Price Accuracy
Sale price divided by asking price — expressed as a percentage. The one metric that tells you whether an agent is a skilled valuer or just chasing the instruction. The stat no agent publishes voluntarily.
What avg_sale_percent means
For each agent, the API returns the average ratio of achieved sale price ÷ original asking price × 100. Calculated across all completed sales in the period and radius.
Sale price exactly matched asking price. Rare — usually means the agent under-valued or the market was very hot.
1.8% below asking — typical for well-priced properties. This is what top agents in the area achieve.
5.9% below asking — agent over-valued to win the instruction, then ground the vendor down. A classic pattern.
Response fields
Price accuracy fields in results[] per agent.
What it reveals
Agents who consistently achieve 94-95% have likely over-valued to win the listing — then negotiated the seller down. avg_sale_percent exposes this pattern objectively.
A 2% difference in accuracy on a £500k property is £10,000 in the vendor's pocket. Price accuracy is the single most financially significant agent metric.
High accuracy requires strong buyer qualification and negotiation — not just portal listings. It separates full-service agents from passive ones.
Compare accuracy across time windows. Rising accuracy indicates a seller's market; falling accuracy signals increasing buyer leverage and longer negotiation periods.
API example
curl https://api.homedata.co.uk/api/agent_stats/100023336956/ \ -H "Authorization: Api-Key YOUR_KEY"
{
"count": 12,
"results": [
{
"agent_name": "Hamptons",
"sales_count": 38,
"avg_sale_percent": 98.5,
"avg_sold_price": 54000000,
"avg_time_to_sstc": 38
},
{
"agent_name": "Savills Bristol",
"sales_count": 71,
"avg_sale_percent": 98.2,
"avg_sold_price": 48500000,
"avg_time_to_sstc": 34
}
]
}