Collection of college statistics, draft team information, and NFL career statistics for every quarterback drafted since the year 2000 until the 2024 offseason. Originally created in an attempt to train a neural network that predicts NFL success level of a quarterback at the time of being drafted.

This database was only made possible by the many NFL stat keeping websites I discovered in the data collection process:

• Draft Data: https://www.drafthistory.com/index.php/positions/qb
• College Statistics: https://www.sports-reference.com/cfb
• Physical Combine Measurements: https://www.pro-football-reference.com
• Assorted Missing Stats: https://www.walterfootball.com
• NCAA Conference Strength Metric: https://www.jhowell.net/cf/
• Assorted Missing QB Stats: https://www.ncaa.com and respective school websites
• NFL Team Records: https://www.jt-sw.com/football/
• Coach Tenure: https://www.pro-football-history.com/
• NFL Stats: https://www.stathead.com/ (paid subscription)

Database Feature Glossary

year-drafted: The year drafted into the NFL

qb-num-picked: The number taken relative to other quarterbacks (1 = first quarterback selected, 2 = second selected, etc.)

rd-picked: The round of the NFL draft the player was selected

num-picked: The overall draft position the player was drafted at

name: Name of player

height (in): Player height in inches as reported at the NFL Draft

weight (lbs): Player weight in pounds as reported at the NFL Draft

nfl-team: The NFL team that drafted the player

coach-tenure: The number of years the head coach had been employed by the team that drafted the player at the time of the draft

drafted-team-winpr: The win percentage in the most recent season of the team that drafted the player at the time of drafting

drafted_team_ppg_rk: The points per game ranking in the most recent season of the team that drafted the player at the time of drafting

college: The college the player attended at the time of drafting

conf: The conference of the college the player participated in

conf-str: The calculated strength of the conference in the final year the quarterback played (reference link above)

p-cmp: Pass completions in college career

p-att: Pass attempts in college career

cmp-pct: Pass completion percentage in college career

p-yds: Total pass yards in college career

p-ypa: Passing yards per attempt in college career

p-adj-ypa: Adjusted passing yards per attempt in college career

p-td: Passing touchdowns in college career

int: Interceptions in college career

rate: Passing efficiency rating (reference link above)

r-att: Rushing attempt count in college career

r-yds: Rushing yards in college career

r-avg: Average yards per rush in college career

r-tds: Rushing touchdowns in college career

nfl-starts: Total number of started games in the NFL

nfl-wins: Total games won in the NFL

nfl-losses: Total games lost in the NFL

nfl-ties: Total games tied in the NFL

nfl-winpr: Total win percentage as a starter in the NFL

nfl-qbr: Quarterback rating in the NFL

nfl-cmp: Total pass completions in the NFL

nfl-att: Total pass attempts in the NFL

nfl-inc: Total incompletions thrown in the NFL

nfl-comp%: Career completion percentage in the NFL

nfl-yds: Total passing yards in the NFL

nfl-tds: Total passing touchdowns in the NFL

nfl-int: Total interceptions thrown in the NFL

nfl-pick6: Number of interceptions thrown that were returned for touchdowns in the NFL

nfl-int%: Percentage of NFL throws that were interceptions

nfl-sack%: Percentage of NFL passing plays the player gave up a sack

nfl-y/a: Yards per passing attempt in the NFL

nfl-ay/a: Adjusted yards per passing attempt in the NFL

nfl-any/a: Adjusted net yards per passing attempt in the NFL

nfl-y/c: Passing yards per completion in the NFL

nfl-y/g: Passing yards per game in the NFL

nfl-succ%: Passing success rate in the NFL (reference link above)

nfl-4qc: 4th quarter comebacks completed in the NFL

nfl-gwd: Game winning drives completed in the NFL

Access comprehensive NFL data, including historic stats and results, with datasets available in various formats. Perfect for sports analysts and enthusiasts, this product offers a free trial to explore detailed National Football League data for insights and research.

