i'm talking about the numbers Of matches ..disputed ...for them in career Official Matches only Pelé 812 matches .... or 825 matches ???? Puskas .... 719 matches or 792 matches ???? Messi 1069 matches ???? Cruyff 709 matches ... or 720 matches ????
Is Interesting at all ! Edson Arantes .Pelé ... 819 matches ... 487 assists ... 0, 59, 46 % Lionel Messi ............. 1069 matches .... 458 assists .... 0, 42, 84 % Johan Cruyff .............. 709 matches ..... 458 assists .....0, 64, 59 % Ferenc Puskas ......... 719 matches ... 440 assists ..........0, 61, 19 %
yes ... Lionel Messi ... Ferenc Puskas .. Johan Cruyff Could you tell me in which seasons Messi, Puskas, Johan Cruyff did triple-doubles in the Leagues they played in??? for example ... Ruud Gullit 1986/87 Ballon D'or season Eredivisie year (annual ) 34 matches .... 22 goals ... 21 assists .... 10 pre-assists .. Puskas ... Cruyff and Messi did it in the seasons ??? for example Puskas ... 58/59 and 59/60 or others ...???? Cruyff 68/69.. 69/70 ... 70/71 ... 71/72 ????
Clutch Goals: Goals that put the team ahead, like a 1-0, and goals that equalize the score, like a 1-1 when trailing Maradona 195/342 (57.02%) Ibrahimovic 304/561 (54.19%) C.Ronaldo 448/895 (50.06%) Messi 369/838 (44.03%) Di Stéfano 217/514 (42.22%) Puskás 277/710 (39.01%) Cruyff 150/401 (37.41%) Clutch Goals/Assists First 65 Matches Clutch Goals/Assists First 100 Matches Here's something interesting... 2 players could participate in 50% of a team's goals, but one could participate in important goals and another could score when the team is already winning... If we analyze it carefully, that 50% of the first player is worth more than the 50% of the second player. If we consider that scoring 1-0 is worth more than 6-0, then clutch goals are worth more. For exmple, (counting penalty goals and only Opta assists) Maradona has a team's goal contribution of 51.52% and Puskás 49.04%...very close, but... for Maradona 56.78% of his G/A were clutch while for Puskás 38.71% of his G/A were clutch This means that it could be said that although both players are close to 50% of participation in their team's goals, Maradona has participated in goals of greater value.
So it would be factually correct to say cristiano Ronaldo has more clutch goals(448) than Ronaldo Nazario had total goals in his career(414)? To score 900~career goals is one thing. For 50% of them to be clutch is a superhuman feat and almost fiction. Never to be seen again
The two caveats I would genuinely offer would be: a) for analysing clutch goals I think it would be informative to also look at clutch assists at the same time (of course players can also be key in helping score goals and/or playing very well before a goal is scored in terms of getting some initiative and momentum, but in terms of the tangible end product the assists would be the key other thing to study I guess, even if looking at the goal footage sometimes pre-assists would be more impressive and/or crucial in making the goal). b) I think a goal to go 2-0 or 3-1 or 4-2...or 7-5 etc etc is still in most cases 'clutch'. Arguably teams can and have come back from being down 2 or even 3 goals, but I would at least think going 2 goals up would be generally a big advantage, and that unless a team is way over-matched and has no real ambition or confidence to go forwards they would still feel 'in the game' at just one goal behind. I guess to some extent clutch % could be likely higher on teams with less stars too as an aside, and on teams that score less goals overall. Not to dismiss the idea of looking at it, but yeah I guess Puskas having various world class team-mates including in the goal scoring department, and playing in high scoring teams in a high scoring era, could make having a high clutch goal % less likely in itself (but it makes it easier to have a high overall goals+assists tallly of course on the other hand).
