Methods

Our goal with this project was to develop a “Contested Possession Metric” — a composite statistic designed to reflect a player's in-game contributions that either win the ball or secure possession.

In homage to club legend Brian Schmetzer, we started with a stat he frequently emphasizes: duels won. An aerial duel is defined as a challenge between two players to gain control of the ball above elbow height (typically with the head). We assigned the value for an aerial duel won at +1.

A tackle in soccer represents when a player challenges their opponent with their feet for a ball on the ground (or at least below the elbow), a game event markedly similar to an aerial duel won and often yielding the same results. Tackles are the rarer event, though — across our eight seasons players average 0.98 tackles won per 90 against 1.25 aerial duels won — so valuing them identically let the more common event do more of the talking. We value a tackle won at +1.5.

To account for aerial duels lost we assigned a value of -0.85. This weighting ensures that an aerial duel lost does not fully offset an aerial duel won. Every aerial duel has one winner and one loser, so the league as a whole wins exactly half of them; what these two values really set is the win rate at which a player breaks even, and at -0.85 that rate is 45.9%. Players with a 50/50 split are still credited for actively contesting possession, even when they don't win the ball. (Unfortunately, tackles lost are not available in the source data. More on that below.)

After aerial duels and tackles won, the next most valued statistic for this metric is interceptions. An interception occurs when a player gains possession of the ball after an opponent passes, crosses, or shoots before the ball can reach the intended target. While this game event is not a result of a direct physical challenge for the ball, the player wins the ball through positioning, reading game flow, and anticipating ball movement, as such interceptions are valued at +0.9. An intercepted ball is also the cleanest evidence of possession genuinely kept — the player has it under control with no scramble — which is the second half of what this metric is trying to see.

The final statistic weighted by the algorithm is recoveries. A recovery represents any action that ends a spell of possession by the opposition and starts possession for the player's team. Recoveries are valued at +0.25 — the lowest of the five, because a recovery is the one event in the set where the ball was already loose. Nobody was beaten. It is also by far the most common event we count, making up more than half of everything in the database, so a higher value drowns out the duels this metric exists to measure.

We chose these weights to prioritize direct challenges (duels and tackles) while still recognizing off-ball efforts (interceptions and recoveries) that affect possession dynamics. The final Schmetzer Score is the sum of the weighted values for each statistic.

In the source data a player was listed twice if they played for multiple teams in a season (this could be the result a number of scenarios including contract terms, inter-league trades or loans within the league). This could effectively lower the rank of a player as their statistics would be distributed across multiple teams. To capture the full picture of a player's performance over the season, a player's statistics are consolidated to the squad with which the player played more minutes (i.e. higher value in nineties.)

When tabulating the season average of any given statistic, we exclude players with less than five games worth of minutes (450 minutes, or five 90s). Though all players are ranked, regardless of how many minutes they played. This decision was made to ensure that the season average is a more accurate reflection of the average for players who genuinely featured in a particular season — a lower threshold pulls in too many brief cameo appearances and drags the league average down.

Fine-Tuning the Weights

The values above are not the ones we launched with. In 2026 we reviewed every weight against the full database — 5,876 player-seasons from 2018 through 2025 — and adjusted four of the five.

The problem the review found is that a weight is not the same thing as an influence. Recoveries carried the smallest weight and the largest effect, simply because there are so many of them: 339,947 recoveries in the database against 66,056 tackles won. More than half of every point the Schmetzer Score awarded was a recovery, and the score correlated far more strongly with recoveries than with duels. A metric named for duels won was not primarily measuring duels. Halving the recovery value brings it from 55% of all points awarded down to 32%.

Raising tackles won to +1.5 answers the mirror-image problem. Because tackles are both rarer and more tightly clustered than aerial duels, matching them at +1 gave them noticeably less pull on the rankings. Valuing a tackle at the average-volume ratio would mean +1.27; giving tackles genuinely equal say would mean +1.89. We took the middle of that range rather than the top, because tackle counts turn out to be the least stable statistic we track — they move with a team's defensive scheme more than the others do, dropping most sharply when a player changes clubs.