This dataset contains following data: - CSV of All NFL Weather From 1960 to 2013 - Every NFL Player in CSV format - Play by Play data from 2013 till 2022

Original data

Acknowlegement

Foto von Muyuan Ma auf Unsplash

Context

This is an NFL data set separated by teams. All data scraped from Pro Football Reference (https://www.pro-football-reference.com/).

Content

Each data has annual stats split into five types of files. - Roster All Years is, as it sounds, the roster of players each year. - Stats by Year includes some basic statistics about each team for each season (listed by year season started) - Weekly Odds All Years has the betting odds every week for each matchup. - Weekly Scores All Years has some basic game information every week for each matchup. It also includes the team's current season record after that game. - Weekly Injuries has a separate file for each year. It shows each player's injury status each week going into the game (P=probably, O=out, D=doubtful, Q=questionable, IR=Injured Reserve Most of the stats should be fairly obvious, but if there's any abbreviations you aren't sure about, be sure to check out their glossary.

Acknowledgements

Huge thanks to the stats nerds at Pro Football Reference who keep such an amazing list of information stretching so far back, as well as some of their subjective measurements like AV (approximate value) for each player each year.

Inspiration

A lot of the NFL stats out there weren't quite what I was looking for so I decided to make my own dataset.

In 2023, the greatest share of players by ethnic group in the National Football League (NFL) were black or African American athletes, constituting just over ** percent of players within the NFL. Despite the large population of Hispanic or Latino people within the United States, there is a substantial underrepresentation within the NFL, with only *** percent of players identifying as such. National Football League The National Football League (NFL) is a professional American football league that was established in 1920 and now consists of 32 clubs divided into two conferences, the National Football Conference (NFC) and the American Football Conference (AFC). The league culminates in the Super Bowl, the NFL's annual championship game. As the league’s championship game, the Super Bowl has grown into one of the world's largest single-day sporting events, attracting high television ratings and generating billions of dollars in consumer spending. NFL revenues The NFL is one of the most profitable sports leagues in the world, generating a staggering **** billion U.S. dollars in 2022. This total revenue of all ** NFL teams has constantly increased over the past 15 years and, although this figure dropped significantly in 2020, this was largely as a result of the impact of coronavirus (COVID-19) containment measures. This significant drop in revenue demonstrates one of the primary impacts of COVID-19 on professional sports leagues. NFL franchises As a result of this profitability in non-pandemic times, the franchises of the NFL are attributed extremely high market values. The Dallas Cowboys were by far the most valuable franchise in the NFL, with a market value of **** billion US dollars in 2023. The high value of NFL franchises can be seen clearly when compared to those of the NBA, MLB, and NHL. Franchises within the NFL had an average market value of approximately *** billion U.S. dollars in 2023.

Context

I created this dataset using data from Pro Football Reference over the last 10 seasons.

Content

The data includes weekly game stats from the 2010 to 2019 season. Each record includes the week (Week), home team (HomeTeam), away team(AwayTeam), the total (Total), home team rushing attempts (H-RushAtt), home rushing yards (H-RushYards), home passing yards (H-PassYards), home turnovers (H-Turnover), points scored by the home team (H-Score), away rushing attempts (A-RushAtt), away rushing yards (A-RushYards), away passing yards (A-PassYards), away turnovers (A-Turnover), points scored by the away team (A-Score), and the result of the game based on the points scored (Result) if 1 then the combined points scored is greater than the total, if -1 then the combined points scored is less than the total, if 0 then combined points scored is equal to the total.

Acknowledgements

Pro Football Reference

Inspiration

I wanted to create a model to predict totals to NFL Games using weekly game stats. I created some scripts to average a teams game stats going into each week starting for week 6 games. I didn't have much success with my model, but I figured the data would be helpful for any sort of NFL game analytics.

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

Comprehensive dataset of college football teams ranked by nfl draft picks. Includes historical data, statistics, and performance metrics for NCAA Division I FBS teams.

The dataset contains every Pro Football Hall of Fame Inductee in NFL history. This includes player stats for rushing, passing and receiving.

