On a whole, the outlook on crime in Ohio is fairly positive, as the state’s 2018 violent crime rate of 2.8 offenses per 1,000 people was about 24% lower than the national average, while its property crime rate was just a notch lower than nationwide levels. However, Ohio’s safest cities do even better, boasting low crime rates on par with the best of the nation.
Olmsted Township is Ohio’s safest community. The Cleveland-area suburb of around 13,400 recorded just 2 violent crimes in 2018, for a stunning violent crime rate of 0.15 per 1,000, while its property crime rate is about 10% of the national average.
The 2nd safest community in Ohio is Brecksville, another wealthy Cleveland suburb of similar size to #1 Olmsted Township. Brecksville’s violent and property crime rates resemble those of the first entry on the list, albeit just a notch higher.
#3 North Ridgeville is the 3rd straight Cleveland suburb in the ranking of Ohio’s safest cities. With a population of around 34,000, North Ridgeville is larger than #1 and #2 combined, yet still managed to record less than 10 violent crimes in 2018, for a remarkable violent crime rate of 0.26 per 1,000.
We move away from the Greater Cleveland area for #4 Poland Township, a community in Mahoning County located near the Pennsylvania border. Poland Township’s violent crime rate of 0.17 per 1,000 is just a hair higher than that of the top entry in the ranking.
Rounding out the list is Clearcreek Township (#5), a community of 15.7K that logged only 4 violent crimes and less than 50 property crimes in 2018.
Ohio’s Safest Cities
OH City Population Violent
crimeProperty
crimeLaw enforcement
employeesTotal crimes Crime rate per 1,000 Violent crimes per 1,000 Property crimes per 1,000 Law enforcement per 1,000
1 Olmsted Township 13425 2 28 16 30 2.23 0.15 2.09 1.19
2 Brecksville 13652 10 44 37 54 3.96 0.73 3.22 2.71
3 North Ridgeville 34025 9 97 47 106 3.12 0.26 2.85 1.38
4 Poland Township 11888 2 31 12 33 2.78 0.17 2.61 1.01
5 Clearcreek Township 15765 4 48 20 52 3.30 0.25 3.04 1.27
6 Seven Hills 11662 3 52 16 55 4.72 0.26 4.46 1.37
7 Springboro 18789 4 101 29 105 5.59 0.21 5.38 1.54
8 Brunswick 34954 22 173 52 195 5.58 0.63 4.95 1.49
9 Berea 18838 10 116 32 126 6.69 0.53 6.16 1.70
10 Hilliard 37184 35 242 76 277 7.45 0.94 6.51 2.04
11 Solon 22948 10 210 64 220 9.59 0.44 9.15 2.79
12 Dublin 48570 29 413 107 442 9.10 0.60 8.50 2.20
13 Mason 33583 6 264 52 270 8.04 0.18 7.86 1.55
14 Montgomery 10807 7 97 24 104 9.62 0.65 8.98 2.22
15 Aurora 16047 10 148 36 158 9.85 0.62 9.22 2.24
16 Powell 13455 6 109 22 115 8.55 0.45 8.10 1.64
17 Perrysburg Township 12935 8 133 31 141 10.90 0.62 10.28 2.40
18 Fairview Park 16248 16 140 29 156 9.60 0.98 8.62 1.78
19 Lyndhurst 13519 14 154 37 168 12.43 1.04 11.39 2.74
20 Shawnee Township 12061 12 104 18 116 9.62 0.99 8.62 1.49
21 Streetsboro 16411 10 215 37 225 13.71 0.61 13.10 2.25
22 North Olmsted 31653 13 397 62 410 12.95 0.41 12.54 1.96
23 Harrison 11513 2 156 25 158 13.72 0.17 13.55 2.17
24 Lakewood 50078 58 674 113 732 14.62 1.16 13.46 2.26
25 Bowling Green 32017 24 386 55 410 12.81 0.75 12.06 1.72
26 Struthers 10193 11 141 22 152 14.91 1.08 13.83 2.16
27 Strongsville 44819 12 642 91 654 14.59 0.27 14.32 2.03
28 Kent 30065 36 421 56 457 15.20 1.20 14.00 1.86
29 Amherst 12100 11 187 26 198 16.36 0.91 15.45 2.15
30 Cleveland Heights 44413 93 711 111 804 18.10 2.09 16.01 2.50
31 Blue Ash 12227 14 247 40 261 21.35 1.15 20.20 3.27
