Explaining our 2020 MLS playoffs projections

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Explaining our 2020 MLS playoffs projections

Predicting playoff outcomes in MLS has always been particularly difficult. While about 400 regular season games may seem like a lot, it is still not even close to enough of a sample size to home in on fine differences between teams through the data alone. And now, with a COVID-shortened season and fake home games, it’s even more difficult. With that said, here are our model’s predicted probabilities of each team making it to each stage of the MLS Cup Playoffs, along with the implied championship probabilities from the Bovada sportsbook and championship probability differences between the two. I’ll go over what we did to produce these predictions, and what missing information could make them better.

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Updated Playoff Seeding Projections

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Updated Playoff Seeding Projections

We have updated our playoff seeding projections on our web application, which show the probability that each team finishes in each playoff seed postion within its conference. We have done this in years past, but dedicated fans of the site will recognize that this is a bit earlier in the season than usual. Some tweaks to the predictive model have allowed us to publish meaningful predictions sooner! I’m here to tell you about those tweaks.

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Why the new MLS Playoff format doesn't create a more meaningful regular season

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Why the new MLS Playoff format doesn't create a more meaningful regular season

Major League Soccer has updated their playoff format for 2019 to a March Madness style single elimination tournament that will take roughly a month play out. The prior competition used a combination of single elimination and home and away ties over a month and a half period, and had long breaks in the action. The one clear benefit of this change is the shortened duration of the tournament. Avoiding the November international window will create a compact and uninterrupted tournament that should improve the momentum of the story lines that emerge.

The new format is also supposed to benefit the higher seeds, as the single elimination games will give advantage to the home teams, versus the old method of home and away legs for each team. This seemingly makes regular season games more important. More Victory! [Insert scratching record sound here]. These types of simplifying statements make my geek antenna start to hone in on theoretical galaxies of mathematics. Sadly, the only off switch I have for my antenna is my keypad and a Google docs session. So let’s dig in and deconstruct this new tournament bracket and see who benefits and who does not.

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Playoff Seeding Probabilities Model

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Playoff Seeding Probabilities Model

Starting yesterday, you will find playoff seeding probabilities in our web app. We show the probability that each team finishes in each playoff seeding position in its conference, as well as the Supporters’ Shield probabilities for all teams.

What is this based on? Well, it’s a two-part process. First, we built a model capable of predicting the probabilities of future game outcomes based on team performance to date. Then we set up a simulation to randomly determine outcomes for all the remaining games this season, with probabilities derived from that predictive model. For each of 1,000 simulated seasons, we tallied each team’s final points, wins, and goals scored and allowed, and seeded the teams in each conference. Then we figured out what proportion of those 1,000 seasons each team finished in each place.

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Playoff Probabilities 2017

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Playoff Probabilities 2017

Today we're happy to debut our playoff probabilities and seeding probabilities for 2017! It will also show up as an option in the upper right corner of ASA until the end of the season.

As in our 2016 iteration, playoff probabilities come from a combination of where teams are now in the tables, what their remaining schedule is, and how good our model thinks they are. The remaining games of the 2017 season were simulated 10,000 times based on win-loss-draw predictions for each game. The probabilities and averages given below are calculated from those simulations.

You'll notice that we're missing a Supporter's Shield column this year - that's because in all 10,000 of our simulations Toronto won it. To reiterate just how great Toronto's season is going, on the final weekend of the season last year we still had a 35.7% chance that Colorado would win the Shield.

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Playoff Probabilities

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Playoff Probabilities

You may have noticed that yesterday we debuted our playoff probabilities for 2016! It will also show up as an option in the upper right corner until the end of the season.

As in our 2015 iteration, playoff probabilities come from a combination of where teams are now in the tables, what their remaining schedule is, and how good our model thinks they are. The remaining games of the 2016 season were simulated 10,000 times based on win-loss-draw predictions for each game. The probabilities and averages given below are calculated from those simulations. A bit more in-depth explanation follows:

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Conference Final Home Teams Have A First-leg Up

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As you probably know, we've been projecting the MLS playoffs after each round of games. Using a bivariate Poisson model, we simulate goal scoring based off our expected goals model. Given that goals are an essential ingredient for emulating soccer's two-legged system, this has proven quite important, and the conference finals are no different.  