As of the Class of 2022, there are a total of 362 members of the Hall of Fame. Members are referred to as "Gold Jackets" due to the distinctive gold jackets they receive during the induction ceremony. Between four and eight new inductees are normally enshrined every year.

Comprehensive dataset of college football teams ranked by first round nfl draft picks. Includes historical data, statistics, and performance metrics for NCAA Division I FBS teams.

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

The American Football market has experienced a dynamic evolution, carving out a significant niche in both the sporting world and the broader entertainment landscape. As of recent evaluations, the market size stands robust, reflecting the profound popularity of the sport across demographics, particularly in the Unite

This data was created using three different sources: pro-football-reference.com, covers.com, teamrankings.com. I used various CSV files and web scraping to combine 88 tables to create this data set. There are no missing values and the data provides information about a team's performance throughout the years 2010-2021. It does not contain 2022 stats, since that's what I'm trying to predict.

In this CSV dataset you will find: Team (char) - Name of the team WinLoss.perc (num) - This is a percentage metric which gives an idea about how often the team wins. If the winning % of a team is 50%, the team wins 50% of the games it plays. PD (int) - This number signifies the sum of the difference in points scored in all games for that team. For eg: If a team wins game 1 with a score of 21-17, the PD is 4. The same team loses their game 2 with a score of 20-21, their new D would be 4 + (-1) = 3 Year (int) FGM (int) - This is a numeric metric of the Field goals made by a team in the whole season. FG_prec (num) - This is a percentage metric which measures the ratio of all the field goals made over all the field goals attempted RedZone_perc (num) - This is a percentage metric that gives insight on the performance of the offensive team. It measures the ratio of the offensive drives that end in the Red Zone compared to all the offensive drives the team has made in the season. The Red Zone is the 20 yard area adjacent to the End Zone, which is where the offensive team is trying to get the ball in. playoff_win_perc (num) - Since not all the teams make it in the playoffs, this metric is quite important. Only seven teams from each conference qualifies for the playoffs. This percentage is a ratio of the games a team wins in the playoff over the total number of games played by the team in the playoffs. Score_perc (num) - This is a percentage metric providing information of the scoring success of the offensive team Turnover_perc (num) - This is a percentage metric that measures the ratio of the offensive drives that end up as a turnover via any method and the total offensive drives made by the team per season. The lower this statistic, the better it is for the team’s chances of winning. RushYperG (num) - This is a numeric metric which measures the average rushing yards the offensive team covers trying to move towards the endzone per game. PassYperG (num) - This is a numeric metric which measures the average passing yards the offensive team covers trying to move towards the endzone per game. PointperG (num) - This is a numeric metric giving insight on the average of the points the team scores per game throughout the season. possperG (num) - This is a percentage metric of the average ball possession of a team throughout the season. For eg: If a team has a possession percentage/game of 60%, the team on an average throughout the season possessed the ball 60% of the total game duration. YallowedperG (num) - This is a numeric metric that gives insight about how many yards the opposition offensive team was able to gain while the defense was trying to defend the End Zone. PointallowedperG (num) - This is a numeric metric of the points scored by the opposing team while the defense was trying to defend the End Zone. **perc_punt_20 (num) **- This is another percentage metric signifying the ratio of the punts that make it within 20 yards of the endzone compared to the total number of punts made by the punter. Result (char) - This is a categorical label which tells if the team won the superbowl or not that particular year

Comprehensive dataset of college football teams ranked by all-americans. Includes historical data, statistics, and performance metrics for NCAA Division I FBS teams.

Fantasy Football Market Outlook

In 2023, the global fantasy football market size was valued at approximately USD 24.4 billion, and it is projected to reach USD 48.7 billion by 2032, growing at a compound annual growth rate (CAGR) of 8.9%. This robust growth is driven by the increasing popularity of sports betting, the expansion of internet penetration, and the evolving digital landscape that has made fantasy sports more accessible to a global audience.

