This is our own statistical model: before kick-off, each team's strength comes from a global team rating built on our results — every league and cup on one scale, linked through European and other cross-league matches — blended with the league's own results when both teams play in it. During the match it is updated with the minute, the score, red cards and the last 15 minutes of pressure (a Poisson goal model with the Dixon-Coles correction for low scores). Without enough data on both teams we show no percentages. It is a probability, not a certainty.
Preview
Ironi Nesher FC vs Hapoel Nir Ramat HaSharon: preview
Ironi Nesher FC have won 4, drawn 0 and lost 1 of their last 5 matches. Ironi Nesher FC have scored in 12 matches in a row. 6 of Ironi Nesher FC's last 10 matches had 3 or more goals, and both sides scored in 6. Hapoel Nir Ramat HaSharon have won 3, drawn 1 and lost 1 of their last 5 matches. 5 of Hapoel Nir Ramat HaSharon's last 10 matches had 3 or more goals, and both sides scored in 6.
Our pre-match model estimate: Ironi Nesher FC 54%, draw 24%, Hapoel Nir Ramat HaSharon 22%.
Match simulation
Model estimate · 20,000 simulations
Preparing the simulation…
Model simulation (20,000 runs): Ironi Nesher FC win in 54% of the simulated matches, 24% end level and Hapoel Nir Ramat HaSharon win 22%. Average goals 2.6; the most likely score is 1-0 (13%); both teams score in 50%.
The percentages in this tab are estimates of the ScoreMondo statistical model, not certainties.
Ironi Nesher FC – Hapoel Nir Ramat HaSharon preview
Over the last 5 matches, Ironi Nesher FC have collected 4 wins and 1 defeat. Ironi Nesher FC have found the net in 12 straight games. Goals have flowed in Ironi Nesher FC's games: 6 of the last 10 produced at least three.
Recent form for Hapoel Nir Ramat HaSharon: 3 wins, 1 draw and 1 defeat in 5, with 6 goals for and 4 against. MS Dimona beat Hapoel Nir Ramat HaSharon 2-0 last time out. Across 10 matches, Hapoel Nir Ramat HaSharon have scored 1.8 and let in 1.1 goals per match on average.
This text is written automatically from our match data; every number and name in it comes from that data.
