Every Orlando City Player’s Impact Assessed

Brace yourselves, stat nerds, I’ve taken every outfield Orlando City player and broken down their “minutes per” team goals scored and conceded, split between that player being on and off the pitch to try and have an overview of every individual’s impact.

In simple terms, the four figures are calculated by taking the number of total minutes played and dividing it by the total number of goals Orlando City has scored while they have been on the pitch, the same for the number of goals conceded and then the same for when they weren’t on the pitch. For example, if someone was to play the whole 90 minutes in a 2–1 win, they would have a rate of 45 minutes per goal scored and 90 minutes per goal conceded. However, if Orlando had scored a stoppage time winner but a player had been substituted in the 80th minute with the scored tied at 1–1, they would register 80 minutes per goal scored and 80 minutes per goal conceded, but they would also have a 10 minutes per goal scored when not playing figure.

It’s by no means a foolproof method. Correlation is not causation is the old adage. There are plenty of other circumstances that combine to create this picture, but it can give us some insight into general trends over the course of the season. It isn’t particularly helpful for players with limited minutes either, but that has become less of a problem this season. Take Kyle Smith, for example, who spent the early part of the season as a stoppage time substitute and so would have seen an extreme figure of a goal conceded every two minutes were Orlando to concede during that brief appearance but exactly half of his 12 appearances have now come as a starter. This much rotation in the team makes these figures more illuminating as 18 different outfield players have five or more starts in MLS and 17 have clocked over 500 minutes, which gives us a fairer indication of trends. Only Santiago Patiño and the now-loaned out Josué Colmán have played fewer than 300 minutes in MLS this year.

Both data sets have been presented in charts. The team average is represented by a single yellow bar. Each player, meanwhile, has two bars. The blue bar represents the figure for when they do play, the red represents that figure for when they don’t. The shorter the bar, the quicker Orlando scores/concedes goals. Likewise, the longer the bar, the longer it takes.

To start with, let’s look at goals scored. In this instance, a shorter bar is better as it means the team takes less time to score. As a measuring stick, Orlando City as a whole has scored an average of a goal every 64.3 minutes. Cristian Higuita has the fastest minutes-per-goal rate of anyone on the team, with the Lions scoring an average of a goal every 46.9 minutes (shown in blue) with the Colombian on the pitch — eight goals scored in his 375 total minutes. Nani is not far behind, with a goal scored every 50.8 minutes the Portuguese DP is playing. Colmán, having played limited minutes before returning to Paraguay on loan, Chris Mueller, Lamine Sané, Tesho Akindele, Patiño, Uri Rosell, João Moutinho, and Dom Dwyer all also have a minutes-per-goal rate better than the team average.

Meanwhile, Carlos Ascues ranks lowest on the team, with the Lions scoring six goals during his 563 minutes played, a lowly rate of one goal every 93.8 minutes. The worst rate for a forward is Benji Michel, who scored his debut MLS goal in the Lions’ last game, but that was only one of four scores in total by the team during the rookie’s 307 minutes of playing time, giving him a rate of a goal every 76.8 minutes. Kamal Miller, Alex De John, and Will Johnson make up the bottom five.

In terms of goals scored without the individual on the pitch (shown in red), Orlando City unsurprisingly struggles without Nani. While the team scores every 40.8 minutes with him in the side, it only finds the net every 145.5 minutes when he is absent — a total of four in the 582 minutes he hasn’t played. Mueller is the only other player who has a goals-scored-without rate over 90 minutes. Sané, Akindele, Higuita, Rosell, Moutinho, Dwyer, Colmán and Patiño are the only other players who have a goals-scored-without rate slower than the team average.

The absence of Brazilian right back Ruan represents the team’s most fruitful spells, with the team scoring eight goals in the 418 minutes he has not played, a rate of one goal every 52.3 minutes. Johnson, Ascues, Miller, and Sacha Kljestan all have minutes-per-goal value faster than 60 when they do not play.

Perhaps most importantly, however, is that the chart is laid out in descending order of attacking impact (i.e., the difference between the two figures). As you can see, Nani has by far the biggest impact with the team, taking 95 fewer minutes to score when he is playing. Mueller is second, with the team 45 minutes better off, and central defender Sané has a positive attacking correlation to the tune of 30 minutes, while Higuita and Akindele round out the top five at 24 and 21 minutes faster, respectively.

