The average length of a player's career in the National Football League (NFL) is relatively short, with the average career lasting around 3.3 years. The league is considered one of the most physically demanding sports leagues in the world, with players regularly exposed to hard hits and collisions. This leads to a high risk of injury, and many players are forced to retire early or miss significant time due to injuries. Additionally, the NFL is highly competitive, with a large pool of talented players who are eager to take the place of those who are injured or no longer able to perform at a high level.

Injuries are all too common in the NFL Injuries are a common and significant concern in the NFL. Due to the physical nature of the sport, players are at risk of a wide range of injuries, including both acute injuries such as broken bones and concussions, as well as chronic injuries such as joint and muscle problems. Concussions and other head injuries are also a major concern in the NFL. Football players are at a higher risk of concussions than athletes in other sports, due to the nature of the game and the fact that players are often hit in the head. Concussions can lead to a variety of long-term health problems, including chronic traumatic encephalopathy (CTE), a progressive degenerative disease of the brain that is linked to repeated head trauma.

Preventative measures The NFL has implemented some measures to try to reduce the number and severity of injuries, such as rule changes to reduce the number of hits to the head, better equipment, and more stringent return-to-play protocols after an injury. The NFL also funds research on injuries and works with medical experts to develop best practices for preventing and treating injuries. However, many fans still believe that more can be done to improve player welfare and prioritize player safety over entertainment and revenues.

Life after football When a player decides to retire, they have several options available to them. Many players transition to a different career, while others may choose to pursue other interests or spend time with their families. Some of the common career paths that retired NFL players pursue include broadcasting, coaching, business, philanthropy, politics, sports management, continuing education, and personal training or fitness coaching.

The NFL also offers several retirement benefits for players, such as pension plan, disability and death benefits, and health insurance for players, and their families. The NFL Players Association also provides assistance and support for players as they transition out of football and into new careers.

Number of employed persons by job tenure, National Occupational Classification (NOC) and sex, last 5 years.

Employment Rate in the United States increased to 59.70 percent in September from 59.60 percent in August of 2025. This dataset provides - United States Employment Rate- actual values, historical data, forecast, chart, statistics, economic calendar and news.

In 2024, the employment rate of the workforce of 55 years and older decreased to 37.3 percent. Employment rate among young adults (age 16-24) was at 50.9 percent in 2024. For monthly updates on employment in the United States visit the annual national employment rate here.

In 2025, it was estimated that over 163 million Americans were in some form of employment, while 4.16 percent of the total workforce was unemployed. This was the lowest unemployment rate since the 1950s, although these figures are expected to rise in 2023 and beyond. 1980s-2010s Since the 1980s, the total United States labor force has generally risen as the population has grown, however, the annual average unemployment rate has fluctuated significantly, usually increasing in times of crisis, before falling more slowly during periods of recovery and economic stability. For example, unemployment peaked at 9.7 percent during the early 1980s recession, which was largely caused by the ripple effects of the Iranian Revolution on global oil prices and inflation. Other notable spikes came during the early 1990s; again, largely due to inflation caused by another oil shock, and during the early 2000s recession. The Great Recession then saw the U.S. unemployment rate soar to 9.6 percent, following the collapse of the U.S. housing market and its impact on the banking sector, and it was not until 2016 that unemployment returned to pre-recession levels. 2020s 2019 had marked a decade-long low in unemployment, before the economic impact of the Covid-19 pandemic saw the sharpest year-on-year increase in unemployment since the Great Depression, and the total number of workers fell by almost 10 million people. Despite the continuation of the pandemic in the years that followed, alongside the associated supply-chain issues and onset of the inflation crisis, unemployment reached just 3.67 percent in 2022 - current projections are for this figure to rise in 2023 and the years that follow, although these forecasts are subject to change if recent years are anything to go by.

Number of job vacancies, proportion of job vacancies and average offered hourly wage by National Occupational Classification (NOC) and duration of job vacancy, last 5 quarters.

