Liverpool vs Real Madrid prediction for Champions League fixture as supercomputer calculates chances

Liverpool will reignite its UEFA Champions League rivalry with Real Madrid on Tuesday night when the Spanish side visits Anfield in the first leg of a last-16 tie.

While the Reds have endured a somewhat underwhelming Premier League campaign to date, supporters know that tipping Liverpool for defeat on a European night under the lights on Merseyside is not a wise act.

Back-to-back triumphs in their last two league outings over Everton and Newcastle respectively have only enhanced confidence in Jürgen Klopp's squad. They will, however, be required to end a 14-year hoodoo if a first-leg lead is to be achieved.

Klopp will have to look all the way back to 2009 in his search for inspiration, when goals from Fernando Torres, Steven Gerrard and Andrea Dossena secured a 4-0 second-leg win over Los Blancos at the same stage of the tournament.

Since then, Real has twice inflicted agony on Liverpool in European finals, most recently in 2022 when Thibaut Courtois' goalkeeping heroics helped the club clinch a 14th Champions League title.

There was also 2018 in Kyiv, a night largely remembered for Loris Karius' disastrous showing between the sticks. The German gifted Madrid two goals as Gareth Bale netted a hat-trick in the 3-1 win.

Nevertheless, such memories are resigned to the past and all eyes are fixed on securing a positive result.

Interestingly, too, American statisticians FiveThirtyEight have predicted that the Reds have a 41 per cent chance of winning the first leg. Carlo Ancelotti's team, though, are determined to be underdogs with just a 35 per cent chance of triumphing away from home.

It is also suggested that there is a 23 per cent chance that the encounter will end in a draw.

FiveThirtyEight takes into account several factors when making their predictions, including the Soccer Power Index (SPI) rating of each team.

They have been predicting the outcomes of major football leagues since 2017 using their specialist methodology.