Piastri leads McLaren one-two in Imola practice

Emilia-Romagna Grand Prix

Venue: Imola Dates: 16-18 May Race start: 14:00 BST on Sunday

Coverage: Live commentary of all sessions on BBC Radio 5 Sports Extra; live text updates on BBC Sport website and app

Oscar Piastri led Lando Norris to a McLaren one-two in first practice at the Emilia-Romagna Grand Prix.

Less than a 10th of a second covered the top five cars, as Williams driver Carlos Sainz took third place ahead of Mercedes' George Russell and Ferrari's Lewis Hamilton.

The session was brought to a premature end two minutes before the scheduled end when Sauber's Gabriel Bortoleto crashed at the second Rivazza corner.

The Brazilian lost control at the right-hander, effectively the last corner on the lap, when he got a snap of oversteer mid-corner. The car flicked into the barriers pretty much front-on and damaged his front wing and nose.

Piastri, leading the world championship from Norris by 16 points after four wins in the first six races, was 0.032 seconds ahead of his team-mate at the top of the times.

Alpine's Pierre Gasly was sixth fastest from the Red Bull of reigning champion Max Verstappen.

Red Bull have some upgrades on the car, including a revised side-pod shape and radiator inlet, but Verstappen was complaining of a lack of rear grip over the radio as he lapped 0.36secs off the pace.

The demands of the old-school Imola circuit caught out a number of drivers, as Hamilton and his team-mate Charles Leclerc were among those who ran wide or bounced over the kerbs at one of the three chicanes that populate the historic track.

Another was Williams' Alex Albon, who was eighth fastest ahead of the Saubers of Bortoleto and Nico Hulkenberg.

Lance Stroll, driving a heavily upgraded Aston Martin as the team seek to improve their performance after a poor start to the year, was 11th fastest.

The Canadian was 0.089secs and three places ahead of team-mate Fernando Alonso, who is running the car in its previous specification on Friday for a back-to-back comparison of data.