At the other end of the scale, Ascues statistically correlates to have the biggest negative impact on the team’s goal scoring when playing, adding 38 minutes to Orlando’s goal rate. Defenders Miller, De John, and Ruan also make the bottom five, while of the non-defenders, Johnson and Michel have the next-worst effect at -20 and -15, respectively. Meanwhile, the likes of Danilo Acosta, Dwyer, Robin Jansson, and Méndez all show minimal difference with all four only seeing a difference of under +/-5.

Defensively, Orlando City has conceded a goal every 66.7 minutes over the course of its 20 MLS games so far this season. In this instance, a longer bar is better as it means opponents take longer to score. The team statistically is most defensively sound with Michel on the pitch, with teams taking 102.3 minutes to score (blue bar). In total, three goals have been scored by opponents during Michel’s 307 career MLS minutes. Higuita is the only other player with a conceded rate slower than 90 minutes. In terms of defenders, Smith comes out on top, with the team only conceding seven goals during his 575 minutes of playing time — a rate of a goal every 82.1 minutes. Jansson and Rosell close out the top five at 78.2 and 76.6, respectively, while Nani, Moutinho, Sané, Johnson, and Akindele also sit above the team average.

Meanwhile, the team statistically concedes fastest with Acosta on the pitch, conceding 12 in his 581 minutes, a rate of a goal every 48.2 minutes, with Kljestan and Shane O’Neill not far behind at 49.2 and 50.5 minutes, respectively. Colmán and Miller complete the bottom five, with the team conceding a goal every 51 and 58.5 minutes they play, respectively.

In terms of absences (red bar), Orlando City performs worst defensively in the absence of early season acquisition Jansson, conceding eight goals in the 315 minutes he has not played in — a rate of a goal every 39.4 minutes. Central partner Sané is the next defender on the list, with the team conceding every 55.1 minutes without him, while Nani, Moutinho, and Johnson round out the top five players who see the fastest goals conceded rate in their absence. Rosell, Smith, Higuita, Michel, and Akindele are the only other players to see the goals conceded rate drop below the team average in their absence.

At the other end, removing Kljestan is statistically the biggest defensive fix, with the team only conceding a goal every 127.5 minutes without him, nearly double the team average and the only player to have a goals conceded in their absence rate better than 90 minutes. In terms of defenders, O’Neill and Acosta are the two players with the best team defensive rate when removed, conceding every 84.1 and 81.3 minutes, respectively, with Méndez and Mueller rounding out the top five.

Again, the biggest indicator is perhaps the difference between an individual’s two figures. The most defensive improvement is seen with Michel on the pitch, with the team taking 40 minutes longer to concede. Jansson is not far behind, improving the team by 39 minutes, while Higuita, Nani, and Smith round out the top five. Sané, Moutinho, Rosell, and Johnson all statistically have a positive impact on Orlando’s defensive stability.

On the flip side, Kljestan correlates to be far and away the biggest defensive liability, with opposition teams taking 78 fewer minutes to score past the Lions with the veteran midfielder on the pitch. His closest teammates are defenders O’Neill and Acosta, who also have pretty dire figures at -34 and -33, respectively. Colmán, Méndez, Miller, Dwyer, Patiño, and Ascues are the remaining players that have noticeable negative correlations that would suggest the team is not as defensively solid in their presence. Ruan, De John, and Akindele all sit within a rather neutral +/-5 range.

Finally, combining the differences between both the goal scoring and conceding, we can start to evaluate a player’s overall impact. Nani comes out on top with a total impact score of 118 (+95 offensive, +23 defensive). The rest of the top five is made up of Higuita with 56 (+24 off, +32 def); Sané at 49 (+30 off, +20 def); Jansson at 37 (-2 off, +39 def); and, finally, Mueller with a score of 28 (+45 off, -17 def). Seven players have positive correlations for both offense and defense: Nani, Mueller, Sané, Higuita, Akindele, Rosell, and Moutinho.

Bottom of the pile is Kljestan, with an impact score of -88 (-10 offense, -78 defense), followed by Ascues (-38 off, -6 def) and O’Neill (-10 off, -34 def) with -44 apiece, Miller with -39 (-26 off, -13 def), and Acosta at -33 (-0.4 off, -33 def). A total of eight players have negative correlations for both offense and defense: Kljestan, Ascues, O’Neill, Miller, Acosta, Méndez, Ruan, and De John.

Again, I’ll stress that correlation doesn’t inherently prove causation. These figures can only give a general overview of trends that can be used in combination with other statistics as well as our overall eye test to better understand who makes this team tick and who is weighing it down. If you’ve read this far, you’ve earned a hearty thank you from me and I hope you enjoyed a slightly different take to stats that are published via the normal channels.