Spain Employment Rate: ow Over 25 Years data was reported at 52.990 % in Sep 2018. This records an increase from the previous number of 52.810 % for Jun 2018. Spain Employment Rate: ow Over 25 Years data is updated quarterly, averaging 48.820 % from Sep 1976 (Median) to Sep 2018, with 169 observations. The data reached an all-time high of 56.180 % in Jun 2007 and a record low of 41.420 % in Mar 1986. Spain Employment Rate: ow Over 25 Years data remains active status in CEIC and is reported by National Statistics Institute. The data is categorized under Global Database’s Spain – Table ES.G012: Employment Rate: Labour Force Survey.

Description: These are research indicators of doctorate holders in Europe that were compiled from the criteria and factors of the Eurostat. This dataset consists of data in five categories (i.e. Career Development of Doctorate Holders; Labour Market - Job Vacancy Statistics; Skill-related Statistics; European and International Co-patenting in EPO Applications and Ownership of Inventors in EPO Applications). The Eurostat Research Indicators consist of (1) Doctorate holders who have studied, worked or carried out research in another EU country (%); (2) Doctorate holders by activity status (%); (3) Doctorate holders by sex and age group; (4) Employed doctorate holders working as researchers by length of stay with the same employer (%); (5) Employed doctorate holders working as researchers by job mobility and sectors of performance over the last 10 years (%); (6) Employed doctorate holders by length of stay with the same employer and sectors of performance (%); (7) Employed doctorate holders by occupation (ISCO_88, %); (8) Employed doctorate holders by occupation (ISCO_08, %); (9) Employed doctorate holders in non-managerial and non-professional occupations by fields of science (%); (10) Level of dissatisfaction of employed doctorate holders by reason and sex (%); (11) National doctorate holders having lived or stayed abroad in the past 10 years by previous region of stay (%); (12) National doctorate holders having lived or stayed abroad in the past 10 years by reason for returning into the country (%); (13) Non-EU doctorate holders in total doctorate holders (%); (14) Unemployment rate of doctorate holders by fields of science; (15) Employment in Foreign Affiliates of Domestic Enterprises; (16) Employment in Foreign Controlled Enterprises; (17) Employment rate of non-EU nationals, age group 20-64; (18) Intra-mural Business Enterprise R&D Expenditures in Foreign Controlled Enterprises; (19) Job vacancy rate by NACE Rev. 2 activity - annual data (from 2001 onwards); (20) Job vacancy statistics by NACE Rev. 2 activity, occupation and NUTS 2 regions - quarterly data; (21) Job vacancy statistics by NACE Rev. 2 activity - quarterly data (from 2001 onwards); (22) Value Added in Foreign Controlled Enterprises; (23) Graduates at doctoral level by sex and age groups - per 1000 of population aged 25-34; (24) Graduates at doctoral level, in science, math., computing, engineering, manufacturing, construction, by sex - per 1000 of population aged 25-34; (25) Level of the best-known foreign language (self-reported) by degree of urbanisation; (26) Level of the best-known foreign language (self-reported) by educational attainment level; (27) Level of the best-known foreign language (self-reported) by labour status; (28) Level of the best-known foreign language (self-reported) by occupation; (29) Number of foreign languages known (self-reported) by educational attainment level; (30) Number of foreign languages known (self-reported) by degree of urbanisation; (31) Number of foreign languages known (self-reported) by labour status; (32) Number of foreign languages known (self-reported) by occupation; (33) Population by educational attainment level, sex, age and country of birth (%); (34) Co-patenting at the EPO according to applicants’/inventors’ country of residence - % in the total of each EU Member State patents; (35) Co-patenting at the EPO: crossing inventors and applicants; (36) Co-patenting at the EPO according to applicants’/inventors’ country of residence - number; (37) EU co-patenting at the EPO according to applicants’/ inventors’ country of residence by international patent classification (IPC) sections - number; (38) EU co-patenting at the EPO according to applicants’/inventors’ country of residence by international patent classification (IPC) sections - % in the total of all EU patents; (39) Domestic ownership of foreign inventions in patent applications to the EPO by priority year; (40) Foreign ownership of domestic inventions in patent applications to the EPO by priority year; and (41) Patent applications to the EPO with foreign co-inventors, by priority year.

