Martin Odegaard: exceptional talent or YouTube sensation?

Article by Sam Green

A player that has caught the eye of many clubs and football fans over the last few months, arguably due to his youth and YouTube-friendly attacking skills is Martin Odegaard (a quick YouTube search brings up films with nearly 2.5 million views). In August 2014, Odegaard made history when he became Norway’s youngest ever player, representing his country in a friendly against the United Arab Emirates at 15 years and 253 days. Since his international debut last summer, Odegaard became the youngest player to play in a European Championship qualifier, playing against Bulgaria in a 2-1 victory.

Following training ground tours of some Europe’s most prestigious clubs, Odegaard has since signed for Real Madrid, and has stated that, should Carlo Ancelotti decide to select him for the first team, he’d be “really happy”.

Creative players and goalscorers such as Odegaard are at a premium (the relative infrequency of goals compared to crosses, passes, tackles and other aspects of football demonstrates this in its simplest form) and subsequently attract more attention, hence many clubs’ desire to attract a player of Odegaard’s reputation and supposed potential.

Clearly, signing for the European Champions after just 23 games for Stromsgodset in your mid-teens is not the standard career path for many footballers. But actually how good is he? Many players’ video highlights have made them look like potential superstars, but can we expect Odegaard to thrive in Madrid?

Thanks to Opta’s detailed Norwegian league data, we can take a more objective, detailed look at Odegaard’s performances, analytically focusing on his attacking output and contribution in the final third of the pitch using the ‘Expected Assists’ and ‘Total Goals Added’ metrics, developed by our analytics team.

Expected Assists

Traditionally we have ranked creative players purely on the volume of key passes and assists they generate but ‘Expected assists’ offers a deeper understanding into the actual quality of the chances a player is creating. ‘Expected assists’ will value the difference between a lay-off 30 yards out and a through ball that puts a forward in one-on-one with the goalkeeper. Disregarding whether the chance was converted and the abilities of the goalscorers they are playing alongside, the metric allows us to rank the players who create the best quality opportunities for their teammates based on on-the-ball data.

A ranking of players with the best expected assist figure should, in theory, show the top creators. A player who has more actual assists than their expected assists demonstrates how clinical their attacking team-mates are. For instance, this recent blog indicates a portion of Cesc Fabregas’ assists from recent seasons may be owed to the finishing abilities of his Chelsea and Barcelona team-mates, whereas it’s likely Odegaard’s Stromsgodset teammates may not be of as high a calibre, which would influence his actual assists total. Therefore, by using this metric we can hope to understand a bit more about a player’s true creativity.

Table 1. Expected Assists per 90 minutes 

This table showcases top five players in Europe, ranked by Expected Assists per 90 minutes.

Rank Name Comp(s) Team(s) Position Mins Expected Assists/90 minutes
1 Franck Ribéry GER FC Bayern München Attacking Midfielder 4460 0.384
2 Sadio Mané AUT, ENG FC Red Bull Salzburg, Southampton Winger 3751 0.315
3 Luciano Narsingh NED PSV Winger 3218 0.312
4 Luis Suárez ENG, ESP Liverpool, Barcelona Second Stricker 6705 0.284
5 Dusan Tadic NED, ENG FC Twente, Southampton Winger 7745 0.284

All players have played over 3000 minutes. Set piece situations removed from the sample

Table 1 provides an interesting mix of players: recognised elite players like Ribéry and Suarez mixing with two new Premier League signings (kudos to Southampton’s recruitment team) and Luciano Narsingh, a Dutch international.


Rank Name Comp(s) Team(s) Position Mins Expected Assists/90 minutes
N/A Martin Odegaard NOR Strømsgodset Attacking Midfielder 1454 0.248


Based on the Expected Assist ratio above, young Martin Odegaard’s creativity in the final third is not to be ignored. With much hype surrounding the Norwegian international, his statistics make for an interesting comparison. If Odegaard’s figures continued with more minutes on the field, his expected assists would sit him at 10th place in this table of Europe’s creative players, sandwiched between Cristiano Ronaldo (0.253) and Dries Mertens (0.244) and sitting above Lionel Messi (0.212) and Gareth Bale (0.188).

Interestingly though, the diverse range of clubs represented in this table indicate Odegaard’s statistics are not simply a product of a perceived weaker national league.

Conversion rates

However, what stands out beyond his ability to create is his ability to score. In what is of course still a fledgling career, any conclusions drawn should include a disclaimer, but Odegaard’s start to life as a professional footballer is impressive, and after a quick look at table 2, it becomes easy to understand why so many clubs reportedly showed an interest.