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MLS Playoff Projections

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Now that're through the first round and leg-one of the quarterfinals of the MLS Playoffs, we just want to remind you about our projections for each subsequent round. The odds you see of teams advancing through the semis take into account the leg one results. The "Change" column tells how much the most recent actual result (i.e. the leg-one results) has altered the model's projection for each club's likelihood of winning MLS Cup 2015.

Throughout the playoffs, you can find our model's predictions under the "Projections" tab in the upper right. We're updating them the day after each round of games.

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MLS Playoff Projections

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By Matthias Kullowatz (@mattyanselmo)

In preparation for the beginning of the MLS Playoffs on Wednesday, we're rolling out projections for each subsequent round. Throughout the playoffs, you can find them under the "Projections" tab in the upper right. First, let's take a look at what our simulation spit out, and then I'll explain what the simulation was thinking.

Team Quarters Semis Finals Cup Winners
NYRB 1.000 0.672 0.445 0.326
CLB 1.000 0.511 0.197 0.130
MTL 0.632 0.331 0.139 0.089
VAN 1.000 0.554 0.288 0.089
FCD 1.000 0.526 0.270 0.082
NE 0.496 0.211 0.099 0.064
TOR 0.368 0.145 0.082 0.051
LA 0.429 0.227 0.126 0.043
POR 0.591 0.257 0.117 0.039
SEA 0.571 0.242 0.106 0.033
SKC 0.409 0.195 0.092 0.028
DCU 0.504 0.130 0.037 0.026

The simulation is designed to follow the new MLS Playoffs format. Two-legged series, which occur in the conference semifinals and finals, are modeled using simulated scores from a bivariate Poisson model. This allows us to both precisely project outcomes, and to update the probabilities after game one of such a series. 50,000 iterations of the MLS Cup Playoffs are run, and the outcomes from those iterations are summarized to produce the projections you see above.

It should come as no surprise that the Red Bulls are far and away the most probable team to win the Cup. They have dominated our power rankings for weeks, and their 32.6% chances at winning the cup line up very closely with what we gave 2014's favorite LA Galaxy (33.4%) and 2013's favorite Sporting KC (30.2%). New York led the league in both actual goals scored and expected goals scored, and the model has found that goal scoring is more predictive of future success than goal allowing. This is why they have topped our power rankings for so long.

It should also come as no surprise that D.C. United received our worst probability of winning the Cup. Despite home-field advantage, DCU is only given 50.4% chances of beating New England in their play-in game. DCU's expected goal differential is bad, and their actual goal differential is surprisingly bad. They are the only playoff team with a negative xGD, and the only playoff team with a negative GD. In other words, even if you don't subscribe to how xGoals handles DCU, actual goals doesn't like them either. 

I think seeing Columbus and Montreal with the next-best chances of winning the Cup is a bit confusing at first, but it actually makes perfect sense. If either of those teams has to face NYRB, they will do so in a two-legged series where home-field advantage is largely stripped away. On the other coast, whichever Western Conference team makes the final has a good chance (44.5%) of playing in New York in that one-game championship. Essentially, when and how you play New York largely determines your probability of winning the Cup.

Speaking of home-field advantage, we account for it with two processes. First, the model knows who's playing at home, and adjusts outputs accordingly. That has been true with our Playoff Push all season. Second, the two-legged series are set up such that if teams tie on goals, and on away goals, they will play two 15-minute overtime periods followed by penalty kicks if necessary. Additionally, that will only happen on the higher seed's turf. Our simulation determines if such an aggregate-tie occurs, and then indirectly gives the home team (also the higher-seeded team) a slight advantage in extra time. We regress the home team's 90-minute probability of winning, conditional on not-tying, halfway back toward 50%. This is an approximation to what FiveThirtyEight has done with extra time, where the better teams are still given advantages in what is not a 50-50 outcome.

Anyway, enjoy the playoffs! And check back for updated projections. 

Introducing Playoff Seeding Projections

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As you've probably seen under the Projections tab in the upper right, for the last couple months we've been keeping the odds for each MLS team's chances at making the playoffs and winning the Supporters' Shield. 

Our playoff probabilities come from a combination of 1) where teams are now in the tables, 2) what their remaining schedule is, and 3) how good our model thinks they are. It's the same model that produces the Power Rankings, but the key difference is that here we take each team's current standing and remaining schedule into account.

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