Yearly Traffic Safety Analysis

280 CRASHES IN
WILBRAHAM, MA
2022

All metrics benchmarked against2021

In 2022, Wilbraham recorded 280 total vehicle crashes, a 15.2% increase from the 243 crashes in 2021. While total collisions rose and fatalities increased from two to three, the number of persons injured decreased by 25% from 76 to 57. One of the most significant changes was a 240% increase in crashes involving speeding, which rose from 5 incidents in 2021 to 17 in 2022.

280

15.2%was 243

Total Crash Events

3

50.0%was 2

Persons Killed

57

-25.0%was 76

Persons Injured

2

-50.0%was 4

Hit-and-Run Crashes

Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 3 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall traffic collision trends in Wilbraham show a notable increase year-over-year. Total crashes rose by 15.2%, from 243 in 2021 to 280 in 2022, and the number of fatalities increased from two to three. In contrast, the number of reported injuries saw a significant 25% decline, falling from 76 to 57 over the same period.

2

Hit-and-Run Crashes — 2022

-50.0% vs prior (4)

The number of hit-and-run incidents decreased by 50% year-over-year, falling from 4 crashes in 2021 to 2 in 2022. This downward trend is also reflected in the hit-and-run rate as a percentage of total crashes, which declined from 1.6% to 0.7% over the same period.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 00.0%

3

Motorists Killed

Prior: 250.0%

2

Cyclists Injured

Prior: 1100.0%

55

Motorists Injured

Prior: 74-25.7%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The timing of crashes shifted between the two periods. In 2022, the peak day for crashes was Friday with 49 incidents, a change from Monday (47 incidents) in the prior year. Similarly, the peak hour for collisions moved from the late morning at 11 AM (24 crashes) in 2021 to the mid-afternoon at 2 PM (34 crashes) in 2022.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While total crashes increased, the proportion of crashes resulting in injury decreased from 22.6% in 2021 to 15.4% in 2022, driven primarily by a drop in the share of minor injury crashes. However, the severity of outcomes worsened at the highest level, with the fatal crash rate increasing from 0.82% to 1.07%. In 2022, there were 3 fatal crashes, up from 2 in the previous year.

Outcome by Severity (Crash Events)

Fatal3fatal crashes1.1%
50.0%prior 2
Serious Injury3serious injury crashes1.1%
50.0%prior 2
Minor Injury28minor injury crashes10%
-31.7%prior 41
Possible Injury12possible injury crashes4.3%
0.0%prior 12
No Injury231no injury crashes82.5%
29.8%prior 178

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Most severe injury per crash record

Top Contributing Factors

Inattention remained a leading contributing factor, with incidents increasing in count from 42 to 53 year-over-year. Crashes attributed to 'Failed to yield right of way' also grew, rising from 19 to 27 incidents. While the top three factors were consistent across both years, there was a notable increase in crashes related to speeding, with 'Driving too fast for conditions' increasing from 3 to 8 incidents and 'Exceeded authorized speed limit' increasing from 1 to 4 incidents.

Officer-Reported Primary Contributing Cause

No improper driving67 (23.9%)15.5%prior 58
Inattention53 (18.9%)26.2%prior 42
Followed too closely27 (9.6%)0.0%prior 27
Failed to yield right of way27 (9.6%)42.1%prior 19
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner18 (6.4%)-14.3%prior 21
Failure to keep in proper lane or running off road16 (5.7%)60.0%prior 10
Disregarded traffic signs, signals, road markings10 (3.6%)66.7%prior 6
Distracted9 (3.2%)
Driving too fast for conditions8 (2.9%)
Other improper action8 (2.9%)-27.3%prior 11

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The distribution of crashes across lighting and road surface conditions remained stable year-over-year, with over 70% of incidents in both periods occurring during daylight and on dry roads. There was a slight shift in weather conditions, with the share of crashes occurring in clear weather increasing from 66.7% in 2021 to 70.4% in 2022. Consequently, the proportion of crashes in adverse weather conditions like rain or snow saw a corresponding decrease.

Weather

Clear197 (70.6%)
21.6%prior 162
Cloudy24 (8.6%)
4.3%prior 23
Rain18 (6.5%)
-10.0%prior 20
Cloudy/Rain9 (3.2%)
80.0%prior 5
Snow7 (2.5%)
-12.5%prior 8
Clear/Other5 (1.8%)
-37.5%prior 8
Rain/Sleet, hail (freezing rain or drizzle)3 (1.1%)
Snow/Sleet, hail (freezing rain or drizzle)2 (0.7%)
Cloudy/Snow2 (0.7%)
Fog, smog, smoke2 (0.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash

Lighting

Daylight199 (71.3%)
15.7%prior 172
Dark - lighted roadway44 (15.8%)
15.8%prior 38
Dark - roadway not lighted21 (7.5%)
5.0%prior 20
Dusk9 (3.2%)
Dawn5 (1.8%)
-16.7%prior 6
Dark - unknown roadway lighting1 (0.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field

Road Surface

Dry217 (77.8%)
13.6%prior 191
Wet39 (14.0%)
14.7%prior 34
Snow13 (4.7%)
8.3%prior 12
Ice9 (3.2%)
Water (standing, moving)1 (0.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field

Vehicles & Demographics

The top three vehicle makes involved in crashes—Toyota, Honda, and Ford—remained the same across both years, though Toyota (68 vehicles) surpassed Honda (63 vehicles) for the top spot in 2022. Analysis of person age distribution shows that the 16-20 age group was the most frequently involved in both years. However, the largest year-over-year increases were seen in the 26-34 age group, which grew from 57 to 77 persons involved, and the 35-44 group, which grew from 48 to 76 persons.