Table 2. Conversion rates

Table 2 shows player conversion rates, based on their success over 100 shots.

Rank Name Comp(s) Team(s) Mins Conversion / 100 shots*
1 Franck Ribéry GER FC Bayern München 4460 7.6
2 Antonio Cassano ITA Internazionale, Parma 6093 6.79
3 Arjen Robben GER FC Bayern München 3717 6.44
4 Theo Walcott ENG Arsenal 3213 6.32
5 Cesc Fàbregas ESP, ENG Barcelona, Chelsea 6566 5.94

Minimum playing time of 3000 minutes. * Non-deflected, non-dead-ball Shooting Goals Added


Focusing exclusively on players’ finishing rates, Franck Ribéry again sits at the top of the pile; perhaps this is not a surprise for one of the senior players of one of Europe’s strongest sides, who have been particularly dominant in their domestic league.

Using these figures as a guide (and taking in to account the very large caveat that Odegaard has played very little in comparison), Odegaard has made an extremely impressive start to his goal-scoring career.

Rank Name Comp(s) Team(s) Mins Conversion / 100 shots*
N/A Martin Odegaard NOR Strømsgodset 1454 16.49


Odegaard’s strike rate of 16.49 is, for want of a better word, striking. Such high figures in this department indicate the player, despite his young age, could be a competent goalscorer.

Of course, these numbers aren’t necessarily repeatable and the figure is hugely influenced by Odegaard’s limited playing time compared to the rest of the field (Odegaard’s data is based on 1454 minutes, whereas Franck Ribéry has notched up over 4000 minutes). However, this impressive start to his career makes it easy to understand why he has attracted so much attention.

Overall attacking output

Finally, we can take a closer look at attacking output, a metric that combines expected assists from open play and Shooting Goals Added (taken from non-deflected shots from open play). This is shown in the ‘ATK/90’ column in table 3.

Table 3. Top 10 players: Attacking output / 90 minutes.

Measured in goals. Scores based on chance creation and added goal probability.

Rk Name Comp(s) Team(s) Age Pos Mins Fin / 100 shots* Expected Assists / 90 mins** ATK ATK / 90
1 Franck Ribéry Ger FC Bayern München 31.8 Att Mid 4460 7.6 0.384 25.7 0.518
2 Arjen Robben Ger FC Bayern München 31 Winger 3717 6.44 0.228 15.8 0.384
3 Luis Suárez ENG, ESP Liverpool, Barcelona 28 Second Striker 6705 3.75 0.284 28.5 0.383
4 Cristiano Ronaldo ESP Real Madrid 29.9 Striker 6687 3.69 0.253 28.2 0.379
5 Dries Mertens NED, ITA PSV, Napoli 27.7 Winger 4934 5.81 0.244 19.3 0.353
6 Kevin Kampl GER2, AUT VfR Aalen, FC Red Bull Salzburg 24.3 Att Mid 4261 4.69 0.28 16.2 0.342
7 Lionel Messi ESP Barcelona 27.7 Second Striker 6700 5.17 0.212 25.5 0.342
8 Cesc Fàbregas ESP, ENG Barcelona, Chelsea 27.7 Cent Mid 6566 5.94 0.266 23.8 0.326
9 Jonatan Soriano AUT FC Red Bull Salzburg 29.3 Striker 3670 3.6 0.233 12.5 0.308
10 Hulk POR, RUS FC Porto, Zenit St Petersburg 28.5 Winger 4973 5.39 0.198 16.8 0.304

* Non-deflected, non-dead-ball shooting goals added
** Open play expected assists/90. Minimum playing time of 3000 minutes


Rank Name Comp(s) Team(s) Age Position Mins Fin / 100 shots* Expected Assists/90 minutes ATK ATK / 90
N/A Martin Odegaard NOR Strømsgodset 16.1 Attacking Midfielder 1454 16.49 0.248 6.5 0.401


Unsurprisingly, the top 10 European-based players listed in this table has a more familiar look to it. However, Odegaard’s performances and output again rank him as one of Europe’s most effective attacking players when disregarding the threshold for minutes played. His efficiency in front of goal and ability to create a goalscoring chance puts him right up with the royalty of European football, second only to Ribéry.

Obviously, the figures outlined above should not necessarily be seen as a guarantee of sustained success. However, Martin Odegaard has made more than a promising start to his career. His contribution to Stromsgodset IF is evidently not only at a level much higher than his peers within his club, but also across the vast majority of European football.

It’s clear therefore that Real Madrid are not just signing a player that looks quite good on YouTube. The monikers bestowed on Odegaard, heralding him as one of the brightest attacking talents in Europe, may not be too far wide of the mark.

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