

Total attendance at National Football League (NFL) games reached about 18.63 million fans across the regular season in 2024. This represented a slight decrease over the previous year's figure of approximately 18.9 million spectators. Attendance at NFL games Over the last few years the total attendance at regular season games of the National Football League has consistently been at more than 18 million per season. The NFL is composed of 32 teams and each team plays a minimum of eight home games during the regular season for a total of 256 games per season. The average attendance at National Football League games was at around 69,500 in the 2023 season. Dallas Cowboys drew record crowds In 2023, the Dallas Cowboys drew the most spectators to their home games with a total attendance of more than 748 thousand. The Cowboys also had the highest average attendance that season with around 93,600 people attending each home game. The average price for a ticket to an NFL game was at 120.94 U.S. dollars in 2023. On average, tickets to Las Vegas Raiders games were the most expensive (168.83 U.S. dollars), while tickets for Arizona Cardinals games were the least expensive, with an average price of 98.54 U.S. dollars.

Significance codes: ***: p < .001, **: p < .01, *: p < .05.

The difference represents . Significance codes: ***: p < .001, **: p < .01, *: p < .05. The home team advantage is also presented.

A total of 9.17 million viewers tuned in on ABC to watch the college football matchup between FSU and LSU on September 3, 2023. This made it the most-viewed college football week one game of the 2023 season.

The tactical formation has been shown to influence the match performance of professional soccer players. This study aimed to examine the effects of in-game changes in tactical formation on match performance and to analyze coach-specific differences. We investigated three consecutive seasons of an elite team in the German Bundesliga which were managed by three different coaches, respectively. For every season, the formation changes that occurred during games were recorded. The match performance was measured on a team level using the variables “goals,” “chances,” and “scoring zone” entries (≙successful attacking sequence) for the own/opposing team. Non-parametric tests were used to compare the 10 min before with the 10 min after the formation change, as well as games with and without formation change. In the 10 min after the formation change, the team achieved more goals/chances/scoring zone entries than in the 10 min before the formation change (mean ES = 0.52). Similarly, the team conceded fewer opposing goals/chances/scoring zone entries in the 10 min after the formation change (mean ES = 0.35). Furthermore, the results indicate that the success of the respective formation change was dependent on the responsible coach. Depending on the season, the extent of the impacts varied (season 1: mean ES = 0.71; season 2: mean ES = 0.26; and season 3: mean ES = 0.22). Over all three seasons, the formation changes had a positive effect on the match performance of the analyzed team, highlighting their importance in professional soccer. Depending on the season, formation changes had varying impacts on the performance, indicating coach-specific differences. Therefore, the quality of the formation changes of the different coaches varied. The provided information can support coaches in understanding the effects of their in-game decisions.

This study explored factors that influence actual playing time by comparing the Chinese Super League (CSL) and English Premier League (EPL). Eighteen factors were classified into anthropogenic and non-anthropogenic factors. Fifty CSL matches (season 2019) and 50 EPL matches (season 2019–2020) were analyzed. An independent sample t-test with effect size (Cohen’s d) at a 95% confidence interval was used to evaluate differences in the influencing factors between the CSL and EPL. Two multiple linear regression models regarding the CSL and EPL were conducted to compare the influencing factors’ impact on actual playing time. The results showed that the average actual playing time (p 

This dataset is about books and is filtered where the book is The people's game : football, state and society in East Germany, featuring 7 columns including author, BNB id, book, book publisher, and ISBN. The preview is ordered by publication date (descending).

Analysis of ‘NFL scores and betting data’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/tobycrabtree/nfl-scores-and-betting-data on 12 November 2021.

--- Dataset description provided by original source is as follows ---

Context

National Football League historic game and betting info

Content

National Football League (NFL) game results since 1966 with betting odds information since 1979. Dataset was created from a variety of sources including games and scores from a variety of public websites such as ESPN, NFL.com, and Pro Football Reference. Weather information is from NOAA data with NFLweather.com a good cross reference. Betting data was used from http://www.repole.com/sun4cast/data.html for 1978-2013 seasons. Pro-football-reference.com data was then cross referenced for betting lines and odds as well as weather data. From 2013 on betting data reflects lines available at sportsline.com.

