The violent crime rate indicator includes both the total number of violent crime incidents per year in Champaign County, and the number of violent crime incidents per 100,000 people per year in Champaign County. “Violent crimes” are those counted in the following categories in the Illinois State Police’s annual Crime in Illinois report: Criminal Homicide, Criminal Sexual Assault (Rape), Robbery, Aggravated Assault, and Aggravated Battery. The incidence of violent crime is an integral part of understanding the safety of a given community.

Both the total number of offenses in Champaign County and the rate per 100,000 population were significantly lower in 2021 than at the start of the measured time period, 1996. The most recent rise in both of these figures was in 2019-2020, before falling again in 2021. The year with the lowest number of total offenses and the rate per 100,000 population in the study period was 2015; both measures are slightly higher since then.

This data is sourced from the Illinois State Police’s annually released Crime in Illinois: Annual Uniform Crime Report, available on the Uniform Crime Report Index Offense Explorer.

Sources: Illinois State Police. (2021). Crime in Illinois: Annual Uniform Crime Report 2021. Illinois State Police. (2020). Crime in Illinois: Annual Uniform Crime Report 2020. Illinois State Police. (2019). Crime in Illinois: Annual Uniform Crime Report 2019. Illinois State Police. (2018). Crime in Illinois: Annual Uniform Crime Report 2018. Illinois State Police. (2017). Crime in Illinois: Annual Uniform Crime Report 2017.Illinois State Police. (2016). Crime in Illinois: Annual Uniform Crime Report 2016. Illinois State Police. (2015). Crime in Illinois: Annual Uniform Crime Report 2015. Illinois State Police. (2014). Crime in Illinois: Annual Uniform Crime Report 2014.; Illinois State Police. (2012). Crime in Illinois: Annual Uniform Crime Report 2012.; Illinois State Police. (2011). Crime in Illinois: Annual Uniform Crime Report 2010-2011.; Illinois State Police. (2009). Crime in Illinois: Annual Uniform Crime Report 2009.; Illinois State Police. (2007). Crime in Illinois: Annual Uniform Crime Report 2007.; Illinois State Police. (2005). Crime in Illinois: Annual Uniform Crime Report 2005.; Illinois State Police. (2003). Crime in Illinois: Annual Uniform Crime Report 2003.; Illinois State Police. (2001). Crime in Illinois: Annual Uniform Crime Report 2001.; Illinois State Police. (1999). Crime in Illinois: Annual Uniform Crime Report 1999.; Illinois State Police. (1997). Crime in Illinois: Annual Uniform Crime Report 1997.

Comprehensive crime statistics for Los Angeles County including homicides, property crime, robbery, assault, and neighborhood-by-neighborhood breakdowns with five-year trend analysis.

The Division of Criminal Justice Services (DCJS) collects crime reports from more than 500 New York State police and sheriffs’ departments. DCJS compiles these reports as New York’s official crime statistics and submits them to the FBI under the National Uniform Crime Reporting (UCR) Program. UCR uses standard offense definitions to count crime in localities across America regardless of variations in crime laws from state to state. In New York State, law enforcement agencies use the UCR system to report their monthly crime totals to DCJS. The UCR reporting system collects information on seven crimes classified as Index offenses which are most commonly used to gauge overall crime volume. These include the violent crimes of murder/non-negligent manslaughter, forcible rape, robbery, and aggravated assault; and the property crimes of burglary, larceny, and motor vehicle theft. Police agencies may experience reporting problems that preclude accurate or complete reporting. The counts represent only crimes reported to the police but not total crimes that occurred.

The data are provided are the Maryland Statistical Analysis Center (MSAC), within the Governor's Office of Crime Control and Prevention (GOCCP). MSAC, in turn, receives these data from the Maryland State Police's annual Uniform Crime Reports.

