Poor Damage Player Performance Predicts Match Outcome

Competitive Discussion
1

The tl;dr

It appears that the performance of the worst-performing Damage player in a Role-Queue Competitive match is a very strong predictor of match outcome. Specifically, if a team in the standard role queue composition (one Tank, two Damage, two Support) has at least one Damage player who finishes the match with an elimination-death ratio of 1.2 or less, that team will usually lose the match. This effect manifested regardless of whether the low-performing player was on the observer’s team or the opposing team.

The Motivation: Stats Are Not Everything, But They Do Mean Something

Blaming your team is not a good look, but the temptation can be strong. Overwatch is fundamentally a team-based game, and teams don’t win that don’t work together effectively. There are many dimensions to what it means to work together effectively: parity of team member knowledge, communication and timing, character composition of the friendly and opposing teams, mindset and group affect. However, an individual player’s ability to contribute to the team is fundamentally limited by their ability to execute effectively in their role. A Support who doesn’t heal is no use, a Tank who can’t hold ground can’t contribute to a win, and a Damage player who can’t get eliminations is ultimately just feeding. This observation raises a natural question: How much can a single player’s performance contribute to the outcome of a match?

We should be cautious about constructing an answer. Causal attribution in a complex system is very tricky, and even a single match of Overwatch involves dozens of dynamics woven across members of both teams. However, anyone who has ever been in a game with a blatant thrower can attest: it is definitely possible for a single player to ruin the game. If one player can ruin the game through deliberately poor performance, it would seem reasonable to infer that one player could also ruin the game through organically poor performance. Certainly, these forums are alive with numerous anecdotes of matches ruined by incapable teammates. The trouble is, such anecdotes don’t resolve into a clear picture of what might actually be happening. After all, people blame their teammates on all sorts of occasions and for all sorts of reasons, many of them self-serving and ill-founded. How could we know if matches were really being ruined by inept teammates, or whether the game community was simply overrun with sore losers?

This question takes on new urgency as grievances mount around the obscure and erratic behavior of the Overwatch 2 matchmaker. Many complaints focus on allegedly large disparities in the skill of teammates and opponents, far beyond what one would expect in matches made according to estimated player ability. The complex, team-based mechanic of Overwatch makes it difficult to quantify what exactly “skill” means – but there is a distinct feeling in the air that something is very wrong with the relative skill levels in many of the matches made.

The purpose of this project was to answer the question: Is there an objective measure of player performance that can predict the outcome of a game? Since Overwatch 2 made whole-game stats available during the match, I had begun to foment the suspicion that I was being frequently matched with low-performing Damage players. Certainly, the symptoms seemed to be there: enemy flankers roving about unchecked in the back lines, violent but one-sided firefights that somehow never advanced, positions that seemed to abruptly fold under even light attack. But it’s easy to see what you want in a game, especially when you’re frustrated and looking to make sense of it – and there’s a strong psychological bias to shift blame away frome one’s self. When I looked at the scoreboard in losing matches, though, I began to notice that my team often had at least one Damage player struggling to get kills. The pattern seemed very consistent. As a Support main, though, I couldn’t get past the obviously conflicted interest that I might have in seeing a failure in the other roles: maybe I was cherry-picking observations? So, at the start of Season 3, I resolved to record the outcome of every competitive game I played in the Support queues, along with a neutral observation: Did either team have a Damage player whose number of eliminations came at a ratio close to their number of deaths?

What follows are my observations thus far.

The Methodology

Between Feburary 07 and February 23 of 2023, I played 103 games of Competitive Overwatch, in the Support queue. For all of these matches, I queued alone, without a group. After the Season-start deranking, I began at a visible rating of Bronze 5, rising to Bronze 2 in the middle of the observational period, and falling eventually to Bronze 3. I did not count games in which a player left early enough for the match to be cancelled without a result. I did record games in which a player left before match-end, if the departure happened late enough that the match was allowed to continue.

For each match, I recorded the following data in a spreadsheet:

  • Date of the match
  • Time at which the match ended
  • Duration of the match
  • Map played
  • Match outcome (win or loss)
  • Whether a player on my team left before match-end
  • Whether a player on the opposing team left before match-end
  • Whether a Damage player on my team finished the match with an elimination-death ratio less than 1.2
  • Whether a Damage player on the enemy team finished the match with an elimination-dath ratio less than 1.2

The last two of these points are the ones of most interest for this discussion.

