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

Traffic analytics, rankings, and competitive metrics for baseball-reference.com as of September 2025

Current and updated dataset of NBA Playoff statistics since the 1949-1950 season!

All standard statistics like Assists Per Game, Minutes Per Game, etc. are present as well as advanced statistics like Player Efficiency Rating (PER), Value Over Replacement Player (VORP), Win Share, and more!

This dataset was web scraped from https://www.basketball-reference.com.

Feel free to let me know if there are any statistics or player information that isn't present that you think should be added!

If you want the regular season statistics check out my other data set.

For more details on how some statistics are calculated, please see the https://www.basketball-reference.com/about/glossary.html

These tables provide annual and quarterly data for a selection of key statistics under the following themes: population, demography and health. Figures for the latest quarters and years may be provisional, these will be updated to final figures when data is available. Source agency: Office for National Statistics Designation: National Statistics Language: English Alternative title: Vital Statistics Reference Tables

Traffic analytics, rankings, and competitive metrics for sports-reference.com as of September 2025

Provide 11-digit import commodity number and its corresponding import and export regulations (including historical data that has expired).

Descriptive data on reference-rates across organizations.

Context

This data was scraped from basketball-reference.com with the intended purpose of analyzing how NBA prospect performance in the NCAA and international league play translates to the NBA. The data is not complete as it is limited to the information that was available on basketball-reference.com. For unique IDs use player name and date of birth since there have been multiple players with the same name.

Content

You can find 3 datasets:

• Draft_table: information about the player
• NBA_game_logs: game statistics from each game of the players NBA career
• Pre_NBA_game_logs: game statistics from each game of the players career after highschool but before the NBA. This includes NCAA data and any available game logs from international leagues.

Acknowledgements

Thank you to basketball-reference.com for having so much great data in one interconnected site.

Inspiration

To bring greater understanding about the statistical relationships of draft prospect performance and future NBA performance

The Reference Management Tool System market has emerged as a critical component for researchers, academics, and professionals in various fields, facilitating the organization and management of bibliographic data and references. As the volume of published research grows exponentially, these tools serve a pivotal role

Traffic analytics, rankings, and competitive metrics for basketball-reference.com as of September 2025

Age of household reference person (%) by Age Range, Social Group and Year

View data using web pages

Download .px file (Software required)

Context

I used the Paul Rossotti’s data set on my personal projects. However, after a long time using it I noticed that I would need more old and recent data, so I ended up with a more complete data set and I thought that might help someone. Since his data set was used as a base, all the credits goes to him. I only incremented it. Also I am willing to update this data set yearly.

You can access his work using this link on the reference section.

Content

This data set contains information about the box score of every NBA game since 1949-50 until now. You can get the data individually for each season, decade or a compiled of all the data. In total the data set has, approximately, 120 features/columns/attributes that goes from basic stats (like total points, rebounds, assists, blocks, and so on) to more advanced ones (like floor impact counter, assist rate, possessions, pace, play% and much more!).

Each game will contain the same features to the home team and its opponent (away team) and some other features related to the game itself (like game date, season, season type and match winner). If you like stats and NBA, this data set was made for you!

If do you wanna more about the formulas used and its meaning, please check the reference section. Also you can check the “features_description” file. There you will find a brief description of each feature and its respective formula (only for more advanced stats).

Acknowledgements

LAST TIME THE DATA SET WAS UPDATED:

July 26, 2021 (07/26/2021) – 1pm EDT

Questions about the dataset:

Q:How did you collected the data? A: I created a web scrapper using python to do the hard work.

Q: How did you filled the missing values? A: For the float columns I filled with “0.0”. For the object columns I left with a NaN value, but don’t need to worry about it. The only columns that I need to do that was teamWins, teamLosses, opptWins, opptLosses. However only 8 rows in the entire data set has NaN values! Great news, isn’t it?

Q: Where can I see the description/formula for each attribute/column/feature? A: You can check it out in the “features_informations” file inside the data set.

Q: Will you constantly update the data set? A: Yes!

Q: The data contains only regular reason games? A: No! The data contains playoffs games as well.