Job Quits Rate in the United States decreased to 1.90 percent in August from 2 percent in July of 2025. This dataset includes a chart with historical data for the United States Job Quits Rate.

Emmitt Smith is the all-time rushing leader of the National Football League (NFL) with 18,355 career rushing yards. The running back, who spent the majority of his 15-year career with the Dallas Cowboys, became the all-time leader rusher in the NFL in the 2002 season.

The running backs in the NFL

Running backs are often an integral part to the offense of an NFL team. The players manning the position carry the ball from behind the line of scrimmage with the aim to gain yards and advance the offensive position of their team towards the opposing team’s end zone. The position is physically demanding as the running back is usually hit by opposing defensive players on every play that they touch the ball. Therefore, it is no surprise that the average career length of running backs is the shortest when compared to other positions on an NFL team.

Longevity as a major challenge

With the average career of a running back in the NFL lasting only roughly two and a half seasons, chances are slim for any player starting out in the league to move onto the all-time rushing leader list at some point. All players in the top 10 played at least ten seasons in the NFL and were rarely injured for more than a few games. Emmitt Smith, for example, recorded 11 consecutive seasons with at least 1,000 yards in rushing yards from 1991 to 2001 for the Dallas Cowboys, missing a total of only seven games during that time span.

VITAL SIGNS INDICATOR Jobs by Wage Level (EQ1)

FULL MEASURE NAME Distribution of jobs by low-, middle-, and high-wage occupations

LAST UPDATED January 2019

DESCRIPTION Jobs by wage level refers to the distribution of jobs by low-, middle- and high-wage occupations. In the San Francisco Bay Area, low-wage occupations have a median hourly wage of less than 80% of the regional median wage; median wages for middle-wage occupations range from 80% to 120% of the regional median wage, and high-wage occupations have a median hourly wage above 120% of the regional median wage.

DATA SOURCE California Employment Development Department OES (2001-2017) http://www.labormarketinfo.edd.ca.gov/data/oes-employment-and-wages.html

American Community Survey (2001-2017) http://api.census.gov

CONTACT INFORMATION vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator) Jobs are determined to be low-, middle-, or high-wage based on the median hourly wage of their occupational classification in the most recent year. Low-wage jobs are those that pay below 80% of the regional median wage. Middle-wage jobs are those that pay between 80% and 120% of the regional median wage. High-wage jobs are those that pay above 120% of the regional median wage. Regional median hourly wages are estimated from the American Community Survey and are published on the Vital Signs Income indicator page. For the national context analysis, occupation wage classifications are unique to each metro area. A low-wage job in New York, for instance, may be a middle-wage job in Miami. For the Bay Area in 2017, the median hourly wage for low-wage occupations was less than $20.86 per hour. For middle-wage jobs, the median ranged from $20.86 to $31.30 per hour; and for high-wage jobs, the median wage was above $31.30 per hour.

Occupational employment and wage information comes from the Occupational Employment Statistics (OES) program. Regional and subregional data is published by the California Employment Development Department. Metro data is published by the Bureau of Labor Statistics. The OES program collects data on wage and salary workers in nonfarm establishments to produce employment and wage estimates for some 800 occupations. Data from non-incorporated self-employed persons are not collected, and are not included in these estimates. Wage estimates represent a three-year rolling average.

Due to changes in reporting during the analysis period, subregion data from the EDD OES have been aggregated to produce geographies that can be compared over time. West Bay is San Mateo, San Francisco, and Marin counties. North Bay is Sonoma, Solano and Napa counties. East Bay is Alameda and Contra Costa counties. South Bay is Santa Clara County from 2001-2004 and Santa Clara and San Benito counties from 2005-2017.