The best team a fully fit Diego Maradona ever played for in Europe(in terms of goalscoring) was Barcelona 1982/83 In all competitions he scored 23 goals This was his highest ever scoring tally in a single season playing in Europe 4 of those goals were match winning goals 17% https://www.transfermarkt.co.uk/die...=&pos=&minute=&pos=&torart=&stand=gamewinning When the quality of his teammates goes up the clutch ability takes an epic nosedive Another thing to look at Clutch ability via Penalties Club statistics only Diego Maradona(in Europe playing for FC Barcelona,Napoli and Seville) 45 match winning goals 16 penalties 35.5% of his match winning goals were penalties Diego Maradona - All goals | Transfermarkt Diego Maradona - All goals | Transfermarkt Vs his rivals/contemporaries Sir Kenny Dalglish 56 match winning goals 0 penalties 0% of his match winning goals were penalties Sir Kenny Dalglish - All goals | Transfermarkt Sir Kenny Dalglish - All goals | Transfermarkt Ruud gullit 65 match winning goals 1 penalty 0.01% of his match winning goals were penalties Ruud Gullit - All goals | Transfermarkt Ruud Gullit - All goals | Transfermarkt Micheal laudrup 34 match winning goals 1 penalty 0.03% of his match winning goals were penalties Michael Laudrup - All goals | Transfermarkt Michael Laudrup - All goals | Transfermarkt karl heinz rummenigge 73 match winning goals 2 penalties 0.03% of his match winning goals were penalties Karl-Heinz Rummenigge - All goals | Transfermarkt Karl-Heinz Rummenigge - All goals | Transfermarkt Michel platini 74 match winning goals 9 penalties 12.1% of his match winning goals were penalties Michel Platini - All goals | Transfermarkt Michel Platini - All goals | Transfermarkt Marco Van basten 75 match winning goals 11 penalties 14.6% of his match winning goals were penalties Marco van Basten - All goals | Transfermarkt Marco van Basten - All goals | Transfermarkt Lothar matthaus 57 match winning goals 16 penalties 28% of his match winning goals were penalties Lothar Matthäus - All goals | Transfermarkt Lothar Matthäus - All goals | Transfermarkt His research is built on deducting,dismissing and undermining the worth of penalties And now it all falls like a deck of cards Penadona
The only one who can touch him(in the illusion of being clutch) was Roberto baggio 76 match winning goals 28 penalties 36.8% of his match winning goals were penalties https://www.transfermarkt.co.uk/rob...os=&minute=&pos=&torart=204&stand=gamewinning Even if it is undeniably true that Roberto baggio had a knack for scoring spectacular goals(and spectacular goals vs great teams to a far greater degree than Diego Maradona) it is also undeniably true that Roberto baggio was extremely reliant on spot kicks dare I say to an almost unprecedented level almost a third of his goals were from penalties 101/318 Not everyone was convinced about him either Michel platini famously remarked he wasn’t good enough to be a 9 or a 10(called him a 9.5 lol) And maybe his over reliance on spot kicks to be a difference maker has a significant role to play in why Platini said what he said(a theory)
Yeah, as alluded to by ffff15 too, as with general goal contributions, it's good to see non-penalty stats to at least level the playing field for non-takers (not to take away everything from excellent penalty takers as such). On the flip side, without looking up/checking out the answer, Maradona's clutch assists in 1982/83 can be looked at I suppose and would add something to his clutch-end product for that season.
Without being sure, I don't know whether he was saying not good enough at either 9 or 10 or simply his role was '9.5' - he also said South Americans (including Pele who he rated/voted as the best or greatest) played as '9.5' players (not strikers, but not withdrawn midfield playmakers which he calls 10s I suppose...like himself...albeit Pele was obviously an iconic number 10 even if as he's said he started with Santos a bit more like a true number 9 in some respects, when Pagao was playing). https://www.bigsoccer.com/threads/interesting-best-xi.325564/page-68#post-42435436 Well, 9 and a half, or South American style number 10 as he calls it. I know the comment about Baggio was seen as a bit 'lukewarm' in terms of praise though, so I'm not sure exactly that there wasn't an element of criticism in it, but mainly I think he was saying he was in between a 9 and a 10 in terms of position/role/style (arguably it can be a good thing though I guess, like in the case of Pele indeed!).
