
At the state level, Massachusetts recorded very respectable crime figures in 2018: its violent crime rate is 8% below the national rate and its property crime rate is 57% of the national level. However, this doesn’t give the full picture, as many of the Bay State’s individual cities have nearly nonexistent levels of crime: the state’s cities earned 6 spots in the ranking of the 10 safest cities in the nation.
Wayland is the safest city in Massachusetts, and perhaps the entire country. The Middlesex County city has earned recognition for its excellent public education system, as well as for being a great place to raise a family, and its low crime no doubt contributes to this status. Wayland recorded just one violent crime and one property crime in 2018, resulting in crime rates beyond comparison.
Hopkinton is Massachusetts’ #2 safest city. Best known as the starting point of the Boston Marathon, Hopkinton logged just 2 violent crimes in 2018, and posted a property crime rate less than 10% of the national level.
Massachusetts’ 3rd safest community is Clinton, a Worcester County town of 14,000 first settled in 1654. Clinton logged less than 30 total crimes in 2018, a rare feat for any municipality.
4th on the list is Norfolk, which, like #1 Wayland, recorded a single violent crime in 2018. In addition to its 11.8K residents, the city is home to 4 state prisons.
Norton (#5) closes out the list of Massachusetts’ 5 safest cities. The community of nearly 20K recorded just 14 violent crimes and 23 property crimes in 2018.
Massachusetts’ Safest Cities
MA | City | Population | Violent crime | Property crime | Law enforcement employees | Total crimes | Crime rate per 1,000 | Violent crimes per 1,000 | Property crimes per 1,000 | Law enforcement per 1,000 |
---|---|---|---|---|---|---|---|---|---|---|
1 | Wayland | 14088 | 1 | 1 | 31 | 2 | 0.14 | 0.07 | 0.07 | 2.20 |
2 | Hopkinton | 18516 | 2 | 30 | 37 | 32 | 1.73 | 0.11 | 1.62 | 2.00 |
3 | Clinton | 14009 | 10 | 18 | 38 | 28 | 2.00 | 0.71 | 1.28 | 2.71 |
4 | Norfolk | 11872 | 1 | 21 | 26 | 22 | 1.85 | 0.08 | 1.77 | 2.19 |
5 | Norton | 19983 | 14 | 23 | 35 | 37 | 1.85 | 0.70 | 1.15 | 1.75 |
6 | Franklin | 33156 | 5 | 85 | 54 | 90 | 2.71 | 0.15 | 2.56 | 1.63 |
7 | Southborough | 10187 | 11 | 23 | 23 | 34 | 3.34 | 1.08 | 2.26 | 2.26 |
8 | Shrewsbury | 37631 | 4 | 114 | 61 | 118 | 3.14 | 0.11 | 3.03 | 1.62 |
9 | Holliston | 14924 | 12 | 40 | 29 | 52 | 3.48 | 0.80 | 2.68 | 1.94 |
10 | Sharon | 18373 | 13 | 51 | 33 | 64 | 3.48 | 0.71 | 2.78 | 1.80 |
11 | Lexington | 34050 | 8 | 113 | 63 | 121 | 3.55 | 0.23 | 3.32 | 1.85 |
12 | North Reading | 15849 | 16 | 44 | 33 | 60 | 3.79 | 1.01 | 2.78 | 2.08 |
13 | Groton | 11462 | 11 | 36 | 26 | 47 | 4.10 | 0.96 | 3.14 | 2.27 |
14 | Bedford | 14319 | 7 | 58 | 37 | 65 | 4.54 | 0.49 | 4.05 | 2.58 |
15 | Scituate | 18761 | 15 | 63 | 37 | 78 | 4.16 | 0.80 | 3.36 | 1.97 |
16 | Sudbury | 19037 | 21 | 63 | 40 | 84 | 4.41 | 1.10 | 3.31 | 2.10 |
17 | Wellesley | 29681 | 12 | 124 | 55 | 136 | 4.58 | 0.40 | 4.18 | 1.85 |
18 | Marshfield | 25922 | 33 | 83 | 43 | 116 | 4.47 | 1.27 | 3.20 | 1.66 |
19 | Andover | 36324 | 7 | 173 | 73 | 180 | 4.96 | 0.19 | 4.76 | 2.01 |
20 | Billerica | 44482 | 37 | 171 | 77 | 208 | 4.68 | 0.83 | 3.84 | 1.73 |
21 | Norwell | 11144 | 9 | 51 | 26 | 60 | 5.38 | 0.81 | 4.58 | 2.33 |
22 | Arlington | 45876 | 34 | 191 | 81 | 225 | 4.90 | 0.74 | 4.16 | 1.77 |
23 | Pepperell | 12234 | 13 | 41 | 17 | 54 | 4.41 | 1.06 | 3.35 | 1.39 |