32 Gahanna 35596 31 588 71 619 17.39 0.87 16.52 1.99
33 Bellefontaine 13137 12 282 38 294 22.38 0.91 21.47 2.89
34 Wadsworth 23744 26 371 38 397 16.72 1.10 15.63 1.60
35 Greenville 12707 48 226 32 274 21.56 3.78 17.79 2.52
36 Delaware 39944 64 601 58 665 16.65 1.60 15.05 1.45
37 Tallmadge 17550 20 290 28 310 17.66 1.14 16.52 1.60
38 Ashland 20446 20 369 37 389 19.03 0.98 18.05 1.81
39 Macedonia 12056 3 271 31 274 22.73 0.25 22.48 2.57
40 Defiance 16620 25 313 33 338 20.34 1.50 18.83 1.99
41 Norwalk 16800 14 311 30 325 19.35 0.83 18.51 1.79
42 East Cleveland 17127 112 311 44 423 24.70 6.54 18.16 2.57
43 Conneaut 12616 19 256 25 275 21.80 1.51 20.29 1.98
44 Norton 12003 11 215 17 226 18.83 0.92 17.91 1.42
45 Fairborn 33604 106 673 72 779 23.18 3.15 20.03 2.14
46 Austintown 35029 42 667 56 709 20.24 1.20 19.04 1.60
47 Monroe 16310 15 407 41 422 25.87 0.92 24.95 2.51
48 West Chester Township 62063 64 1279 109 1343 21.64 1.03 20.61 1.76
49 Troy 25960 33 535 46 568 21.88 1.27 20.61 1.77
50 Eastlake 18111 7 399 32 406 22.42 0.39 22.03 1.77
51 West Carrollton 12893 36 261 24 297 23.04 2.79 20.24 1.86
52 Miamisburg 19954 49 443 42 492 24.66 2.46 22.20 2.10
53 Fairfield 42568 84 909 78 993 23.33 1.97 21.35 1.83
54 Brimfield Township 10330 5 232 18 237 22.94 0.48 22.46 1.74
55 Tiffin 17492 2 458 39 460 26.30 0.11 26.18 2.23
56 Union Township, Clermont County 48187 35 951 62 986 20.46 0.73 19.74 1.29
57 Bexley 13893 13 398 36 411 29.58 0.94 28.65 2.59
58 Huber Heights 37969 57 916 68 973 25.63 1.50 24.12 1.79
59 Reynoldsburg 38126 88 942 75 1030 27.02 2.31 24.71 1.97
60 Findlay 41351 90 1043 82 1133 27.40 2.18 25.22 1.98
61 Niles 18370 43 505 40 548 29.83 2.34 27.49 2.18
62 Van Wert 10631 30 319 28 349 32.83 2.82 30.01 2.63
63 Beavercreek 47203 40 1145 67 1185 25.10 0.85 24.26 1.42
64 Englewood 13474 14 400 26 414 30.73 1.04 29.69 1.93
65 Mount Vernon 16607 20 510 34 530 31.91 1.20 30.71 2.05
66 Cambridge 10369 14 396 32 410 39.54 1.35 38.19 3.09
67 Pierce Township 11669 10 307 17 317 27.17 0.86 26.31 1.46
68 Sidney 20537 54 688 45 742 36.13 2.63 33.50 2.19
69 Columbus 892576 4416 31512 2255 35928 40.25 4.95 35.30 2.53
70 Washington Court House 14210 23 489 27 512 36.03 1.62 34.41 1.90
71 Urbana 11337 22 363 19 385 33.96 1.94 32.02 1.68
72 Cincinnati 301952 2535 13710 1167 16245 53.80 8.40 45.40 3.86
73 Barberton 26060 94 833 44 927 35.57 3.61 31.96 1.69
74 Circleville 13993 43 530 31 573 40.95 3.07 37.88 2.22
75 Cleveland 384666 5576 16970 1675 22546 58.61 14.50 44.12 4.35
76 Toledo 275023 2333 10222 686 12555 45.65 8.48 37.17 2.49
77 Akron 197690 1704 7159 475 8863 44.83 8.62 36.21 2.40
78 Brooklyn 10759 18 566 35 584 54.28 1.67 52.61 3.25
79 Fairfield Township 22789 19 681 23 700 30.72 0.83 29.88 1.01
80 Dayton 140094 1291 6323 424 7614 54.35 9.22 45.13 3.03
81 Mansfield 45941 237 2087 118 2324 50.59 5.16 45.43 2.57
82 Lancaster 40498 116 1687 79 1803 44.52 2.86 41.66 1.95
83 Warren 39280 245 1500 75 1745 44.42 6.24 38.19 1.91
84 Heath 10774 25 546 27 571 53.00 2.32 50.68 2.51
85 Steubenville 17913 55 958 44 1013 56.55 3.07 53.48 2.46
86 Newark 49687 152 2166 78 2318 46.65 3.06 43.59 1.57
87 Fremont 16125 20 870 33 890 55.19 1.24 53.95 2.05
88 Trotwood 24380 165 893 31 1058 43.40 6.77 36.63 1.27
89 Springfield 59016 336 3141 135 3477 58.92 5.69 53.22 2.29
90 Canton 70605 845 3790 188 4635 65.65 11.97 53.68 2.66
91 American Township 12094 2 144 1 146 12.07 0.17 11.91 0.08
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.