Top Vehicle Makes (452 vehicles)

1
TOYOTA68 (15%)
44.7%prior 47
2
HONDA63 (13.9%)
26.0%prior 50
3
FORD57 (12.6%)
26.7%prior 45
4
CHEVROLET34 (7.5%)
13.3%prior 30
5
NISSAN33 (7.3%)
0.0%prior 33
6
JEEP20 (4.4%)
0.0%prior 20
7
HYUNDAI16 (3.5%)
-11.1%prior 18
8
SUBARU16 (3.5%)
-20.0%prior 20
9
MERCEDES-BENZ11 (2.4%)
22.2%prior 9
10
VOLKSWAGEN11 (2.4%)
0.0%prior 11

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records

20 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (507 persons with recorded sex)

Male271 (53.5%)
13.4%prior 239
Female236 (46.5%)
15.7%prior 204

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Person-level records linked to crash events

Speed Limit Zones

In both 2021 and 2022, the highest number of crashes occurred in 35 mph zones, with the count increasing from 107 to 131. A notable shift occurred in the location of fatal crashes; in 2021, fatalities were recorded in 40 mph and 65 mph zones. In 2022, two of the three fatal crashes occurred in lower speed zones of 25 mph and 35 mph, suggesting a shift of the most severe incidents to roads with lower posted speeds.

Fatal crashes by zone: 25 mph: 1 of 14 (7.143%) · 35 mph: 1 of 131 (0.763%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Posted speed limit at crash location

Data Sources & Methodology

Primary Data Source

All crash data in this report is sourced from Massachusetts Crash Data (MassDOT CDV), accessed programmatically via the Arcgis_yearly Open Data API (SODA). This dataset contains official police-reported motor vehicle traffic crash records maintained by the reporting jurisdiction's law enforcement agency. Records are published to the open data portal by the municipality and are subject to the portal's terms of use.

Data Retrieval

  • Access method: Arcgis_yearly Open Data API (SoQL queries)
  • Data format: Structured JSON via REST API
  • Record types queried: Crash events, person records, and vehicle unit records
  • Date filter applied: 2022-01-01 through 2022-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-01-01 through 2022-12-31 (365 days)
  • Geographic scope: WILBRAHAM, MA
  • Total crash records analyzed: 280
  • Total persons involved: 532
  • Total vehicles involved: 452

Analytical Methodology

  • Severity classification: Uses the KABCO injury scale (K=Fatal, A=Incapacitating injury, B=Non-incapacitating injury, C=Possible injury, O=No injury/property damage only), the standard classification in U.S. Model Minimum Uniform Crash Criteria (MMUCC). Severity is assigned per crash event based on the most severe injury in that crash. A single fatal crash (K) may involve multiple fatalities; therefore the "Persons Killed" count in the headline KPIs may differ from the "Fatal" crash count in the severity breakdown.
  • Contributing factors: Reflect the officer-determined primary contributory cause recorded at the time of the crash report. These are preliminary determinations and may not reflect final investigation findings.
  • Hit-and-run classification: Based on the hit-and-run indicator field in the official crash report, as determined by the responding officer at the scene.
  • Temporal analysis: Day-of-week and hour-of-day distributions are computed from the crash date/time timestamp in each record.
  • Demographics: Age and sex distributions are drawn from person-level records linked to each crash event. A single crash may involve multiple persons.
  • Vehicle data: Make information is drawn from vehicle unit records linked to each crash event.
  • AI commentary: Narrative sections are generated by Google Gemini (large language model) based on the structured data. Commentary is descriptive, not predictive, and should not be interpreted as expert opinion.

Limitations & Disclaimers

  • Only crashes reported to and documented by law enforcement are included. Minor incidents, unreported crashes, and near-misses are not captured in this dataset.
  • Data reflects conditions at the time of the initial police report and may be subject to subsequent corrections, reclassifications, or supplements by the reporting agency.
  • Open data portal records may experience a publication lag - recently occurring crashes may not yet appear in the dataset at the time of report generation.
  • AI-generated commentary is produced by a large language model and is intended to highlight patterns in the data. It does not constitute legal, medical, or professional analysis.
  • Percentages are calculated from reported data and are subject to rounding.

Non-Affiliation Disclosure

This report is produced independently by ThatCarHitMe.com (Injuria.ai). It is not affiliated with, endorsed by, or produced in partnership with any law enforcement agency, municipal government, state department of transportation, or the National Highway Traffic Safety Administration (NHTSA). Data is sourced from publicly available government open data portals.

Data License

The underlying crash data is provided under the municipality's Open Data Terms of Use and is made available to the public for unrestricted use. This analysis and report is © 2026 Injuria.ai and may be cited with attribution using the suggested citation below.

Corrections & Feedback

If you believe any data in this report is inaccurate or have questions about our methodology, please contact: data@injuria.ai. We are committed to accuracy and will issue corrections promptly.

Suggested Citation

ThatCarHitMe.com (Injuria.ai). "WILBRAHAM, MA Crash Intelligence Report: 2022." Published June 21, 2026. Reporting period: 2022-01-01 to 2022-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/wilbraham/2022-annual-report

About the Publisher

ThatCarHitMe.com is a crash data intelligence platform developed by Injuria.ai, a legal technology company specializing in traffic safety analytics. We aggregate and analyze publicly available government crash data to produce structured intelligence reports for communities, researchers, journalists, and legal professionals. Our reports combine programmatic data retrieval from official open data portals with AI-assisted narrative analysis.

Questions about this report's data or methodology: data@injuria.ai

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Wilbraham, MA Crash Report — 2022 | ThatCarHitMe.com