Interceptions rose to +0.9 on the strength of what they say about keeping possession, while staying clearly below tackles because no one is beaten in a contest. And the aerial penalty moved to -0.85 so that the aerial term measures how well a player competes in the air rather than how often. At -0.75 a player broke even by winning just 42.9% of their duels, which quietly paid for volume; at -0.85 the break-even is 45.9%, still under the 49.2% a median contested player manages, so contesting is credited and losing badly is not.

These changes rearrange the middle of the table more than the top. The retuned ranking still agrees closely with the original one, because a season total is driven first and foremost by how much a player featured; four or five names change in a given season's top 25. Ball-winning full-backs and holding midfielders rise, while players whose score was mostly loose-ball volume — including goalkeepers, whose totals are almost entirely recoveries — fall. One consequence worth stating plainly: because four of five values went down, every score in the app is now lower than it was, and season averages fall by roughly 16%. That is a change of scale, not a change in anyone's standing.

Salary & The Schmetzer Value Metric

A Schmetzer Score says how much contested possession a player won. It says nothing about what that work cost. So alongside each player's score we carry their publicly disclosed compensation, sourced from the MLS Players Association Salary Guide. The salary column shows annual average guaranteed compensation — base salary plus all signing and guaranteed bonuses, annualized over the term of the contract.

The $/smetz column divides that compensation by the player's Schmetzer Score: what a club paid for each point of contested possession, so lower is better. It is left blank for a score of zero or below, where there is nothing bought to divide by. Players are ranked on it only once past the same five 90s threshold used for season averages — without a floor, a single substitute appearance on a league-minimum contract would top the table on a handful of duels.

Two things are worth keeping in mind when reading it. It measures contested possession per dollar and nothing else, so a designated player signed to score goals will always look poor on it — that is a statement about what the Schmetzer Score counts, not about the player. And clubs are not on a level field: MLS roster rules mean a homegrown player on a league-minimum deal does the same work for a fraction of the cap hit, so the metric tends to reward clubs that develop and play their academy.

The MLSPA publishes salary info each season and that data does not share a player id with our statistics source, so players are matched by name within their club. Roughly 91–97% of ranked players in a given season carry a salary. A player showing “—” either left the league before the release was compiled or could not be matched with confidence; we show nothing rather than a guess.

Data Source, Limitations, & Further Development

Our source data came from the amazing folks at FBref  (the source data set for this project) and Sports Reference. They're doing incredible work, democratizing sports data by making it publicly available. One current limitation is the granularity of available statistics. While providers like Wyscout break down duels into 4 types (offensive duels, defensive duels, loose ball duels, and aerial duels) FBRef lists only aerial duels won or lost as well as tackles won. Tackles lost, as well as duel types beyond aerial, are not available in this dataset.

While this is a limitation of the current iteration of this application, fortunately the data architecture is modular and the ETL pipelines could be pointed at a new data source in the future. This data could also be combined with field position to ascertain if a player tends to win or lose possession in specific zones on the field or during certain patterns of play. We also have under development fine tuning controls which would allow a user to manipulate the default values which weight the Schmetzer Score. This feature is live! Try fine tuning the weights of statistics using the Tuning button.

Read more about the inspiration that sparked this project on the About page.
Meet the two developers behind this project on the Team page.

Update: March 2026

Unfortunately, as of January 2026, the advanced statistics that made this project possible are no longer publicly available. Opta terminated Sports Reference's access to its data feeds, citing an alleged agreement violation, ending free access to the advanced statistics that aspiring sports data analysts and soccer fans had come to love.

As a result, further development beyond the 2025 MLS season will not be possible until a new data source can be identified. We're exploring alternatives, and the modular architecture of the ETL pipeline means the platform can be repointed at a new source without a full rebuild. In the meantime, Duels Mapping remains fully functional as a historical record, offering insights into player performance and league trends from 2018–2025.