References

About the stats and formulas used: https://www.basketball-reference.com/about/glossary.html https://basketball.realgm.com/info/glossary https://www.kaggle.com/pablote/nba-enhanced-stats (Paul Rossotti’s data set)

Where the data was collected: https://www.basketball-reference.com/leagues/

The CMS Center for Strategic Planning produces an annual CMS Statistics reference booklet that provides a quick reference for summary information about health expenditures and the Medicare and Medicaid health insurance programs. The CMS Statistics reference booklet is published in June of each calendar year and represents the most currently available information at the time of publication. CMS Statistics reference booklets are available for 2003 through the most currently available complete calendar year.

Managing reliable reference data across the global fixed income universe is complex and resource-intensive. With the All Asset Classes Bond Reference Data package from SIX Flex®, you gain access to global fixed income data—including Corporates, Governments, U.S. Municipals, and Structured Finance (ABS/MBS/Agency debt). Get comprehensive, up-to-date data on-demand or in bulk via a user-friendly platform that streamlines workflows and boosts efficiency. Easily maintain your security master or power your website with accurate, timely information. Stay ahead with updates on new issues and key fields like Issuer Name, Seniority, Call Features, Jurisdiction, Obligor Name, Bond Type, and Insurance/Insurer details.

Each year Eurostat collects demographic data at regional level from EU, EFTA and Candidate countries as part of the Population Statistics data collection. POPSTAT is Eurostat’s main annual demographic data collection and aims to gather information on demography and migration at national and regional levels by various breakdowns (for the full overview see the Eurostat dedicated section). More specifically, POPSTAT collects data at regional levels on:

• population stocks;
• vital events (live births and deaths).

Each country must send the statistics for the reference year (T) to Eurostat by 31 December of the following calendar year (T+1). Eurostat then publishes the data in March of the calendar year after that (T+2).

Demographic data at regional level include statistics on the population at the end of the calendar year and on live births and deaths during that year, according to the official classification for statistics at regional level (NUTS - nomenclature of territorial units for statistics) in force in the year. These data are broken down by NUTS 2 and 3 levels for EU countries. For more information on the NUTS classification and its versions please refer to the Eurostat dedicated pages. For EFTA and Candidate countries the data are collected according to the agreed statistical regions that have been coded in a way that resembles NUTS.

The breakdown of demographic data collected at regional level varies depending on the NUTS/statistical region level. These breakdowns are summarised below, along with the link to the corresponding online table:

NUTS 2 level

• Population by sex, age and region of residence — demo_r_d2jan
• Population on 1 January by age group, sex and region of residence — demo_r_pjangroup
• Live births by mother's age, mother's year of birth and mother's region of residence — demo_r_fagec
• Deaths by sex, age, and region of residence — demo_r_magec

NUTS 3 level

• Population on 1 January by sex, age group and region of residence — demo_r_pjangrp3
• Population on 1 January by broad age group, sex and region of residence — demo_r_pjanaggr3
• Live births (total) by region of residence — demo_r_births
• Live births by five-year age group of the mothers and region of residence — demo_r_fagec3
• Deaths (total) by region of residence — demo_r_deaths
• Deaths by five-year age group, sex and region of residence — demo_r_magec3

This more detailed breakdown (by five-year age group) of the data collected at NUTS 3 level started with the reference year 2013 and is in accordance with the European laws on demographic statistics. In addition to the regional codes set out in the NUTS classification in force, these online tables include few additional codes that are meant to cover data on persons and events that cannot be allocated to any official NUTS region. These codes are denoted as CCX/CCXX/CCXXX (Not regionalised/Unknown level 1/2/3; CC stands for country code) and are available only for France, Hungary, North Macedonia and Albania, reflecting the raw data as transmitted to Eurostat.

