Yearly Traffic Safety Analysis

45 CRASHES IN
HATFIELD, MA
2024

All metrics benchmarked against2023

In 2024, Hatfield recorded 45 total crashes, a 12.5% increase from the 40 crashes documented in 2023. While the number of fatalities remained stable at one death in each period, the total number of persons injured doubled from 7 in 2023 to 14 in 2024. This sharp rise in injuries represents the most notable year-over-year shift in crash outcomes.

45

12.5%was 40

Total Crash Events

1

Persons Killed

14

100.0%was 7

Persons Injured

1

-66.7%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. 1 crash with unreported severity is not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash trends in Hatfield are increasing year-over-year. Total reported crashes rose by 12.5%, from 40 incidents in 2023 to 45 in 2024. This increase was accompanied by a 100% rise in the number of people injured, which grew from 7 to 14, while fatalities held constant at one person in both years.

1

Hit-and-Run Crashes — 2024

-66.7% vs prior (3)

Hit-and-run incidents showed a significant downward trend. The total count of hit-and-run crashes fell from 3 in 2023 to 1 in 2024. As a result, the hit-and-run rate as a percentage of all crashes decreased from 7.5% in the prior period to 2.2% in the current period.

Vulnerable Road User Casualties

1

Motorists Killed

Prior: 0%

14

Motorists Injured

Prior: 7100.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Temporal crash patterns shifted between the two periods. While Saturday was the peak day for crashes in both 2023 (8 crashes) and 2024 (10 crashes), the peak hour for incidents moved from 7 a.m. in the prior year to 1 p.m. in the current year. Crashes in 2024 also showed a higher concentration on weekends, with Friday and Saturday accounting for 19 of the 45 total incidents, compared to a more even distribution across weekdays in 2023.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While the fatal crash rate remained relatively stable, decreasing slightly from 2.5% in 2023 to 2.2% in 2024, the severity of outcomes worsened in terms of non-fatal injuries. The total number of persons injured doubled from 7 to 14 year-over-year. The proportion of crashes resulting in some form of injury (fatal, serious, minor, or possible) increased from 17.5% of all crashes in 2023 to 20% in 2024.

Outcome by Severity (Crash Events)

Fatal1fatal crashes2.2%
0.0%prior 1
Minor Injury4minor injury crashes8.9%
0.0%prior 4
Possible Injury3possible injury crashes6.7%
200.0%prior 1
No Injury36no injury crashes80%
9.1%prior 33

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record

Top Contributing Factors

In both years, 'No improper driving' was the most common factor listed, accounting for 19 crashes in 2023 and 20 in 2024. The most significant change was a 300% increase in the count of crashes attributed to 'Inattention,' which rose from 1 incident in 2023 to 4 in 2024. Conversely, crashes involving 'Fatigued/asleep' and 'Operating defective equipment' each decreased in count from 2 incidents in the prior year to 1 in the current year.

Officer-Reported Primary Contributing Cause

No improper driving20 (44.4%)5.3%prior 19
Inattention4 (8.9%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (4.4%)
Followed too closely2 (4.4%)
Failed to yield right of way2 (4.4%)
Visibility obstructed2 (4.4%)
Driving too fast for conditions2 (4.4%)
Wrong side or wrong way1 (2.2%)
Made an improper turn1 (2.2%)
Exceeded authorized speed limit1 (2.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

A notable shift occurred in lighting conditions, with 'Daylight' crashes increasing from 15 incidents (37.5% of total) in 2023 to 27 (60% of total) in 2024. Correspondingly, crashes in 'Dark - roadway not lighted' conditions decreased from 17 to 12. Road surface and weather conditions remained broadly similar, with 'Dry' roads and 'Clear' weather being the predominant conditions in both periods.

Weather

Clear29 (65.9%)
3.6%prior 28
Cloudy4 (9.1%)
-33.3%prior 6
Clear/Clear4 (9.1%)
Snow2 (4.5%)
Cloudy/Rain2 (4.5%)
Rain2 (4.5%)
Clear/Cloudy1 (2.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash

Lighting

Daylight27 (60.0%)
80.0%prior 15
Dark - roadway not lighted12 (26.7%)
-29.4%prior 17
Dark - lighted roadway3 (6.7%)
Dawn2 (4.4%)
-66.7%prior 6
Dusk1 (2.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field

Road Surface

Dry37 (82.2%)
15.6%prior 32
Wet5 (11.1%)
-28.6%prior 7
Snow3 (6.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field

Vehicles & Demographics

Demographics of vehicles and persons involved in crashes showed distinct changes. The most common vehicle make involved shifted from Honda (8 vehicles) in 2023 to Toyota (9 vehicles) in 2024. Regarding persons involved, the 35-44 age group saw its representation more than double from 12 individuals in 2023 to 25 in 2024, while the number of persons in the 26-34 age group decreased from 23 to 9.

Top Vehicle Makes (69 vehicles)

1
TOYOTA9 (13%)
28.6%prior 7
2
FORD8 (11.6%)
33.3%prior 6
3
SUBARU6 (8.7%)
4
HONDA6 (8.7%)
-25.0%prior 8
5
HYUNDAI5 (7.2%)
6
NISSAN4 (5.8%)
7
CHEVROLET4 (5.8%)
8
VOLVO3 (4.3%)
9
AUDI2 (2.9%)
10
GMC2 (2.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records

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

Sex Distribution (74 persons with recorded sex)

Male38 (51.4%)
2.7%prior 37
Female36 (48.6%)
24.1%prior 29

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Person-level records linked to crash events

Speed Limit Zones

The distribution of crashes across different speed zones remained largely consistent year-over-year. The 65 mph zone accounted for the majority of incidents in both periods, with 25 crashes in 2023 and 26 in 2024. The single fatal crash recorded in 2024 occurred in a 65 mph zone. There was no significant shift in crash locations toward higher or lower speed zones between the two years.

Fatal crashes by zone: 65 mph: 1 of 26 (3.846%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · 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: 2024-01-01 through 2024-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-01-01 through 2024-12-31 (366 days)
  • Geographic scope: HATFIELD, MA
  • Total crash records analyzed: 45
  • Total persons involved: 85
  • Total vehicles involved: 69

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). "HATFIELD, MA Crash Intelligence Report: 2024." Published June 21, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/hatfield/2024-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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Hatfield, MA Crash Report — 2024 | ThatCarHitMe.com