The choice of 1.2 as the cutoff for a judgment of “poor” performance was admittedly arbitrary, but chosen to reflect a relatively narrow standard. This particular number derived from my occasional observations in Season 2, and I do not assert that it is the “correct” or “optimal” threshold – only that it is an observable feature that seems to separate the data into two distinct groups. For those not doing the arithmetic: a ratio of 1.2 is equivalent to 6 elminations for every 5 deaths, e.g. it would correspond to elimination death ratios of 6-5, 12-10, 18-15, and so on. For instance, a Damage player ending the match with 13-11 would qualify as “poor” under this criterion, since 13 divided by 11 is roughly 1.18, whereas a player ending with 13-10 would not, since 13 divided by 10 is 1.3. Since getting an elimination point on the board is relatively easy in Overwatch (you only need to touch a target with damage shortly before it expires), I reasoned that even a middling Damage character performance should be able to do better.

(Technical note: I would really have preferred to calculate the threshold by way of a logistic regression on the actual scores. However, it is extremely cumbersome to record the necessary data. Although the game reports under the “Career Profile” menu recently feature a tab with the final scoreboard, I have observed that the scores listed are often wrong – blatantly wrong, in that they all-zeroes for most rows of a finished game.)

The Numbers

My team won in 48 percent of the matches observed (49 out of 103) and lost 52 percent (54 out of 103). None of the observed matches ended in a draw.

Of the matches observed, including both wins and losses, 66 percent (68 out of 103) involved at least one Damage player with an elimination-death ratio of 1.2 or less. For the sake of brevity in the remaining discussion, I will refer to these players simply as “poor-performing DPS”. Those players were split across both my own team and the opposing team: In 39 percent (41 out of 103) of games, I was matched with a poor-performing DPS, and in 30 percent (31 out of 103) of games, I was matched against a team with at least one poor-performing DPS.

To the point: How did the presence of a poor-performing DPS correlate with match outcome?

When I was matched with a poor-performing DPS on my own team, the match ended in a loss 90 percent of the time (37 out of 41 games). When I was matched against a team on which there was at least one poor-performing DPS, that team lost (i.e. my team won) at a comparable rate: nearly 90 percent of the time (28 out of 31 games).

It is worth noting that some matches ended with neither team exhibiting a poor DPS, and some ended with both teams exhibiting a poor-performing DPS. Games in which both teams had a poor-performing DPS were rare within the sample: only 4 matches out of the 103 observed (about 3 percent). Games in which neither team had a poor-performing DPS were observed at a higher incidence, but still represented only a minority of observations: 35 out of 103 (33 percent of all matches). Of the games in which neither team had a poor-performing DPS, the observer’s team (i.e. my team) won 57 percent of the time (20 out of 35 matches).

Some Hypotheses and Cautions

It is striking that the presence of a poor-performing DPS on a team correlated with a loss for that team 90 percent of the time, and even more striking that the effect was observed regardless of the side to which the player was matched. Support mains have long argued that it is arduously difficult to rank up through solo queuing, and this finding is evidence in favor of that claim. Certainly, if Support mains are making observations similar to these, they could not be blamed for concluding that inept Damage players are costing them wins. However, one should excercise caution before jumping to such a conclusion: correlation is not causation, and while the elimination-death ratio of Damage players correlates with game outcome, it is not necesarily the cause of a loss. There are other potential explanations for a poor elmination-death ratio which might also explain a losing game without appeal to that individual player’s skill: perhaps they were outclassed by a Damage player on the opposing team due to poor matchmaking, or perhaps they were matched with inept Supports who failed to keep them in the fight. However, a low skill level relative to the other players in the game is a straightforward explanation nonetheless. Given the poor quality of matchmaking thus far, it is difficult to dismiss the proposition that players will relatively low skill are being matched into games at a high rate, and that these matches have a strong influence on the outcome.