For the reference years from 1990 to 2012 all countries sent to Eurostat all the data on a voluntary basis, therefore the completeness of the tables and the length of time series reflect the level of data received from the responsible National Statistical Institutes’ (NSIs) data provider. As a general remark, a lower data breakdown is available at NUTS 3 level as detailed:

• population data are broken down by sex and broad age groups (0-14, 15-64 and 65 or more). The data have this disaggregation since the reference year 2007 for all countries, and even longer for some — demo_r_pjanaggr3
• vital events (live births and deaths) data are available only as totals, without any further breakdown — demo_r_births and demo_r_deaths

Demographic indicators are calculated by Eurostat based on the above raw data using a common methodology for all countries and regions. The regional demographic indicators computed by NUTS level and the corresponding online tables are summarised below:

NUTS 2 level

• Population structure indicators by region of residence (shares of various population age groups, dependency ratios and median age) — demo_r_pjanind2
• Fertility indicators by region of residence — demo_r_find2
• Fertility rates by age and region of residence — demo_r_frate2
• Life table by age, sex and region of residence — demo_r_mlife
• Life expectancy by age, sex and region of residence — demo_r_mlifexp
• Infant mortality rates by region of residence — demo_r_minfind

NUTS 3 level

• Population change - Demographic balance and crude rates at regional level — demo_r_gind3
• Population density by region — demo_r_d3dens
• Population structure indicators by region of residence (shares of various population age groups, dependency ratios and median age) — demo_r_pjanind3
• Fertility indicators by region of residence (total fertility rate, mean age of woman at childbirth and median age of woman at childbirth) — demo_r_find3

Notes:

1) All the indicators are computed for all lower NUTS regions included in the tables (e.g. data included in a table at NUTS 3 level will include also the data for NUTS 2, 1 and country levels).

2) Demographic indicators computed by NUTS 2 and 3 levels are calculated using input data that have different age breakdown. Therefore, minor differences can be noted between the values corresponding to the same indicator of the same region classified as NUTS 2, 1 or country level.

3) Since the reference year 2015, Eurostat has stopped collecting data on area; therefore, the table 'Area by NUTS 3 region (demo_r_d3area)' includes data up to the year 2015 included.

4) Starting with the reference year 2016, the population density indicator is computed using the new data on area 'Area by NUTS 3 region (reg_area3).

Distribution of households by educational attainment level of the reference person - experimental statistics

Traffic analytics, rankings, and competitive metrics for reference.com as of September 2025

Data on work activity during the reference year by industry sector (2-digit code) from the North American Industry Classification System (NAICS) 2017, occupation broad category (1-digit code) from the National Occupational Classification (NOC) 2021, income statistics and age, for the population aged 15 years and over in private households in Canada, provinces and territories, census metropolitan areas and census agglomerations with parts.

Objectives: To analyse the total number of newspaper articles citing the four leading general medical journals and to describe national citation patterns. Design: Quantitative content analysis Setting/sample: Full text of 22 general newspapers in 14 countries over the period 2008-2015, collected from LexisNexis. The 14 countries have been categorized into four regions: US, UK, Western World (EU countries other than UK, and Australia, New Zealand and Canada) and Rest of the World (other countries). Main outcome measure: Press citations of four medical journals (two American: NEJM and JAMA; and two British: The Lancet and The BMJ) in 22 newspapers. Results: British and American newspapers cited some of the four analysed medical journals about three times a week in 2008-2015 (weekly mean 3.2 and 2.7 citations respectively); the newspapers from other Western countries did so about once a week (weekly mean 1.1), and those from the Rest of the World cited them about once a month (monthly mean 1.1). The New York Times cited above all other newspapers (weekly mean 4.7). The analysis showed the existence of three national citation patterns in the daily press: American newspapers cited mostly American journals (70.0% of citations), British newspapers cited mostly British journals (86.5%), and the rest of the analysed press cited more British journals than American ones. The Lancet was the most cited journal in the press of almost all Western countries outside the US and the UK. Multivariate correspondence analysis confirmed the national patterns and showed that over 85% of the citation data variability is retained in just one single new variable: the national dimension. Conclusion: British and American newspapers are the ones that cite the four analysed medical journals more often, showing a domestic preference for their respective national journals; non-British and non-American newspapers show a common international citation pattern.

Economically Active Population Survey: Population by family relationship to the reference person, sex and age group. Quarterly. National.