Acknowledgements

Helpful sites with interest in football and sports betting include:

https://github.com/fivethirtyeight/nfl-elo-game

http://www.repole.com/sun4cast/data.html

https://www.pro-football-reference.com/

http://www.espn.com/nfl/

http://www.nflweather.com/

http://www.noaa.gov/weather

https://www.sportsline.com/

https://github.com/jp-wright/nfl_betting_market_analysis

http://www.aussportsbetting.com/data/historical-nfl-results-and-odds-data/

Inspiration

Can you build a predictive model to better predict NFL game outcomes and identify successful betting strategies?

--- Original source retains full ownership of the source dataset ---

All-time San Marino's international football matches, San Marino national football team records and stats, biggest victory, heaviest defeat

The file football.gml contains the network of American football gamesbetween Division IA colleges during regular season Fall 2000, as compiledby M. Girvan and M. Newman. The nodes have values that indicate to whichconferences they belong. The values are as follows: 0 = Atlantic Coast1 = Big East2 = Big Ten3 = Big Twelve4 = Conference USA5 = Independents6 = Mid-American7 = Mountain West8 = Pacific Ten9 = Southeastern10 = Sun Belt11 = Western Athletic If you make use of these data, please cite M. Girvan and M. E. J. Newman,Community structure in social and biological networks,Proc. Natl. Acad. Sci. USA 99, 7821-7826 (2002).

Overview

• Introduction
• Object Classes
  • Football
  • Player

Introduction

This dataset is designed to facilitate the detection of objects in football match images. The two main classes are:

• Football: The ball used in play.
• Player: Individuals participating in the game, including referees.

Object Classes

Football

Description

The football is a spherical object, typically small and distinctive from the players and field. It may be found on the grass or in the air during active play.

Instructions

• Position: Locate the spherical object identifiable as the football, present on the field or in the air.
• Spatial Extent: Encapsulate the entire visible section of the ball within a bounding box.
• Visibility: Do not label if obstructed beyond recognition.

Player

Description

Players are human figures engaged in the game, typically wearing sports uniforms. This category includes referees who are dressed differently but are part of the on-field activity.

Instructions

• Position: Identify all human figures present on the field, including those in motion or standing still.
• Spatial Extent: Include the entire human figure from head to toe if visible, or up to the visible portion if partially obscured by other players or objects.
• Disambiguation: Identify referees by their distinct uniform, generally contrasting with team colors, and include them in annotations as players too.
• Visibility: Do not annotate if a player is obscured in a manner where identification is unclear.

This study explored factors that influence actual playing time by comparing the Chinese Super League (CSL) and English Premier League (EPL). Eighteen factors were classified into anthropogenic and non-anthropogenic factors. Fifty CSL matches (season 2019) and 50 EPL matches (season 2019–2020) were analyzed. An independent sample t-test with effect size (Cohen’s d) at a 95% confidence interval was used to evaluate differences in the influencing factors between the CSL and EPL. Two multiple linear regression models regarding the CSL and EPL were conducted to compare the influencing factors’ impact on actual playing time. The results showed that the average actual playing time (p 

The average per game attendance during the 2024 NFL regular season was at 69,520. The Dallas Cowboys had the highest average attendance of all the 32 NFL teams, averaging 92,972 for their nine regular-season home games in 2024. Cowboys in a league of their own Since moving to AT&T Stadium in 2009, the Dallas Cowboys have led the NFL in average regular-season home attendance for over a decade. During that time, the Cowboys have averaged more than 90,000 per home game, well above the league average of around 69,000. At the other end of the rankings, the Chicago Bears had the lowest average regular-season home attendance in 2024. Touchdown in London for the NFL Regular-season NFL games have been played every year in London since 2007, and the attendances for these games are included in the figures for the designated home teams. The NFL London games have been a huge success: attendance of over 60,000 was achieved for all the games held in 2024. Since the games in London started in 2007, all 32 franchises playing in the NFL have played in the UK's capital, with the Green Bay Packers being the last franchise to play there for the first time in 2022.