This map shows the total crime index in the U.S. in 2020 in a multi-scale map (by state, county, ZIP Code, tract, and block group). The pop-up is configured to include the following information for each geography level:Total crime indexPersonal and Property crime indices Sub-categories of personal and property crime indicesThe values are all referenced by an index value. The index values for the US level are 100, representing average crime for the country. A value of more than 100 represents higher crime than the national average, and a value of less than 100 represents lower crime than the national average. For example, an index of 120 implies that crime in the area is 20 percent higher than the US average; an index of 80 implies that crime is 20 percent lower than the US average.Additional Esri Resources:Esri DemographicsU.S. 2020/2025 Esri Updated DemographicsEssential demographic vocabularyEsri's arcgis.com demographic map layersPermitted use of this data is covered in the DATA section of the Esri Master Agreement (E204CW) and these supplemental terms.

This dataset provides comprehensive data on violent and property crimes in Maryland counties from 1975 to the present. It includes various crime metrics such as murder, rape, robbery, aggravated assault, burglary, larceny theft, motor vehicle theft, and more.

Columns Information

JURISDICTION

• Description: County name in Maryland.
• Data Type: String

YEAR

• Description: Year of the data.
• Data Type: Integer

POPULATION

• Description: Population of the county.
• Data Type: Integer

MURDER

• Description: Number of murders.
• Data Type: Integer

RAPE

• Description: Number of rapes.
• Data Type: Integer

ROBBERY

• Description: Number of robberies.
• Data Type: Integer

AGG. ASSAULT

• Description: Number of aggravated assaults.
• Data Type: Integer

B & E

• Description: Number of burglaries (breaking and entering).
• Data Type: Integer

LARCENY THEFT

• Description: Number of larceny thefts.
• Data Type: Integer

M/V THEFT

• Description: Number of motor vehicle thefts.
• Data Type: Integer

GRAND TOTAL

• Description: Total number of crimes.
• Data Type: Integer

PERCENT CHANGE

• Description: Percent change in total crimes from the previous year.
• Data Type: Float

VIOLENT CRIME TOTAL

• Description: Total number of violent crimes.
• Data Type: Integer

VIOLENT CRIME PERCENT

• Description: Percent of violent crimes out of total crimes.
• Data Type: Float

VIOLENT CRIME PERCENT CHANGE

• Description: Percent change in violent crimes from the previous year.
• Data Type: Float

PROPERTY CRIME TOTALS

• Description: Total number of property crimes.
• Data Type: Integer

PROPERTY CRIME PERCENT

• Description: Percent of property crimes out of total crimes.
• Data Type: Float

PROPERTY CRIME PERCENT CHANGE

• Description: Percent change in property crimes from the previous year.
• Data Type: Float

OVERALL CRIME RATE PER 100,000 PEOPLE

• Description: Crime rate per 100,000 people.
• Data Type: Float

OVERALL PERCENT CHANGE PER 100,000 PEOPLE

• Description: Percent change in crime rate per 100,000 people from the previous year.
• Data Type: Float

VIOLENT CRIME RATE PER 100,000 PEOPLE

• Description: Violent crime rate per 100,000 people.
• Data Type: Float

VIOLENT CRIME RATE PERCENT CHANGE PER 100,000 PEOPLE

• Description: Percent change in violent crime rate per 100,000 people from the previous year.
• Data Type: Float

PROPERTY CRIME RATE PER 100,000 PEOPLE

• Description: Property crime rate per 100,000 people.
• Data Type: Float

PROPERTY CRIME RATE PERCENT CHANGE PER 100,000 PEOPLE

• Description: Percent change in property crime rate per 100,000 people from the previous year.
• Data Type: Float

MURDER PER 100,000 PEOPLE

• Description: Murder rate per 100,000 people.
• Data Type: Float

RAPE PER 100,000 PEOPLE

• Description: Rape rate per 100,000 people.
• Data Type: Float

ROBBERY PER 100,000 PEOPLE

• Description: Robbery rate per 100,000 people.
• Data Type: Float

AGG. ASSAULT PER 100,000 PEOPLE

• Description: Aggravated assault rate per 100,000 people.
• Data Type: Float

B & E PER 100,000 PEOPLE

• Description: Burglary (breaking and entering) rate per 100,000 people.
• Data Type: Float