It is also striking to note the substantial difference between the observed sample’s global win rate versus the win rate conditioned on the absence of any poor-performing DPS players: a 48 percent win rate versus a 56 percent win rate. Because these are my own matches, it is difficult to generalize this result; doing so would require not only determining what contributions, if any, I might have made to the appearance of a poor DPS performance (e.g. maybe I’m a bad Support, and they died because of me), but also determining what my win rate would be if matched with only “similarly skilled” players (whatever that might mean). However, if you are a Support main struggling with the question of whether it is your own performance or that of your teammates that is holding you back, you might consider recording similar data, and calculating the difference between your win rate under various conditions of friendly- and enemy-team performance. This study represents only a single data point with respect to the larger question of player performance in general, but it is a point that indicates that Damage player performance can substantially drag down the win rate of a solo-queuing Support main.

It is also worth nothing that players queuing for Damage might enjoy an advantage to their win rate for purely combinatorial reasons: If I queue for Damage, there is only one other Damage slot on my team that could be filled by a “poor” player. If I queue for a different role, there are two such slots. For that reason alone, I will encounter fewer poor-performing DPS players on average, which should correlate with a higher incidence of wins for my team. This observation is in line with a somewhat longer explainer that I posted previously.

While the data accounts for whether the poor-performing DPS appeared on the observer’s team (i.e. my team) or on the enemy team, it cannot tell us whether this effect appears at a similar strength in other parts of the MMR curve. In particular, it would be interesting to see at what rate poor-performing DPS players appear in higher or lower MMR matches. While MMR itself is hidden, we could potentially reach some conclusions if we had similar data from a broad sample of players.

Even without attributing a cause, the fact that poor DPS performance predicts game outcome suggests courses of action whereby players might improve their win rate. If the scoreboard shows a Damage player failing to keep up, the rest of the team could prioritize taking action to remediate that player’s struggle. For instance, Support players could take a more aggressive posture with respect to getting key eliminations, or could prioritize healing the struggling player (at least when feasible to do so). Alternately, a poor ratio might give an early indication that the player in question could benefit the outcome by switching characters. If the team has good communication and trust, more experienced members could take the stats as cue to coach the struggling player into more effective tactics while match time still remains. These conversations can be fraught, but sometimes people really do listen.

Conclusion

There is strong evidence that the lowest elimination-death ratio of a Damage player in a Competitive match correlates with match outcome, when that ratio drops below a certain threshold. This effect was observed on both the friendly and the enemy team, suggesting that the effect was not produced by the observer. In games where neither team exhibited a Damage player with an elimination-death ratio less than 1.2, the observer’s team won at a much higher rate (56 percent) than in games in which the observer’s team exhibited a poor DPS (10 percent win rate), which supports the claim that Damage player performance greatly influences match outcome.

Appendix: CSV of the Original Data

For anyone who wants to run the numbers themselves and knows what to do with a CSV, here’s the original data as CSV-formatted text:

(begin CSV)
date,stop_time,duration,outcome,teammate_left,enemy_left,poor_friendly_dps,poor_enemy_dps,map
2023/02/07,23:33,16:04,L,1,0,0,0,Paraiso
2023/02/08,0:26,10:08,L,0,0,0,0,Antarctica
2023/02/08,0:43,6:58,L,1,0,1,0,New Queen Street
2023/02/08,0:59,11:05,L,0,0,1,0,Paraiso
2023/02/08,1:18,14:47,L,0,0,0,1,Blizzard World
2023/02/08,22:36,18:00,W,0,0,0,0,Havana
2023/02/08,22:58,18:24,L,0,0,1,0,Paraiso
2023/02/08,23:16,11:51,W,0,0,0,0,Shambali Monastery
2023/02/08,23:30,9:55,W,0,0,0,1,Ilios
2023/02/08,23:41,7:17,W,0,0,0,1,Junkertown
2023/02/09,0:29,11:13,L,0,0,1,0,Lijiang Tower
2023/02/09,0:44,10:36,L,0,0,1,0,Havana
2023/02/09,1:03,12:42,L,0,0,0,0,Blizzard World
2023/02/09,1:14,5:59,W,0,1,0,0,Antarctica
2023/02/09,1:21,10:21,L,0,0,1,0,Colosseo
2023/02/09,1:52,18:27,L,0,0,0,0,Midtown
2023/02/10,22:18,6:07,L,1,0,1,0,Lijiang Tower
2023/02/10,22:33,11:04,L,1,0,1,0,Paraiso
2023/02/10,22:51,13:31,W,0,1,0,1,Midtown
2023/02/10,23:02,4:19,L,1,0,1,0,Esperanca
2023/02/10,23:23,17:13,L,0,0,1,0,Shambali Monastery
2023/02/11,0:55,10:48,W,0,0,0,0,Colosseo
2023/02/11,1:10,L,1,0,0,0,Blizzard World
2023/02/11,1:38,22:58,W,0,0,0,0,Rialto
2023/02/11,2:05,7:11,W,0,0,0,0,Nepal
2023/02/11,10:42,13:25,L,0,0,1,0,Dorado
2023/02/11,22:02:00,17:06,L,0,0,0,0,King’s Row
2023/02/11,22:56,11:29,L,0,0,0,1,New Queen Street
2023/02/11,23:14,13:40,W,0,0,0,0,Midtown
2023/02/11,23:23,6:09,W,0,0,0,1,Colosseo
2023/02/11,23:38,10:54,L,0,0,0,0,Esperanca
2023/02/12,0:38,12:37,W,0,0,0,0,Paraiso
2023/02/12,0:57,14:54,W,0,0,0,0,Havana
2023/02/12,1:15,13:11,W,0,0,0,0,Nepal
2023/02/12,1:27,7:10,L,0,0,1,0,Antarctica
2023/02/12,1:42,12:16,W,0,1,0,1,Esperanca
2023/02/12,1:56,7:03,L,0,0,1,0,Oasis
2023/02/12,2:18,10:26,L,0,0,1,0,New Queen Street
2023/02/12,2:39,17:57,W,0,0,0,1,King’s Row
2023/02/12,15:57,9:45,L,0,0,1,0,Blizzard World
2023/02/12,16:08,8:34,L,0,0,1,0,New Queen Street
2023/02/12,16:43,13:14,W,0,1,0,0,Paraiso
2023/02/12,17:08,20:15,L,0,0,1,1,Rialto
2023/02/12,18:27,16:26,W,0,0,0,0,Shambali Monastery
2023/02/12,18:51,20:04,W,0,0,0,1,Rialto
2023/02/12,23:58,6:03,W,0,0,0,1,Antarctica
2023/02/12,0:20,18:20,W,0,0,0,0,Havana
2023/02/13,23:35,10:37,L,0,0,1,0,Esperanca
2023/02/13,23:54,15:43,W,0,0,0,1,Paraiso
2023/02/14,0:33,6:37,L,0,0,1,0,Havana
2023/02/14,0:53,14:56,W,0,0,0,0,King’s Row
2023/02/14,1:01,10:41,L,0,0,0,0,Esperanca
2023/02/14,1:23,11:53,W,0,0,1,0,Ilios
2023/02/14,1:46,15:25,L,0,0,0,0,Junkertown
2023/02/15,23:59,11:43,L,0,0,1,0,Oasis
2023/02/19,0:41,5:12,L,0,0,1,0,Esperanca
2023/02/19,0:52,6:33,W,0,1,0,1,Numbani
2023/02/19,1:06,9:38,L,0,0,1,0,Ilios
2023/02/19,1:20,10:06,W,0,0,0,1,Oasis
2023/02/19,1:30,5:59,L,0,0,1,0,Midtown
2023/02/19,1:51,16:37,L,0,0,1,0,Dorado
2023/02/19,14:17,5:49,L,0,0,1,0,Esperanca
2023/02/19,14:45,24:48:00,L,0,0,0,0,King’s Row
2023/02/19,15:12,19:20,L,0,0,0,0,Midtown
2023/02/19,15:40,10:20,L,1,0,1,0,Paraiso
2023/02/19,22:43,17:30,L,0,0,0,0,Blizzard World
2023/02/19,23:08,17:31,L,0,0,1,0,King’s Row
2023/02/19,23:27,10:44,L,0,0,1,0,Circuit Royal
2023/02/19,23:27,7:57,L,0,0,1,0,Ilios
2023/02/20,0:12,8:33,W,0,0,0,1,Nepal
2023/02/20,0:32,14:14,W,0,0,0,1,Midtown
2023/02/20,0:48,13:17,L,0,0,1,0,Dorado
2023/02/20,1:06,10:18,W,0,0,0,0,Antarctica
2023/02/20,1:30,11:07,W,0,0,0,0,Colosseo
2023/02/19,1:53,17:01,L,0,0,1,0,Havana
2023/02/20,2:06,8:16,L,0,0,1,0,Oasis
2023/02/20,2:22,12:20,W,0,0,0,1,Ilios
2023/02/20,13:45,10:20,W,0,0,0,0,Colosseo
2023/02/20,14:04,13:11,L,0,0,1,0,King’s Row
2023/02/20,18:40,8:29,W,0,0,0,1,Ilios
2023/02/20,19:01,13:30,L,0,0,1,0,Nepal
2023/02/20,19:36,13:27,W,0,0,0,1,Havana
2022/02/20,22:12,4:55,W,0,0,1,1,New Queen Street
2022/02/20,22:24,7:59,W,0,0,1,1,Junkertown
2022/02/20,22:39,8:17,L,0,0,1,0,Ilios
2022/02/20,22:48,6:16,W,0,0,1,1,New Queen Street
2022/02/20,23:09,8:26,W,0,0,0,0,Lijiang Tower
2022/02/20,23:27,11:43,W,0,0,0,1,Paraiso
2022/02/20,23:42,12:07,L,0,0,1,0,Nepal
2023/02/21,10:45,23:32,L,0,0,0,0,Rialto
2023/02/21,10:59,6:43,W,0,0,0,1,Antarctica
2023/02/21,11:24,12:18,W,0,0,0,1,Havana
2023/02/21,11:42,10:55,W,0,0,0,1,Colosseo
2023/02/21,11:59,12:15,W,0,0,0,1,Oasis
2023/02/21,22:39,23:23,L,0,0,0,0,Shambali Monastery
2023/02/21,23:00,8:15,W,0,0,0,1,Circuit Royal
2023/02/21,23:16,12:23,W,0,0,0,0,Ilios
2023/02/21,23:29,7:09,W,0,0,0,1,Junkertown
2023/02/21,23:44,11:33,L,0,0,1,0,Oasis
2023/02/23,0:27,17:35,L,0,0,0,0,Dorado
2023/02/23,22:39,7:44,W,0,0,0,1,New Queen Street
2023/02/23,22:51,6:59,W,0,0,0,1,Junkertown
2023/02/23,23:16,10:41,W,0,0,0,0,Oasis
(end CSV)