The burgeoning interest in fantasy football is significantly fueled by the thrill associated with virtual sports management and the competitive spirit it invokes among participants. The advent of high-speed internet and the proliferation of smartphones have considerably lowered entry barriers, enabling users from diverse demographics to engage with fantasy football platforms. Enhanced user interfaces and the strategic inclusion of real-time data and analytics have further enriched the user experience, making the game more immersive and engaging. Additionally, the growing partnerships between fantasy sports platforms and major sports leagues have enhanced the credibility and reach of the market.

Another crucial growth factor is the increasing monetization avenues within the fantasy football ecosystem. Platforms are leveraging ad revenues, subscription models, and in-app purchases to enhance their profitability. The introduction of innovative revenue streams like virtual goods, personalized content, and premium features provides substantial growth opportunities. Furthermore, the gamification of fantasy sports, including interactive features like social sharing and leaderboards, has significantly contributed to user retention and engagement.

Public perception and societal trends have also played a pivotal role in the market's growth. The cultural acceptance of fantasy sports as a mainstream activity has expanded its demographic reach beyond traditional sports enthusiasts. The integration of fantasy sports into mainstream media, including dedicated shows and podcasts, has increased visibility and user adoption. This cultural shift has also led to the formation of fantasy football communities, fostering a sense of camaraderie and collective enthusiasm.

American Football has played a pivotal role in the evolution of fantasy sports, particularly in North America, where the National Football League (NFL) stands as the most popular league for fantasy football. The deep-rooted passion for American Football among fans has translated into a robust fantasy football culture, with millions of participants engaging in both daily and season-long leagues. The NFL's extensive media coverage and the availability of detailed player statistics have made it an ideal sport for fantasy leagues, offering fans an opportunity to test their managerial skills and engage with the sport on a deeper level. This engagement is further amplified by the NFL's active promotion of fantasy football, which has helped to sustain and grow its fan base over the years.

From a regional perspective, North America continues to dominate the fantasy football market, driven by the high penetration of internet services and the strong sports culture in the region. The United States alone accounts for a significant portion of the market owing to the popularity of the National Football League (NFL). Meanwhile, Europe and the Asia Pacific are emerging as significant growth regions. The increasing popularity of soccer and the rising number of internet users in countries like India and China are expected to contribute to the market's expansion in these regions.

Platform Analysis

The fantasy football market is segmented into mobile applications and websites based on the platform. Mobile applications have revolutionized the fantasy sports experience by offering users the convenience of managing their teams on the go. The advent of sophisticated mobile apps with user-friendly interfaces, real-time updates, and interactive features has significantly enhanced user engagement. The integration of advanced analytics and personalized recommendations in mobile applications has made it easier for users to make informed decisions, thereby increasing user satisfaction and retention.

On the other hand, websites continue to be a popular platform among a segment of users who prefer a more detailed and expansive interface. Websites offer a broader range of features and functionalities compared to mobile applicatio

NFL Passing stats between 2000 and 2016. For regular season only. Extracted from FoxSports by Christopher Hayles for Fantasy Football purposes.

Total attendance at National Football League (NFL) games reached about ***** million fans across the regular season in 2024. This represented a slight decrease over the previous year's figure of approximately **** 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 ** million per season. The NFL is composed of 32 teams and each team plays a minimum of 8 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 ****** 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 *** thousand. The Cowboys also had the highest average attendance that season with around ****** people attending each home game. The average price for a ticket to an NFL game was at ****** U.S. dollars in 2023. On average, tickets to Las Vegas Raiders games were the most expensive (****** U.S. dollars), while tickets for Arizona Cardinals games were the least expensive, with an average price of ***** U.S. dollars.

212 verified sports games with complete statistics from MLB, NFL, College Football, and College Basketball

The American Football Club market represents a dynamic and ever-evolving segment within the larger sports industry, encompassing a vast array of professional and amateur leagues, clubs, and associations. With a current market size valued at several billion dollars, this sector has witnessed significant growth over t

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