LARCENY THEFT PER 100,000 PEOPLE

• Description: Larceny theft rate per 100,000 people.
• Data Type: Float

M/V THEFT PER 100,000 PEOPLE

• Description: Motor vehicle theft rate per 100,000 people.
• Data Type: Float

MURDER RATE PERCENT CHANGE PER 100,000 PEOPLE

• Description: Percent change in murder rate per 100,000 people from the previous year.
• Data Type: Float

RAPE RATE PERCENT CHANGE PER 100,000 PEOPLE

• Description: Percent change in rape rate per 100,000 people from the previous year.
• Data Type: Float

ROBBERY RATE PERCENT CHANGE PER 100,000 PEOPLE

• Description: Percent change in robbery rate per 100,000 people from the previous year.
• Data Type: Float

AGG. ASSAULT RATE PERCENT CHANGE PER 100,000 PEOPLE

• Description: Percent change in aggravated assault rate per 100,000 people from the previous year.
• Data Type: Float

B & E RATE PERCENT CHANGE PER 100,000 PEOPLE

• Description: Percent change in burglary (breaking and entering) rate per 100,000 people from the previous year.
• Data Type: Float

LARCENY THEFT RATE PERCENT CHANGE PER 100,000 PEOPLE

• Description: Percent change in larceny theft rate per 100,000 people from the previous year.
• Data Type: Float

M/V THEFT RATE PERCENT CHANGE PER 100,000 PEOPLE

• Description: Percent change in motor vehicle t...

Violent crime rate for each jurisdiction in Fulton County, Georgia (2014 and 2015)

The Division of Criminal Justice Services (DCJS) collects crime reports from more than 500 New York State police and sheriffs’ departments. DCJS compiles these reports as New York’s official crime statistics and submits them to the FBI under the National Uniform Crime Reporting (UCR) Program. UCR uses standard offense definitions to count crime in localities across America regardless of variations in crime laws from state to state. In New York State, law enforcement agencies use the UCR system to report their monthly crime totals to DCJS. The UCR reporting system collects information on seven crimes classified as Index offenses which are most commonly used to gauge overall crime volume. These include the violent crimes of murder/non-negligent manslaughter, forcible rape, robbery, and aggravated assault; and the property crimes of burglary, larceny, and motor vehicle theft. Police agencies may experience reporting problems that preclude accurate or complete reporting. The counts represent only crimes reported to the police but not total crimes that occurred.

Updated daily postings on Montgomery County’s open data website, dataMontgomery, provide the public with direct access to crime statistic databases - including raw data and search functions – of reported County crime. The data presented is derived from reported crimes classified according to the National Incident-Based Reporting System (NIBRS) of the Criminal Justice Information Services (CJIS) Division Uniform Crime Reporting (UCR) Program and documented by approved police incident reports. The data is compiled by “EJustice”, a respected law enforcement records-management system used by the Montgomery County Police Department and many other law enforcement agencies. To protect victims’ privacy, no names or other personal information are released. All data is refreshed on a quarterly basis to reflect any changes in status due to on-going police investigation.

dataMontgomery allows the public to query the Montgomery County Police Department's database of founded crime. The information contained herein includes all founded crimes reported after July 1st 2016 and entered to-date utilizing Uniform Crime Reporting (UCR) rules. Please note that under UCR rules multiple offenses may appear as part of a single founded reported incident, and each offense may have multiple victims. Please note that these crime reports are based on preliminary information supplied to the Police Department by the reporting parties. Therefore, the crime data available on this web page may reflect:

-Information not yet verified by further investigation -Information that may include attempted and reported crime -Preliminary crime classifications that may be changed at a later date based upon further investigation -Information that may include mechanical or human error -Arrest information [Note: all arrested persons are presumed innocent until proven guilty in a court of law.]