I didn't look properly at the post to be honest - I see now assists are factored in. Although I also agree with a Twitter poster that it probably makes more sense to look at clutch % out of clutch goals scored by teams, not % of goals/assists of players that are clutch, because the second way is surely much more stacked to favour players on lower scoring teams indeed. On a further note, a goal to make the score 2-3, or even 1-3, whether or not the team completes the comeback, is in theory not less valuable than a goal to make the score 3-2 or 2-2, I think.
For a more complete picture, it should be goals and assists that led to victory. Following the criteria of non-opta assists (such as penalties suffered), i mean, offensive actions in the broad sense. Then you'd have the cluchts players. Maybe you also could open up to equalizing goals/assist. And g+a in decisions Just goals seems very specific
It penalizes players who: 1. Play for better teams and teammates. Someone who plays for worse teams will play more minutes under situations in which they can score these type of goals. If you play for a great team and already in 10th minute result is 1-0, you effectively have no more opportunity to score clutch goal by definition. This can not be an argument against the player. 2. Who are influencing games outside of goalscoring and assisting. Self-explanatory. If you want to do this further, you can do clutch goals per 90' or even if possible, clutch goals per 90' of being 1 down or equal (situations in which clutch goals happen). It would require to calculate how much player has played minutes in any game state (-3, -2, -1, 0, +1,..) then you can somehow compare them.
It doesnt matter if he knows it or not, I dont see it being mentioned at all even tho it is extrenely important. I dont think percantage would be better than per 90' of a match situation, because, again, strikers and players in the "stats role" will be overrepresented by virtue of their role in team. Hypothetically, percantages of clutch goals relative to team's overall would be great if there was a way to quantify expected percantage of clutch goals relative to team's overall. In that way, every player would be assigned expected percantage based on his role in the team and his actual perxantage would be compared to the expected number.. like with goals and xG. For example, it could be determined that Cruyff in a season played a role that would exepctedly yield 35% of clutch goals based on his role, and his actual number is 42%. 7% more than expected which would be better than Zlatan having 51%, while expected to have 58% based on his role. In theory, the expected percantage could be determined empirically (just like xG is determined), but it would be a daunting task that would need cross-checking data and fine-tunning. Rudimentary statistic (that is not available for most players) such is number of shots by a player relative to his team would be a decent, starting point indicator of the extent of his "stats role" in team. Player that has a high percantage of team's shots can confidently be reasoned to play closer to goal and have more of in a "stats role" for his team. Otherwise, any percantage stat relative to team's performance will fall into the same trap..
Another idea is not to calculate percantage of clutch goals by a player relative to his team's overall, but to calculate how much a player scores per 90 minutes for each match situation than compare numbers to himself or the standard trends for players. For example, if Maradona was scoring at rates: -2 - 0,35 per 90' -1 - 0,55 per 90' 0 - 0,52 per 90' +1 - 0,48 per 90' +2 - 0,45 per 90' +3 - 0,36 per 90' Now looking at this, you could reason that when matters the most, he is at high rates. This compeltely ignores percantages relative to his team and even his changing roles as well and compares his performance to himself regardless of role. In this way it is crucial to use per 90 minutes basis because for a palyer who plays in worse teams, his total number of goals in very favorable situations will be much lower because he played less time in such situations. And the opposite is true than, that he played more minutes in match situations of interest (-1, 0) therefore his total number of goals and percantage of them in such situation will be relatively bigger. The point is that the context in terms of how much player has played in certain match situation is essential to even begin entertaining such data.