6 Likes
2

It goes tank, then damage as the two most important roles imo. Tank needs to be able to make space and the dps need to be able to capitalize on the space the tank makes to get picks. You can not die and heal 20k in 15 mins and still lose if your tank and damage can’t do their job on par with their enemy counterpart. You can usually tell if your dps will be capable within the first few team fights.

With that said, everyone can have a bad early game, but if they aren’t doing close to their counterpart by like team fight 3, yeah, you prob gonna lose.

1 Like
3

homie just wrote a scientific paper, where are your sources??? jk

4

this is all wrong.

tank is the most important by far, then supports, then dps

one weak dps won’t change the game as much as a weak tank

2 Likes
5

I generally agree with your point, and I don’t think the original post contradicts your view. My point isn’t that only Damage players’ performance can result in a bad game, only that when there is bad Damage player performance, it correlates with a loss.

The Tank is extremely important, and I do not mean to suggest otherwise.

The reason i didn’t write “Poor Tank Performance Predicts Match Outcome” is that it’s much harder to quickly and objectively quantify what “poor” performance means for a Tank. I know it when I see it, and it sounds like you do too – but not everyone might agree on every case, and it’s much harder to separate “fair” from “poor” by a clear and consistent threshold. By contrast, a Damage player who is dying almost as often as they get an elimination is almost certainly failing in their role, and there’s no two ways about it.

While one could, in theory, do an exhaustive analysis of replays – and while that would be a very interesting finding – I would have to develop a protocol for evaluating Tank performance and then play ~100 games and then watch ~100 replays, and I just didn’t have that kind of time.

Sure did :rofl:

Seriously though: the forums are full of opinions, and I got tired of some of them. Opinions take zero effort, and there’s far too many.

See first response: My point isn’t that only poor Damage player performance predicts a loss, nor is it that Damage player performance predicts a loss better than other factors. Yes, the Tank is very important, maybe even the most important. I don’t disagree, and neither does the original post.

It’s entirely possible that the poor Damage indicators in the data above were even caused by the failure of the tank to e.g. hold reasonable and appropriate tactical space. It’s just that the Damage numbers are clearly observable and measurable, whereas the blame that could be laid on the Tank is harder to disentangle from other factors.

