ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · DEERFIELD, MA · 2022
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/massachusetts/deerfield/2022-annual-report
Yearly Traffic Safety Analysis
139 CRASHES IN
DEERFIELD, MA
2022
In 2022, Deerfield recorded 139 traffic crashes, a 31.1% increase from the 106 crashes reported in 2021. The total number of injuries also rose from 36 to 43 during this period. The most significant year-over-year shift was the occurrence of one fatal crash in 2022, whereas there were no traffic fatalities recorded in the prior year.
139
▲ 31.1%was 106
Total Crash Events
1
Persons Killed
43
▲ 19.4%was 36
Persons Injured
4
▲ 33.3%was 3
Hit-and-Run Crashes
Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 4 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 crashes in Deerfield are on an upward trend year-over-year. Total crashes increased by 31.1%, from 106 in 2021 to 139 in 2022. Similarly, the number of people injured in these incidents rose from 36 to 43.
4
Hit-and-Run Crashes — 2022
▲ 33.3% vs prior (3)
The number of hit-and-run incidents saw a minor increase, from 3 crashes in 2021 to 4 crashes in 2022. The corresponding hit-and-run rate remained nearly stable, increasing slightly from 2.8% of all crashes in the prior year to 2.9% in the current year. This indicates a minimal change in the trend of hit-and-run crashes.
Vulnerable Road User Casualties
0
Cyclists Killed
1
Motorists Killed
1
Cyclists Injured
42
Motorists Injured
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 temporal patterns of crashes shifted between the two periods. In 2022, the peak day for crashes moved to Friday with 24 incidents, compared to Tuesday in 2021 which had 21 incidents. The peak hour also shifted later in the day, from 2 p.m. in 2021 (11 crashes) to 4 p.m. in 2022 (17 crashes), suggesting a change in daily traffic risk patterns.
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
In 2022, Deerfield experienced one fatal crash resulting in one fatality, a significant change from zero in 2021. Despite the increase in total crashes and the occurrence of a fatality, the overall proportion of crashes involving any injury decreased from 28.3% in 2021 to 23.0% in 2022. Consequently, the share of crashes with no injuries increased from 68.9% of all incidents in 2021 to 74.1% in 2022.
Outcome by Severity (Crash Events)
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
The leading contributing factors saw a shift in ranking between the two years. In 2022, 'No improper driving' was the most cited factor with 47 crashes, a 62% increase in count from 29 crashes in 2021. Conversely, crashes attributed to 'Inattention' decreased by 21% in count, from 29 in 2021 to 23 in 2022, moving it from the top-ranked factor (tied) to the second-ranked. Crashes involving erratic operation and failure to yield both saw a slight increase in count from 8 to 9 incidents each.
Officer-Reported Primary Contributing Cause
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
Crashes in 2022 were more likely to occur on dry roads and in clear weather compared to the previous year. The share of crashes on dry surfaces increased from 72.6% in 2021 to 79.1% in 2022, while the proportion during clear weather rose from 61.3% to 70.5%. However, the percentage of crashes occurring in non-daylight conditions also increased, rising from 31.1% of all crashes in 2021 to 36.7% in 2022.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field
Vehicles & Demographics
The most common vehicle makes involved in crashes remained consistent, with Toyota, Honda, Chevrolet, and Ford leading in both years. Toyota-involved crashes increased from 26 to 34, and Honda-involved crashes rose from 21 to 28. An analysis of persons involved shows a notable shift in age demographics; the proportion of individuals aged 55-64 grew from 10.9% of all persons in 2021 to 15.6% in 2022. Conversely, the share of persons aged 65 and older decreased from 17.1% to 14.0%.
Top Vehicle Makes (206 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records
22 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (231 persons with recorded sex)
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
The distribution of crashes across speed zones remained relatively stable, with about 44% of incidents in both years occurring in zones with speed limits of 45 mph or higher. However, the absolute number of crashes in these higher-speed zones increased, including a rise from 18 to 25 crashes in 45 mph zones and from 3 to 7 crashes in 50 mph zones. The single fatal crash recorded in 2022 occurred in a 50 mph speed zone.
Fatal crashes by zone: 50 mph: 1 of 7 (14.286%)
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: DEERFIELD, MA
- Total crash records analyzed: 139
- Total persons involved: 250
- Total vehicles involved: 206
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). "DEERFIELD, 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/deerfield/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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2022-01-01 – 2022-12-31
Generated: June 21, 2026 · All rights reserved