Chatgpt can explain better than I can: Your ideas for evaluating "clutch goals" and the broader context of player contributions in different match situations are innovative and address key challenges in football statistics. Here's a breakdown of your concepts and how they could be applied or developed further: ### 1. **Definition and Importance of Clutch Goals** - **Clutch Goals**: Goals scored when the team is down by one goal or the score is tied. These goals are critical because they often have a significant impact on the outcome of the game. - **Current Metrics**: Traditional goal-scoring metrics do not always account for the context in which a goal is scored, potentially overvaluing or undervaluing certain players depending on their roles. ### 2. **Challenges with Current Percentage Stats** - **Role-Based Overrepresentation**: Strikers or attacking players naturally score more goals due to their position and role, making percentage-based metrics biased. - **Team Context Ignored**: Percentages of clutch goals relative to the team's overall goals can misrepresent a player's effectiveness since it doesn't account for their expected role or the game context. ### 3. **Proposal for Expected Clutch Goal Percentage (xCG%)** - **Concept**: Just as xG (Expected Goals) models are used to estimate the quality of scoring chances, xCG% could estimate the expected contribution of clutch goals based on a player's role, position, and other contextual factors. - **Methodology**: This would involve creating a model that looks at historical data, such as the number of shots a player takes, their position on the field, and their team's style of play. The expected percentage of clutch goals (xCG%) would be compared against their actual clutch goals to evaluate their performance. - **Application**: For instance, if a player's xCG% is 35% but they actually contribute 42% of their team's clutch goals, it indicates that they are performing above expectations in critical moments. ### 4. **Using per 90-Minute Metrics Across Different Match Situations** - **Player Performance by Situation**: Analyzing a player's goal-scoring rate per 90 minutes in different match situations (e.g., when the team is trailing by 1, the score is tied, etc.) provides a more nuanced view of their contribution. - **Comparison to Self**: By comparing a player's performance across different match situations to their overall performance, you can identify whether they perform better or worse in critical moments. - **Normalization**: This method controls for the amount of time a player spends in each situation, addressing the issue of players on weaker teams potentially having more opportunities to score in clutch situations simply because they are often trailing. ### 5. **Potential Statistical Models and Analysis Techniques** - **Empirical Determination of xCG%**: Just as xG models are based on large datasets of historical shots and outcomes, xCG% could be developed using data on when and where goals are scored relative to game situations, roles, and positions. - **Rudimentary Indicators**: Metrics like the percentage of team shots taken by a player can serve as a starting point to estimate their role in goal-scoring, which can then be refined into more complex models. - **Advanced Metrics**: With enough data, machine learning techniques could be applied to predict xCG% based on a variety of factors, including team tactics, player positioning, and opposition strength. ### 6. **Implications and Applications** - **Player Evaluation**: This approach would allow for more accurate evaluation of players in terms of their clutch performance, going beyond raw goal totals or percentages that can be misleading. - **Team Strategy**: Coaches and analysts could use these metrics to understand which players are most effective in crucial game situations, potentially influencing substitutions, formations, or strategies during matches. - **Comparative Analysis**: Players from different eras or leagues could be compared more fairly by normalizing their clutch performances relative to their expected contributions and the situations they encountered. ### 7. **Practical Challenges** - **Data Collection**: Developing these metrics would require extensive data collection, including detailed match events and player positions over many seasons. - **Complexity**: The models would need to be transparent and interpretable so that their insights could be effectively communicated to coaches, players, and fans. ### Conclusion The ideas you've outlined could significantly enhance how we understand and evaluate player performance, especially in crucial moments of the game. While implementing these ideas would be complex, the potential benefits for both player evaluation and team strategy are substantial. This approach would lead to a more nuanced understanding of what it means to be "clutch" in football, moving beyond simple goal counts to a more context-sensitive analysis.
I did a test with Messi in CA21-F22-WC22. In total, in 15 matches, the team scored 30 goals, and Messi scored 11 goals and made 10 assists, a 70% contribution. For clutch goals, argentina scored 16, and Messi was involved in 13, a contribution of 81.25%