So, it’s not wrong, just surprising. Unless otherwise noted, I’m just telling you what I saw.

2 Likes
6

A thesis on OW2, intense.
Didnt read it all, but Ive seen sooo many bad dps lately. are they bots? they dont know the heroes they pick, they dont know maps.
They run str8 into gunfire or eat nades to the face.
They have no idea how to take down targets, just completely ineffective and easily outhealed by other team.
Ive found I can win alotta matches in a row, but then I HAVE to lose just as much in the end. the 50/50 rule

2 Likes
7

well yes, that’s because it’s a team game

dps can only do it’s job if you have a proper tank and support…

2 Likes
8

I can often predict the outcome of my matches if my DPS is never captalizing on any of the damage I have done to the opposing tank, supports, and/or DPS. Also if I’m getting less healing than the opposing tank. More often than not, the opposing tank always outlives me despite how much damage I know I’m outputting and how better and consistently I’m mitigating the damage being dealt to me. I’ve opened the way for my DPS to one shot what remaining health I’ve done to several heroes, even eliminated 3 heroes out of 5 in an exchange only to find that my own team was somehow all gone themselves. Supporters staying far away from both DPS and tank and healing only each other. DPS not following close to me despite me not being at a range that would be considered a hard push.

It’s gotten to the point to where I have to somehow perform as a tank in such a way that almost inspires my team to focus up and it’s often by being the only one who can be relied on to eliminate most of the opposing team. But even that can be impossible, I’ve had terrible stats just due to either 3/5ths of my team not understanding their roles or characters or the synergy is just not there no matter what I try. Other times I keep getting teammates that can never reliably play a single character properly and change at least 7 times within a single round. I even had my performance hindered because my support kept trying to play as aggressors more than supporters and died in many situations where that wasn’t necessary because my support had no situational awareness to make sure that their team was healed up regardless if they were standing right in front of them.

Overwatch has made all these changes but it’s clear that it hasn’t improved anything in regards to how people learn or play. Worst is that people keep experimenting or learning in ranked when they need to be doing it in Quick Play and it’s very obvious to spot those types of players too.

1 Like
9

Now do this but with running support numbers.

It’s not so easy to pick a stat like elims.

But for reference you could use deaths / 10min (supports in general should have less deaths / 10 min than their dps)

Or heals/10 min (>1k per min is “good”… below is “bad”)

1 Like
10

The variance in DPS players in a match seems to be quite high compared to supports or even tanks.

11

Personally, I wonder how much of this has to do with an influx of new players. There are many more characters to choose from in the Damage role than in Tank or Support, which potentially makes it a more attractive choice. Regardless of reason, the queue times consistently suggest that Damage is much more popular, and more players translates into more opportunities for the skill level of matches to vary.

What I’ve long suspected (but have not proven) is either that the variance in skill for Damage players is wider, or tends to skew toward the low end. A lot of anecdotal reports, like yours, support that idea, but it’s hard to prove without access to any of the hidden data.

You are, of course, right. Which is why I would re-emphasize a point from the OP: Damage player performance correlates with match outcome, but there is not enough information here to claim with any kind of certainty that Damage player performance causes the outcome. It would seem like a stretch to claim that a poor Damage player never sinks a match – but it would be very reasonable to point out that poor Damage performance might be a sign of failures by other players on the team.

Out of curiosity: Can you see this in the stats? Or do you observe it in some other aspect?

That’s frustrating, for sure, but also shows that you have a well-developed situational awareness, and that you’re doing the right things. It’s like the iconic Doomfist pre-match conversation (paraphrased):

[To Brigitte] A strong leader adapts to their team, not the other way around.

What’s especially frustrating is that I see a lot of people openly suggesting that Supports play this way to escape the lower ranks. Whether it leads to rank up or not, it makes for some bad team dynamics.

Honestly, yes, I would love to do this. The biggest difficulty has been methodological: it might be possible to untangle a feature set from the final scoreboard, but it’s a pain to actually get those numbers and enter them, and that has stopped me from doing it so far. That, and the fact that I’ve been playing Support almost exclusively in Season 3, and if I’m going to do that sort of study, I feel like it would be better to do it from the perspective of a non-Support role. (Which I could – I’ve been both a Tank and a Damage main long ago, in the very old days of Overwatch.)