Update Frequency: Daily

With approximately 122.1 crimes per 1,000 population, Cleveland, in North East England, had the highest crime rate of all the police force areas in England and Wales in 2024/25. High crime rates are evident in other areas of northern England, such as West Yorkshire and Greater Manchester at 114.5 and 108.2, respectively. In the UK capital, London, the crime rate was 105.5 per 1,000 people. The lowest crime rate in England was in the relatively rural areas of Wiltshire in South West England, as well as North Yorkshire. Overall crime in England and Wales The number of crimes in England and Wales reached approximately 6.74 million in 2022/23, falling slightly to 6.66 million in 2023/24, and 6.59 million in 2024/25. Overall crime has been rising steadily across England and Wales for almost a decade, even when adjusted for population rises. In 2022/23, for example, the crime rate in England and Wales was 93.6, the highest since 2006/07. When compared with the rest of the United Kingdom, England and Wales is something of an outlier, as crime rates for Scotland and Northern Ireland have not followed the same trajectory of rising crime. Additionally, there has been a sharp increase in violent crimes and sexual offences since the mid-2010s in England and Wales. While theft offences have generally been falling, the number of shoplifting offences reached a peak of 530,640 in 2024/25. Troubled justice system under pressure Alongside rising crime figures, many indicators also signal that the justice system is getting pushed to breaking point. The percentage of crimes that are solved in England and Wales was just 5.7 percent in 2023, with sexual offences having a clearance rate of just 3.6 percent. Crimes are also taking far longer than usual to pass through the justice system. In 2022, it took an average of 407 days for a crown court case to reach a conclusion from the time of the offence, compared with 233 days in 2018. This is most likely related to the large backlog of cases in crown courts, which reached over 67,750 in 2023. Furthermore, prisons in England and Wales are dangerously overcrowded, with the government even releasing some prisoners early to address the issue.

Historical crime rates per 100,000 people, 1975 - present. In June 2017 we changed the update frequency of this dataset from annual to as-needed because sometimes there is a lag that is often 6 months after the annual date before the new data is available.

Crime severity index (violent, non-violent, youth) and weighted clearance rates (violent, non-violent), Canada, provinces, territories and Census Metropolitan Areas, 1998 to 2024.

The Division of Criminal Justice Services (DCJS) collects crime reports from more than 500 New York State police and sheriffs' departments. DCJS compiles these reports as New York's official crime statistics and submits them to the FBI under the National Uniform Crime Reporting (UCR) Program. UCR uses standard offense definitions to count crime in localities across America regardless of variations in crime laws from state to state. In New York State, law enforcement agencies use the UCR system to report their monthly crime totals to DCJS. The UCR reporting system collects information on seven crimes classified as Index offenses which are most commonly used to gauge overall crime volume. These include the violent crimes of murder/non-negligent manslaughter, forcible rape, robbery, and aggravated assault; and the property crimes of burglary, larceny, and motor vehicle theft. Police agencies may experience reporting problems that preclude accurate or complete reporting. The counts represent only crimes reported to the police but not total crimes that occurred. DCJS posts preliminary data in the spring and final data in the fall.

Crime Rate Trends per 100,000 in Chatham County from years 2017 to 2023.Data retrieved from https://www.ncsbi.gov/Services/Crime-Statistics/Crime-in-North-Carolina-Annual-SummariesIndex Crime includes the total number of violent crimes (murder, rape, robbery, and aggravated assault) and property crimes (burglary, larceny, and motor vehicle theft).This data was created as part of the Manager's Office Chatham County Performance Hub.

Dashboard to display crime rates for Chatham County Information Hub.

SANDAG provides an annual report on crime in the San Diego region. This dataset contains data from the 2009 through 2022 editions of the report. Data for 2023 is converted from California Incident Based Reporting System (CIBRS) data provided by SANDAG. Additional data comes from Arjis and DOJ OpenJustice. Some data for previous years reports is updated with new editions. "San Diego County" includes all cities and unincorporated areas in San Diego County. "Sheriff - Total" includes the contract cities and the unincorporated area served by the San Diego County Sheriff's Department. California and United States data come from the FBI's Annual Crime Reports.

