Extremely proactive teams average 530 passes per match, while extremely reactive teams average 259. The ratio of passes in the final third also holds up consistently, 152 to 86. However, the types of passes made by each team has some notable differences.

Proactive teams use 5% more of their passes in the final third on crosses. If defenses are truly keeping their compact shape, then offenses generally work the ball out wide to the available space. More crosses make sense. Reactive teams strike 8% more of their passes 25 yards or longer (for our purposes, 25+ yard passes are called “long passes”). This is an indication of direct play. The longer passes leads to a lower completion rate. Don’t be fooled by the lower overall pass completion rate of reactive teams; the completion rate difference is due to risk-taking when they have possession. More direct passing comes with more risk as the passes are longer and are generally to players who are on the move. Proactive teams complete 15% more passes than their reactive counterparts.

While this analysis certainly isn't comprehensive or perfect, I do believe it allows accurate insight into how teams would operate at the extreme ends of the strategic spectrum.

Proactive Score

The goal is to develop a simple score that shows fans and analysts where on the spectrum a given team plays. To do that, I started with the variables that had the most spread in the analysis above. I didn't look at shooting statistics, as those measure an outcome of the style of play, not the style of play itself. The two strongest differences were total number of passes and long pass percentage. Of minor comfort is that a multivariate regression including total passes attempted, long passes attempted, and a home/away flag were all statistically significant in predicting possession of MLS teams at the game level with an Rsquared value of 70%.

That said, using passes to identify large spreads in possession is nothing short of obvious. But without Opta data, there are limited choices for fans to use to determine a team’s strategic intent.

After trying a combination of descriptive metrics and looking at the corresponding spread of results, I landed on using total passes attempted and two times long passes to create a score. While multiplying long passes times two adds complication to the formula, the larger spread does create more separation in the target metrics.

From there I scored a team’s performance on a scale of 1 to 7, with 7 being an extremely proactive team. The result when looking at the games in 2014 is a reasonably normal bell shaped curve.