I might conjecture that a useful feature would be “healing done as a ratio of enemy damage output”. That’s still a little imprecise, but it would account for the fact that the raw healing stat isn’t informative by itself. (Some folks might recall that, in the OW1days of “medals” and post-match “cards”, there was an occasional card reflecting just this statistic, though it didn’t always appear.)

I suspect, however, that a much stronger (but much harder to capture) feature would be: How many deaths did the Support prevent? There’s a lot of technical reasons that would be hard to measure (as evidenced by the weirdness and unreliability of the “Saves” statistic for Support heroes), but it would come much closer to representing one of the more important aspects of what Supports do. After all: I could pump 1000 healing into DvA while she dives the enemy line, but if everything goes sideways and she dies without accomplishing anything, those 1000 points mean nothing. By contrast, if I could say, “I kept X hero alive long enough for them to hold this position or succeed at this play,” that would be huge!

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This is a great post. Thank you for putting in the effort to compile this from your games.

This is an important distinction for people replying to understand.

I think intuitively we all know that if your damage players don’t kill enough then you won’t win. So, it’s good that your data supports that.

The question is, what next? The challenge is that you can’t control the variables. Maybe if you could control 9 players and have one pug rotate in each time you could draw some more conclusions but there are just too many variables. Hero choice. Player mental state. Skill differences.

At the end of the day though, what actions can one take to improve their odds? As a support, I find the better damage player and prioritise them. Is that a good strategy or is it better to have one more player alive but not contributing much more than being a target/distraction.

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I think an interesting stat to track and compare to victory would be:

Tank deaths (lost teamfight) vs support player deaths .

Track as a ratio and then whether they won or lost…

Basically, find some way to compare support death rate vs victory.

It’s easy to track and not something subjective.

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I read the whole thing. Very well written.

I’ve noticed this pattern myself on Support. Many of my losses are due to an observable DPS skill gap, whether it’s because they are lower ranked than the opposition, have poor mechanics, or choose the wrong heros for the situation. Of course, there are things I could’ve done better myself. But it’s hard to pin all the blame on yourself when your DPS has 2k damage and 20 deaths.

It’s usually only one DPS player who is underperforming, in my case. Often I’ll get a carry DPS while the other is dead weight, relatively speaking.

Interestingly enough, you can see the same pattern you’re describing here when you queue for Tank or DPS. You see many underperforming Supports. I once had an 86 elim game on Soldier where my Mercy touched me with her blue beam maybe 5 times. Imagine if I was a bad Soldier in that situation?

It seems to me that the matchmaker pairs one underperforming DPS/Support with an overperforming DPS/Support in an effort to balance the game. I don’t have data at hand to confirm this. It’s just something I’ve observed over 5 years of playing. I don’t believe it was always like that, though.

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It’s a combination of stats and observing the situation as it happens then making a deduction after 1-3 different exchanges.

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yes, the matchmaker seems to never give you 2 good dps

it’s always one good dps and one bad one

just makes the game no fun to play

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I think the devs mentioned somewhere that they pair players up in this way on purpose, but I’m not sure.

I see it pretty much every game. Far too often to be a mere coincidence.

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Love you studies into overwatch would be interesting the see one regarding the predictability of games based on who had the significantly better tank based on some kind of criteria of your choosing for what defines better

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What I’m tired of, as a Support player, is these objectively bad Damage players being heal sponges, bringing no value to the team, and still having the most inflated egos. “Heal???” “If only I got HEALS we could have won.” “can i have a Mercy???” jfc. I’m sick of it. I hate babysitting them. Even if you put them on life support with Mercy, they are terrible. They never improve because they never see things rightfully as THEIR FAULT.

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I press “I need healing” if I drop below 100. I wait, I might still peek but I’m effectively out. I know I’m annoying.

But my kdr is crazy.

What annoys me… I’ll be at 20 hp after a team fight and my supports who died are catching up to me back from spawn in a “group up”. They don’t heal me. And that worries me and infuriates me… why?

Either they don’t know I’m at 20 hp. They don’t have the proper settings or not aware of the indicators.

Or they don’t care.

At least 1 heals me. So going back to poor dps. Usually I can’t maintain pressure if I don’t get healing. I don’t get healing cause the healers are bad or the tank is bad.

So before we blame dps, you have to look at all roles and their performances.

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