Due to changes in occupation classifications during the analysis period, all occupations have been reassigned to 2010 SOC codes. For pre-2009 reporting years, all employment in occupations that were split into two or more 2010 SOC occupations are assigned to the first 2010 SOC occupation listed in the crosswalk table provided by the Census Bureau. This method assumes these occupations always fall in the same wage category, and sensitivity analysis of this reassignment method shows this is true in most cases.

In order to use OES data for time series analysis, several steps were taken to handle missing wage or employment data. For some occupations, such as airline pilots and flight attendants, no wage information was provided and these were removed from the analysis. Other occupations did not record a median hourly wage (mostly due to irregular work hours) but did record an annual average wage. Nearly all these occupations were in education (i.e. teachers). In this case, a 2080 hour-work year was assumed and [annual average wage/2080] was used as a proxy for median income. Most of these occupations were classified as high-wage, thus dispelling concern of underestimating a median wage for a teaching occupation that requires less than 2080 hours of work a year (equivalent to 12 months fulltime). Finally, the OES has missing employment data for occupations across the time series. To make the employment data comparable between years, gaps in employment data for occupations are ‘filled-in’ using linear interpolation if there are at least two years of employment data found in OES. Occupations with less than two years of employment data were dropped from the analysis. Over 80% of interpolated cells represent missing employment data for just one year in the time series. While this interpolating technique may impact year-over-year comparisons, the long-term trends represented in the analysis generally are accurate.

Graph and download economic data for Employed full time: Median usual weekly real earnings: Wage and salary workers: 16 years and over (LES1252881600Q) from Q1 1979 to Q2 2025 about full-time, salaries, workers, earnings, 16 years +, wages, median, real, employment, and USA.

Uruguay Employment Rate: Urban: Below 25 Years Old data was reported at 29.647 % in Sep 2018. This records a decrease from the previous number of 30.778 % for Aug 2018. Uruguay Employment Rate: Urban: Below 25 Years Old data is updated monthly, averaging 37.500 % from Jan 2006 (Median) to Sep 2018, with 153 observations. The data reached an all-time high of 42.465 % in Jun 2011 and a record low of 29.075 % in Aug 2017. Uruguay Employment Rate: Urban: Below 25 Years Old data remains active status in CEIC and is reported by National Institute of Statistics. The data is categorized under Global Database’s Uruguay – Table UY.G007: Employment Rate.

Average number of weekly hours dedicated to the care of persons under 15 years of age, by sex and employment situation. Average and standard deviation. Population aged 16 years old and over caring for persons under 15 years of age. National.

Economically Active Population Survey: Employment rate of people between 20 and 64 years old by age group and Autonomous Community. Annual. Autonomous Communities and Cities.

Graph and download economic data for Job Openings: Total Nonfarm (JTSJOL) from Dec 2000 to Aug 2025 about job openings, vacancy, nonfarm, and USA.

Ecuador Employment Rate: 45 to 64 Years Old data was reported at 97.687 % in Jun 2019. This records an increase from the previous number of 97.654 % for Mar 2019. Ecuador Employment Rate: 45 to 64 Years Old data is updated quarterly, averaging 97.943 % from Dec 2013 (Median) to Jun 2019, with 23 observations. The data reached an all-time high of 98.530 % in Mar 2015 and a record low of 96.961 % in Jun 2016. Ecuador Employment Rate: 45 to 64 Years Old data remains active status in CEIC and is reported by National Institute of Statistics and Census. The data is categorized under Global Database’s Ecuador – Table EC.G019: ENEMDU: Employment Rate.

Women and Men in Spain: Employment rate of persons from 25 to 49 years old with children/without children under 12 years old according to period. Spain, UE-27 and UE-28. Annual. National. Nota: UE27_2020: 27 países (desde 2020). UE-28: 28 países (2013-2020).

Graph and download economic data for Unemployment Rate - Black or African American (LNS14000006) from Jan 1972 to Sep 2025 about African-American, 16 years +, household survey, unemployment, rate, and USA.

Economically Active Population Survey: Employment rate for people between 20 and 64 years old by sex and educational level attained. Annual. National.