In 2023/24 the crime rate of Northern Ireland stood at 55 crimes per 1,000 people, with the policing district of Belfast City having the highest crime rate of 96 crimes per 1,000 people.

The city states of Berlin, Hamburg and Bremen were the states with the three highest crime rates in Germany in 2024, while the federal state of Bavaria had the lowest. Urban areas generally have higher crime rates than rural ones, making it difficult to compare Germany's three city states with the much larger federal states, which typically cover quite large areas. The federal state with the highest crime rate was Bremen at 14,998 crimes per 100 thousand people, compared with the German average of 6,995.

For a comprehensive guide to this data and other UCR data, please see my book at ucrbook.comVersion 17 release notes:Adds data for 2020.Please note that the FBI has retired UCR data ending in 2020 data so this will be the last Offenses Known and Clearances by Arrest data they release. Changes .rda files to .rds. Please note that in 2020 the card_actual_pt variable always returns that the month was reported. This causes 2020 to report that all months are reported for all agencies because I use the card_actual_pt variable to measure how many months were reported. This variable is almost certainly incorrect since it is extremely unlikely that all agencies suddenly always report. However, I am keeping this incorrect value to maintain a consistent definition of how many months are missing (measuring missing months through card_actual_type, for example, gives different results for previous years so I don't want to change this). Version 16 release notes:Changes release notes description, does not change data.Version 15 release notes:Adds data for 2019.Please note that in 2019 the card_actual_pt variable always returns that the month was reported. This causes 2019 to report that all months are reported for all agencies because I use the card_actual_pt variable to measure how many months were reported. This variable is almost certainly incorrect since it is extremely unlikely that all agencies suddenly always report. However, I am keeping this incorrect value to maintain a consistent definition of how many months are missing (measuring missing months through card_actual_type, for example, gives different results for previous years so I don't want to change this). Version 14 release notes:Adds arson data from the UCR's Arson dataset. This adds just the arson variables about the number of arson incidents, not the complete set of variables in that dataset (which include damages from arson and whether structures were occupied or not during the arson.As arson is an index crime, both the total index and the index property columns now include arson offenses. The "all_crimes" variables also now include arson.Adds a arson_number_of_months_missing column indicating how many months were not reporting (i.e. missing from the annual data) in the arson data. In most cases, this is the same as the normal number_of_months_missing but not always so please check if you intend to use arson data.Please note that in 2018 the card_actual_pt variable always returns that the month was reported. This causes 2018 to report that all months are reported for all agencies because I use the card_actual_pt variable to measure how many months were reported. This variable is almost certainly incorrect since it is extremely unlikely that all agencies suddenly always report. However, I am keeping this incorrect value to maintain a consistent definition of how many months are missing (measuring missing months through card_actual_type, for example, gives different results for previous years so I don't want to change this).For some reason, a small number of agencies (primarily federal agencies) had the same ORI number in 2018 and I removed these duplicate agencies. Version 13 release notes: Adds 2018 dataNew Orleans (ORI = LANPD00) data had more unfounded crimes than actual crimes in 2018 so unfounded columns for 2018 are all NA. Version 12 release notes: Adds population 1-3 columns - if an agency is in multiple counties, these variables show the population in the county with the most people in that agency in it (population_1), second largest county (population_2), and third largest county (population_3). Also adds county 1-3 columns which identify which counties the agency is in. The population column is the sum of the three population columns. Thanks to Mike Maltz for the suggestion!Fixes bug in the crosswalk data that is merged to this file that had the incorrect FIPS code for Clinton, Tennessee (ORI = TN00101). Thanks for Brooke Watson for catching this bug!Adds a last_month_reported column which says which month was reported last. This is actually how the FBI defines number_of_months_reported so is a more accurate representation of that. Removes the number_of_months_reported variable as the name is misleading. You should use the last_month_reported or the number_of_months_missing (see below) variable instead.Adds a number_of_months_missin

The Department of Justice has the responsibility to collect, analyze, and report statistical data, which provide valid measures of crime and the criminal justice process to government and the citizens of California. The site contains crime data submitted by county and local law enforcement agencies.