This week in our 1.HNL series we will display Dinamo Zagreb in numbers through this data analysis. Because of coach changes at the club, we decided that tactical analysis is not the best option right now. Using statistics and data we will analyze Dinamo as a team, but will analyze players compared to the other players as well.
Dinamo easily won the league title and had room to experiment with young players and players who played a small amount of games. They will pursue Champions League group stage once again through qualifications, but they could face department of some key players which they will have to replace. Dinamo already signed Lokomotiva duo: Lirim Kastrati who impressed last two seasons in 1.HNL and Fran Karačić who waited for transfer to bigger club given his performances in the last few seasons. That gives us a hint that probably Petar Stojanović who played less in the second part of the season, will be sold and there are rumours that Serie A side Bologna is interested in Slovenian right-back services. From wingers, there is a lot of rumours surrounding Croatian international Mislav Oršić who was connected with possible new EPL side West Brom on winter window. Other players who could be in high demand are: Bruno Petković, Amer Gojak, Nikola Moro and Dominik Livaković. Dinamo won’t sell them all cause they have Champions League ambitions, but after recent events, they will probably look to balance their finances by selling players.
Team performance
We will start with team performance compared to the other teams in 1.HNL. Dinamo dominated this season and even that they won only once in the last 5 game weeks they are 14 points above second-placed Osijek. The graph below will show us how they look in terms of points won and expected points per match.
We could assume Dinamo won the most points per match (2.24). Dinamo has the highest expected points value of 1.9 per match as well. That gives us 76 points in 34 matches, which would be probably more if they had real competition this season which would push them to be more motivated and rotate less, but given circumstances that they won league few months in advance, it is reasonable that they slow down.
Second graph we gonna analyze is xG for and against per 90. This will help us see how many quality chances they create and allow per match.
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