24 | Reading | 26293 | 5 | 144 | 59 | 149 | 5.67 | 0.19 | 5.48 | 2.24 |
25 | Grafton | 18900 | 21 | 61 | 24 | 82 | 4.34 | 1.11 | 3.23 | 1.27 |
26 | Needham | 31264 | 16 | 144 | 54 | 160 | 5.12 | 0.51 | 4.61 | 1.73 |
27 | Littleton | 10292 | 9 | 56 | 27 | 65 | 6.32 | 0.87 | 5.44 | 2.62 |
28 | Pembroke | 18446 | 15 | 86 | 33 | 101 | 5.48 | 0.81 | 4.66 | 1.79 |
29 | Marblehead | 20652 | 20 | 102 | 43 | 122 | 5.91 | 0.97 | 4.94 | 2.08 |
30 | Concord | 19459 | 8 | 111 | 42 | 119 | 6.12 | 0.41 | 5.70 | 2.16 |
31 | Dudley | 11807 | 24 | 33 | 15 | 57 | 4.83 | 2.03 | 2.79 | 1.27 |
32 | Ipswich | 14107 | 14 | 74 | 30 | 88 | 6.24 | 0.99 | 5.25 | 2.13 |
33 | Maynard | 10744 | 21 | 52 | 27 | 73 | 6.79 | 1.95 | 4.84 | 2.51 |
34 | Melrose | 28552 | 15 | 146 | 48 | 161 | 5.64 | 0.53 | 5.11 | 1.68 |
35 | Belmont | 26700 | 5 | 167 | 59 | 172 | 6.44 | 0.19 | 6.25 | 2.21 |
36 | Ashland | 17860 | 22 | 90 | 33 | 112 | 6.27 | 1.23 | 5.04 | 1.85 |
37 | Sandwich | 20248 | 23 | 102 | 36 | 125 | 6.17 | 1.14 | 5.04 | 1.78 |
38 | Hudson | 20060 | 48 | 90 | 42 | 138 | 6.88 | 2.39 | 4.49 | 2.09 |
39 | Acton | 24038 | 26 | 156 | 54 | 182 | 7.57 | 1.08 | 6.49 | 2.25 |
40 | Beverly | 42114 | 42 | 243 | 73 | 285 | 6.77 | 1.00 | 5.77 | 1.73 |
41 | Lynnfield | 13141 | 4 | 93 | 27 | 97 | 7.38 | 0.30 | 7.08 | 2.05 |
42 | Rehoboth | 12268 | 8 | 97 | 34 | 105 | 8.56 | 0.65 | 7.91 | 2.77 |
43 | North Andover | 31394 | 35 | 173 | 51 | 208 | 6.63 | 1.11 | 5.51 | 1.62 |
44 | Medway | 13406 | 21 | 73 | 24 | 94 | 7.01 | 1.57 | 5.45 | 1.79 |
45 | Belchertown | 15165 | 25 | 78 | 25 | 103 | 6.79 | 1.65 | 5.14 | 1.65 |
46 | Newton | 89505 | 58 | 629 | 188 | 687 | 7.68 | 0.65 | 7.03 | 2.10 |
47 | Hanson | 10858 | 30 | 58 | 25 | 88 | 8.10 | 2.76 | 5.34 | 2.30 |
48 | Spencer | 11989 | 18 | 69 | 21 | 87 | 7.26 | 1.50 | 5.76 | 1.75 |
49 | Northborough | 15124 | 0 | 111 | 27 | 111 | 7.34 | 0.00 | 7.34 | 1.79 |
50 | Acushnet | 10576 | 19 | 69 | 22 | 88 | 8.32 | 1.80 | 6.52 | 2.08 |
Methodology
To identify the safest cities, we reviewed the most recent FBI Uniform Crime Report statistics. We eliminated any cities that failed to submit a complete crime report to the FBI and cities with populations under 10,000. This left 3,381 cities (out of a total of 9,251).
There are two broad classifications of crimes: violent crimes and non-violent crimes. According to the FBI, “Violent crime is composed of four offenses: murder and non-negligent manslaughter, rape, robbery, and aggravated assault. Violent crimes are defined in the UCR Program as those offenses that involve force or threat of force. Property crime includes the offenses of burglary, larceny-theft, motor vehicle theft, and arson. The object of the theft-type offenses is the taking of money or property, but there is no force or threat of force against the victims. ”
We computed the total number of crimes reported by each city by adding violent crimes and property crimes. We then created a crime rate as the number of crimes per 1,000 population. Then we transformed the total crime rate variable so that the skewness was reduced and normalized.
Data from 2,831 law enforcement agencies was then collected to determine police adequacy (TotalCrimes / Number of police employees). We consider that the smaller the police adequacy statistic is, the safer the city is. This variable was also transformed and normalized.
Finally, the two variables were combined to create a safety score for each city.